2026-04-24 04:57:14
A review of Rework by Jason Fried & David Heinemeier Hansson
\ Okay, so I picked this book up after a friend kept quoting it at me every time I complained about my job. I thought it was going to be one of those generic "wake up at 5 am and grind" type books. It is NOT that. It's actually kind of the opposite.
\ The book is written by the guys who built Basecamp (a project management tool). They basically wrote down all the things they believe about work and building a company, and a lot of it goes against pretty much everything you hear in startup culture.
\ Like, they straight up say planning is a waste of time. That working long hours is not a badge of honor. That you probably don't need investors. At first, I was a little skeptical, but by the end, I was like… yeah, these guys might be onto something.
\
The chapters are super short. Like, some are literally one page. At first that felt weird but honestly it's kind of great? You can read this thing in a few sittings and it never drags.
There’s a chapter called "Meetings are toxic" that I wanted to print out and stick to my monitor. The authors argue that a one-hour meeting with five people isn’t just one hour—it’s five hours. I’d never thought about it that way, and now I remember it every time I get a calendar invite.
\ Another thing they talk about is "scratching your own itch" — basically, build something you yourself would use. The reasoning is simple: if you're solving your own problem, you already understand it deeply. You don't need to do a ton of customer research to know what's missing. That felt really practical to me, especially as someone who's always had side project ideas but never knew where to start.
\ Oh, and there's a whole section on how "ASAP" culture is destroying focus. Every request being "urgent" means nothing is actually urgent. Again, painfully true.
Look, I'm not going to pretend this book is perfect. Some of the advice feels like it only works if you're already Basecamp, you know? Like, okay, cool, you don't need outside funding — but that's easy to say when your product already has paying customers. For someone just starting out with zero audience and zero revenue, some of this stuff reads a bit… idealistic?
\ There's also a chapter where they basically tell you to ignore your competitors entirely. And while I get the spirit of it — don't be paranoid, focus on your own thing — in practice? Completely ignoring what's happening in your market seems like a good way to build something that already exists.
\
I also felt like some chapters were kind of saying the same thing in different ways. Like there are three or four chapters that all basically boil down to "do less stuff." Which, ok, fair point, but you didn't need to say it six times.
If you work at a company that runs on meetings and 60-hour weeks and "move fast" mantras, this book will feel like a breath of fresh air. Probably read it in one or two sittings. It's not a long book, and it doesn't try to be.
\ If you're expecting a detailed how-to guide with frameworks and templates, you'll be disappointed. This is more of a mindset reset than a playbook. Think of it like a friend who's built a successful company coming over and telling you to chill out a little. Some of it you'll agree with, some of it you'll push back on, but the conversation is worth having.
\ I'll definitely be recommending it to people. Already texted my friend who keeps talking about starting a business and told him to read it before he writes a 30-page business plan that nobody asked for.
\ Rating: ★★★★☆ (4 out of 5). It’s worth your time, just don’t treat every word as gospel.
2026-04-24 04:44:09
New York, United States of America, April 23rd, 2026/Chainwire/--Threshold Network today announced Verifiable Bitcoin Accounts (VBA), a new framework for institutional Bitcoin deployment built on the same signer infrastructure that has operated with Bitcoin for six years, processed over $5 billion in cumulative volume, and sustained zero losses.
Verifiable Bitcoin Accounts are a Bitcoin Script and PSBT-based account framework for institutional Bitcoin deployment. They define preauthorized spending paths, signer combinations, timelocks, and recovery routes at account setup, allowing allocators to use Bitcoin-backed onchain strategies while preserving segregated custody workflows and verifiable settlement paths.
BTC remains with the holder's existing custody arrangement. VBA is compatible with Qualified Custodians such as Anchorage and Fireblocks Trust, MPC-based custody networks, and self-custody setups. No title transfer outside of their existing custody. Capital is held in a segregated account, not pooled, and is identifiable at all times. The custody relationship that the allocator already maintains governs every deployed position.
Built for Bitcoin Finance
Institutional Bitcoin lending is accelerating toward a projected $90B by end-of-2026¹, driven by stablecoin growth that reached $308B in early 2026 and is on track to exceed $1T². While major platforms are building proprietary lending stacks to capture the demand, Verifiable Bitcoin Accounts turn any existing custody - Qualified Custodian, MPC network, or self-custody - into institutional-grade lending infrastructure.
Onchain Bitcoin lending and yield markets depend on collateral that resolves reliably across liquidation, maturity, and redemption. Verifiable Bitcoin Accounts are built for that operational reality, with every settlement route agreed at setup and enforced in Bitcoin Script.
For allocators deploying Bitcoin into onchain lending at scale, this is the guarantee that makes the product usable.
The foundation of every Verifiable Bitcoin Account is the Partially Signed Bitcoin Transaction (PSBT), supported by the following features:
The signer infrastructure, Threshold Network, the protocol behind Verifiable Bitcoin Accounts, has operated with Bitcoin for six years, with over $5 billion in cumulative volume and zero losses. Verifiable Bitcoin Accounts is the extension of this proven, existing infrastructure.
Institutional adoption of Bitcoin in onchain markets does not scale on assurance alone. It scales on independent verification.
"Institutions don't need additional layers of trust; they need systems where outcomes are defined, enforceable, and verifiable from the outset. By removing reliance on counterparties, we align Bitcoin onchain with the standards institutional capital actually requires." — MacLane Wilkison, Co-Founder of Threshold Network
Verifiable Bitcoin Accounts (VBA) establish a new standard for institutional Bitcoin deployment: every component of the architecture can be verified before a single satoshi is committed.
Verifiable Bitcoin Accounts are available to qualified institutional participants. To discuss integration and explore deployment into approved onchain venues, users can contact the team via: https://threshold.network/contact
Threshold Network is the protocol behind tBTC, the trust-minimized Bitcoin bridge that has processed over $5 billion in cumulative volume across six years of mainnet operation with zero losses. Verifiable Bitcoin Accounts extend this infrastructure into institutional Bitcoin deployment, combining segregated custody, Bitcoin-enforced spending controls, and access to onchain lending markets. For more information, users can visit www.threshold.network.
PR
Threshold Labs
Threshold Labs
:::tip This story was published as a press release by Blockmanwire under HackerNoon’s Business Blogging Program
:::
Disclaimer:
This article is for informational purposes only and does not constitute investment advice. Cryptocurrencies are speculative, complex, and involve high risks. This can mean high prices volatility and potential loss of your initial investment. You should consider your financial situation, investment purposes, and consult with a financial advisor before making any investment decisions. The HackerNoon editorial team has only verified the story for grammatical accuracy and does not endorse or guarantee the accuracy, reliability, or completeness of the information stated in this article. #DYOR
\
2026-04-24 04:39:16
A couple of years ago, I wrote that The Builder pattern is a finite state machine! A state machine consists of states and transitions between them. As a developer, I want to make illegal states unrepresentable, i.e., users of my API can't create non-existent transitions. My hypothesis is that only a static typing system allows this at compile-time. Dynamic typing systems rely on runtime validation.
\ In this blog post, I will show that it holds true, with a caveat. If your model has many combinations, you also need generics and other niceties to avoid too much boilerplate code. My exploration will use Python, Java, Kotlin, Rust, and Gleam. With that background in mind, let's move on to the model itself.
I will keep the theme of the aforementioned post: a pizza. Here's the full model:
Every pizza starts with dough. Then, you need to choose your base, either regular tomato or cream. At this point, you can't add any ingredients to it. While you can add ham to both, pineapple is only acceptable on the tomato base, while potatoes are only compatible with the cream base.
\
The model is purposely simplistic, intentionally leaving out some options and complexities to maintain clarity. It primarily showcases how illegal transitions are represented and avoided. For example, you can't transition from CreamBase to CreamBase with withPineapple.
I chose to model with Python first to demonstrate how dynamically-typed languages manage illegal transitions.
\ Here are some types: \n
class Crust:
pass
@dataclass(frozen=True)
class ThinCrust(Crust):
pass
@dataclass(frozen=True)
class ThickCrust(Crust):
pass
class Base:
pass
@dataclass(frozen=True)
class CreamBase(Base):
pass
@dataclass(frozen=True)
class TomatoBase(Base):
pass
class Topping:
pass
@dataclass(frozen=True)
class Potatoes(Topping):
pass
@dataclass(frozen=True)
class Pineapple(Topping):
pass
\ The builders look like: \n
class DoughBuilder:
def __init__(self, crust: Crust) -> None:
self._crust = crust
def with_cream_base(self) -> "CreamBuilder":
return CreamBuilder(self._crust, CreamBase(), frozenset())
def with_tomato_base(self) -> "TomatoBuilder":
return TomatoBuilder(self._crust, TomatoBase(), frozenset())
class CreamBuilder:
def __init__(self, crust: Crust, base: CreamBase, toppings: frozenset[Topping]) -> None:
self._crust = crust
self._base = base
self._toppings = toppings
def with_potatoes(self) -> "CreamBuilder":
return CreamBuilder(self._crust, self._base, self._toppings | {Potatoes()})
def with_ham(self) -> "CreamBuilder":
return CreamBuilder(self._crust, self._base, self._toppings | {Ham()})
def with_olives(self) -> "CreamBuilder":
return CreamBuilder(self._crust, self._base, self._toppings | {Olives()})
def build(self) -> Pizza:
return Pizza(self._crust, self._base, self._toppings)
class TomatoBuilder:
def __init__(self, crust: Crust, base: TomatoBase, toppings: frozenset[Topping]) -> None:
self._crust = crust
self._base = base
self._toppings = toppings
def with_pineapple(self) -> "TomatoBuilder":
return TomatoBuilder(self._crust, self._base, self._toppings | {Pineapple()})
def with_ham(self) -> "TomatoBuilder":
return TomatoBuilder(self._crust, self._base, self._toppings | {Ham()})
def with_olives(self) -> "TomatoBuilder":
return TomatoBuilder(self._crust, self._base, self._toppings | {Olives()})
def build(self) -> Pizza:
return Pizza(self._crust, self._base, self._toppings)
\ You can happily write:
pizza = dough(ThinCrust()).with_cream_base().with_potatoes().with_ham().build()
pizza = dough(ThinCrust()).with_cream_base().with_pineapple().with_ham().build() # 1
Pineapple on a creamy base? Yuck!
\
Astute readers may have noticed that I used types in the Python code. Seasoned Python developers may use a type checker, e.g., mypy, to leverage them. \n
uv run mypy .
"CreamBuilder" has no attribute "with_pineapple" [attr-defined]
Without mypy, the call fails at runtime with an AttributeError.
\ Python's gradual typing proves that static typing helps avoid calling non-existent transitions. However, because of the way Python works, one needs to invoke a dedicated type checker. In statically-typed languages, it's unnecessary.
Let's do the same exercise with Java.
\ Here's the model:
public sealed interface Crust permits ThinCrust, ThickCrust {}
public record ThinCrust() implements Crust {}
public record ThickCrust() implements Crust {}
sealed interface BaseState permits CreamBase, TomatoBase {}
record CreamBase() implements BaseState {}
record TomatoBase() implements BaseState {}
\ And here are the builders:
public class DoughBuilder {
private final Crust crust;
private DoughBuilder(Crust crust) {
this.crust = crust;
}
public static DoughBuilder dough(Crust crust) {
return new DoughBuilder(crust);
}
CreamBaseBuilder withCreamBase() {
return new CreamBaseBuilder(crust, new CreamBase());
}
TomatoBaseBuilder withTomatoBase() {
return new TomatoBaseBuilder(crust, new TomatoBase());
}
}
class CreamBaseBuilder {
private final Crust crust;
private final CreamBase base;
private final List<Topping> toppings;
CreamBaseBuilder(Crust crust, CreamBase base) {
this(crust, base, List.of());
}
private CreamBaseBuilder(Crust crust, CreamBase base, List<Topping> toppings) {
this.crust = crust;
this.base = base;
this.toppings = toppings;
}
CreamBaseBuilder withPotatoes() {
return new CreamBaseBuilder(crust, base, append(new Potatoes()));
}
CreamBaseBuilder withHam() {
return new CreamBaseBuilder(crust, base, append(new Ham()));
}
CreamBaseBuilder withOlives() {
return new CreamBaseBuilder(crust, base, append(new Olives()));
}
Pizza build() {
return new Pizza(crust, base, Set.copyOf(toppings));
}
private List<Topping> append(Topping topping) {
return Stream.concat(toppings.stream(), Stream.of(topping)).toList();
}
}
class TomatoBaseBuilder {
private final Crust crust;
private final TomatoBase base;
private final List<Topping> toppings;
TomatoBaseBuilder(Crust crust, TomatoBase base) {
this(crust, base, List.of());
}
private TomatoBaseBuilder(Crust crust, TomatoBase base, List<Topping> toppings) {
this.crust = crust;
this.base = base;
this.toppings = toppings;
}
TomatoBaseBuilder withPineapple() {
return new TomatoBaseBuilder(crust, base, append(new Pineapple()));
}
TomatoBaseBuilder withHam() {
return new TomatoBaseBuilder(crust, base, append(new Ham()));
}
TomatoBaseBuilder withOlives() {
return new TomatoBaseBuilder(crust, base, append(new Olives()));
}
Pizza build() {
return new Pizza(crust, base, Set.copyOf(toppings));
}
private List<Topping> append(Topping topping) {
return Stream.concat(toppings.stream(), Stream.of(topping)).toList();
}
}
\
There's no way we can call withPineapple() on a CreamBase: We didn't declare the method, and compilation fails. However, imagine more combinations: an additional sweet base, or ingredients incompatible with others, e.g., no anchovies with pineapple. This would create additional states, represented as classes, and transitions, as methods.
\
Soon, you'll face an explosion of combinations, which would require lots of boilerplate code. For example, with the anchovies/pineapple exclusion, you'd need two more base classes: TomatoBaseWithPineappleBuilder and TomatoBaseWithAnchoviesBuilder.
\ Java is not a good fit for creating smart builders. Let's see if other languages may improve the situation.
The Kotlin model is pretty similar to the Java one:
sealed interface Crust
data object ThinCrust : Crust
data object ThickCrust : Crust
sealed interface BaseState
data object CreamBase : BaseState
data object TomatoBase : BaseState
sealed interface Topping
data object Ham : Topping
data object Olives : Topping
data object Potatoes : Topping
data object Pineapple : Topping
\ The builder approach is pretty different, though:
class DoughBuilder internal constructor(internal val crust: Crust)
class PizzaBuilder<out S : BaseState> internal constructor( // 1 // 2
internal val crust: Crust,
internal val base: BaseState,
internal val toppings: List<Topping>,
)
fun dough(crust: Crust): DoughBuilder = DoughBuilder(crust)
fun DoughBuilder.withCreamBase() =
PizzaBuilder<CreamBase>(crust, CreamBase, emptyList()) // 3
fun DoughBuilder.withTomatoBase() =
PizzaBuilder<TomatoBase>(crust, TomatoBase, emptyList()) // 3
fun PizzaBuilder<CreamBase>.withPotatoes() =
PizzaBuilder<CreamBase>(crust, base, toppings + Potatoes) // 3
fun PizzaBuilder<TomatoBase>.withPineapple() =
PizzaBuilder<TomatoBase>(crust, base, toppings + Pineapple) // 3
fun <S : BaseState> PizzaBuilder<S>.withHam() =
PizzaBuilder<S>(crust, base, toppings + Ham) // 3 // 4
fun <S : BaseState> PizzaBuilder<S>.withOlives() =
PizzaBuilder<S>(crust, base, toppings + Olives) // 3 // 4
fun <S : BaseState> PizzaBuilder<S>.build() = Pizza(crust, base, toppings.toSet())
out is Kotlin's syntax for covariance: a PizzaBuilder<CreamBase> can be used where a PizzaBuilder<BaseState> is expected. The upper bound : BaseState separately constrains S to BaseState and its subclasses.\ If we were to add pineapple/anchovies exclusion as in Java, we would need a slight change in the existing hierarchy:
sealed interface TomatoBase : BaseState
data object Tomato : TomatoBase
\ And then, add the states and the transitions:
data object TomatoWithPineapple : TomatoBase
data object TomatoWithAnchovies : TomatoBase
fun PizzaBuilder<TomatoBase>.withPineapple(): PizzaBuilder<TomatoWithPineapple> = TODO()
fun PizzaBuilder<TomatoBase>.withAnchovies(): PizzaBuilder<TomatoWithAnchovies> = TODO()
Finally, you'd define the exclusive transitions on the new types with extension functions.
\ In Kotlin, unlike Java, adding a new constraint requires only new type markers and extension functions — the growth is linear, not combinatorial.
Rust isn't an Object-Oriented programming language, contrary to Kotlin. Let's examine what we can learn from it.
\ The model part is quite straightforward:
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum Crust {
Thin,
Thick,
}
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub(crate) enum Base {
Cream,
Tomato,
}
pub struct HasDough;
pub struct CreamBase;
pub struct TomatoBase;
pub struct Pizza {
crust: Crust,
base: Base,
ham: bool,
olives: bool,
potatoes: bool,
pineapple: bool,
}
\ Interestingly enough, the design is pretty similar to Java's:
#[derive(Default)]
struct ToppingState {
ham: bool,
olives: bool,
potatoes: bool,
pineapple: bool,
}
pub struct PizzaBuilder<S> {
crust: Crust,
toppings: ToppingState,
_marker: std::marker::PhantomData<S>, // 1
}
impl PizzaBuilder<HasDough> {
pub fn dough(crust: Crust) -> PizzaBuilder<HasDough> {
PizzaBuilder {
crust,
toppings: ToppingState::default(),
_marker: std::marker::PhantomData, // 1
}
}
pub fn with_cream_base(self) -> PizzaBuilder<CreamBase> {
PizzaBuilder {
crust: self.crust,
toppings: self.toppings,
_marker: std::marker::PhantomData, // 1
}
}
pub fn with_tomato_base(self) -> PizzaBuilder<TomatoBase> {
PizzaBuilder {
crust: self.crust,
toppings: self.toppings,
_marker: std::marker::PhantomData, // 1
}
}
}
impl PizzaBuilder<CreamBase> {
pub fn with_potatoes(mut self) -> Self {
self.toppings.potatoes = true;
self
}
pub fn with_ham(mut self) -> Self {
self.toppings.ham = true;
self
}
pub fn with_olives(mut self) -> Self {
self.toppings.olives = true;
self
}
pub fn build(self) -> Pizza {
Pizza::new(
self.crust,
Base::Cream,
self.toppings.ham,
self.toppings.olives,
self.toppings.potatoes,
self.toppings.pineapple,
)
}
}
impl PizzaBuilder<TomatoBase> {
pub fn with_pineapple(mut self) -> Self {
self.toppings.pineapple = true;
self
}
pub fn with_ham(mut self) -> Self {
self.toppings.ham = true;
self
}
pub fn with_olives(mut self) -> Self {
self.toppings.olives = true;
self
}
pub fn build(self) -> Pizza {
Pizza::new(
self.crust,
Base::Tomato,
self.toppings.ham,
self.toppings.olives,
self.toppings.potatoes,
self.toppings.pineapple,
)
}
}
Phantom type. See section Phantom types below.
\
Java and Rust have fundamental differences in approaches: the former uses a runtime, and the latter compiles to native. Yet, from a pure language syntax point of view, Rust impl maps more or less to a Java subclass in this context.
\ We would get the same combinatory explosion for anchovies and pineapple.
Gleam is a recent programming language that runs on the BEAM. As of now, I'd say I'm proficient in Java and Kotlin, thus covering the JVM. Kotlin also allows JavaScript transpilation for the browser. I'm able to write quite a bit in Python, and consider myself a Rust newbie.
\ The BEAM is outside my reach, and I wanted to widen my options. Erlang is dynamically-typed, and Elixir is a bit too esoteric. Gleam's syntax is a bit similar to Rust's.
\
Note: Given my limited knowledge of Gleam, I used Claude Code a lot in this section. I'll be happy to receive feedback from Gleam programmers as I'm still learning.
\ Types are declared as:
pub type Crust {
Thin
Thick
}
pub type Topping {
Potatoes
Pineapple
Ham
Olives
}
pub type Base {
CreamBase
TomatoBase
}
pub type Cream {
Cream
}
pub type Tomato {
Tomato
}
pub opaque type Pizza { // 1
Pizza(crust: Crust, base: Base, toppings: List(Topping))
}
opaque is Gleam's way to hide the constructor from outside the module.
\ Then the builder looks like: \n
pub opaque type DoughBuilder { // 1
DoughBuilder(crust: Crust)
}
pub opaque type PizzaBuilder(base) { // 1
PizzaBuilder(crust: Crust, base: Base, toppings: List(Topping))
}
pub fn dough(crust: Crust) -> DoughBuilder {
DoughBuilder(crust: crust)
}
pub fn with_cream_base(builder: DoughBuilder) -> PizzaBuilder(Cream) {
let DoughBuilder(crust: crust) = builder
PizzaBuilder(crust: crust, base: CreamBase, toppings: [])
}
pub fn with_tomato_base(builder: DoughBuilder) -> PizzaBuilder(Tomato) {
let DoughBuilder(crust: crust) = builder
PizzaBuilder(crust: crust, base: TomatoBase, toppings: [])
}
pub fn with_potatoes(builder: PizzaBuilder(Cream)) -> PizzaBuilder(Cream) { // 2
let PizzaBuilder(crust: crust, base: base, toppings: toppings) = builder
PizzaBuilder(crust: crust, base: base, toppings: [Potatoes, ..toppings])
}
pub fn with_pineapple(builder: PizzaBuilder(Tomato)) -> PizzaBuilder(Tomato) { // 2
let PizzaBuilder(crust: crust, base: base, toppings: toppings) = builder
PizzaBuilder(crust: crust, base: base, toppings: [Pineapple, ..toppings])
}
pub fn with_ham(builder: PizzaBuilder(a)) -> PizzaBuilder(a) { // 3
let PizzaBuilder(crust: crust, base: base, toppings: toppings) = builder
PizzaBuilder(crust: crust, base: base, toppings: [Ham, ..toppings])
}
pub fn with_olives(builder: PizzaBuilder(a)) -> PizzaBuilder(a) { // 3
let PizzaBuilder(crust: crust, base: base, toppings: toppings) = builder
PizzaBuilder(crust: crust, base: base, toppings: [Olives, ..toppings])
}
pub fn build(builder: PizzaBuilder(a)) -> Pizza {
let PizzaBuilder(crust: crust, base: base, toppings: toppings) = builder
Pizza(crust: crust, base: base, toppings: list.reverse(toppings))
}
\
Adding anchovies topping exclusive to pineapple would require: adding the new states as types and the transitions as functions. As in Kotlin, it would be a linear code expansion, thanks to the generic PizzaBuilder(a) parameter and return type for common transitions.
Kotlin, Rust, and Gleam all allow a generic type on PizzaBuilder. While the syntax is different and the naming differs, phantom data in Rust, phantom type in Gleam, the concept stays the same: use generic types to enforce typing at compilation time, while letting go of them at runtime.
\ Here's the Kotlin code above, simplified: \n
class PizzaBuilder<out S : BaseState>
fun PizzaBuilder<CreamBase>.withPotatoes() = TODO()
fun PizzaBuilder<TomatoBase>.withPineapple() = TODO()
\
The magic is the S generic in the PizzaBuilder. It allows grafting extension functions based on this type. withPotatoes() only applies when S is CreamBase, withPineapple() when it's TomatoBase. Without a generic type, you can't constrain extension functions. However, S isn't used in any other place: it's effectively a phantom type, hence the name.
\ Gleam splits between types and functions. While this design is quite different from Kotlin's, it also enables phantom types to constrain functions depending on the phantom type.
\
The Rust compiler effectively disallows unused types, so you need to reference it somehow. Hence, you need a _marker: std::marker::PhantomData attribute: it's a zero-cost abstraction, discarded in the compiled code and useful only for the compiler. The leading underscore is a Rust convention that suppresses Rust's dead-code warning.
\ Note that despite Java having generics, its lack of extension functions or related mechanisms prevents attaching methods to a specific generic type.
Static typing is the solid foundation that prevents illegal state transitions. Yet, you need more to design a model that doesn't degrade quickly. Without phantom types and a way to leverage them to bind specific functions to them, each new state adds combinatorial complexity. The exact mechanism depends on the language: extension functions in Kotlin, impl blocks in Rust, and constrained parameter types in Gleam.
\ The complete source code for this post can be found on Codeberg.
To go further:
Originally published at A Java Geek on April 19th, 2026.
\
2026-04-24 04:00:09
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2026-04-24 03:24:13
That is the question Space and Time is putting in front of the market. The company behind Proof of SQL, the sub-second zero-knowledge coprocessor that lets smart contracts query onchain and offchain data, has moved from infrastructure into the consumer layer. On April 23, Space and Time opened general access to Dreamspace, an AI app builder that writes the frontend, backend, and smart contract from a sentence.
\ During the beta, users generated 34,000 apps on the platform. Schools across Indonesia built AI labs and curriculum around it last year, with a stated reach of 140,000 students. Today the tool goes to anyone with an internet connection.
\
Think of Dreamspace the way a non-coder thinks about Canva or Squarespace. Describe what you want. The system ships it. The difference is that the output is an onchain application with a smart contract behind it, not a static site.
\ A smart contract is a piece of code that sits on a blockchain and executes the moment its conditions are met. Payments, access rules, ownership, royalty splits, and supply logic all run without a backend server. Dreamspace builds those contracts for the user and makes them fully auditable, which matters because a creator cannot hide code they did not write but are responsible for.
\
\ \ Nate Holiday, Co-Founder of Space and Time and creator of Dreamspace, said,
\
"Space and Time was built to make verifiable data accessible to any application, at any scale. Dreamspace is where that infrastructure meets the people building the next wave of the internet. When the data layer handles itself, the only thing left to focus on is what you want to create."
\
Dreamspace is a stack of three things working in sequence. Microsoft Azure AI Foundry and Azure OpenAI generate the code. Space and Time secures the data layer with ZK-proven SQL, so an app can query real data and prove the result is accurate. Base, the Layer 2 network incubated at Coinbase, settles the transactions.
\
\ \ Base matters because the economics only work when fees and latency disappear. Base averages around $0.01 per transaction with sub-second confirmation, and the team is targeting sub-cent transaction fees as throughput scales. At that cost, a creator can charge 10 cents per AI-generated image, run a tipping feature, or sell token-gated access without a payment processor taking the margin.
\
\
\ Eric Brown, Head of AI Developer Relations at Base, said,
\
"We're building Base as an open stack for the global economy, and that means making it possible for anyone to participate as a builder, not just a user, and especially using cutting edge tools like AI. This exciting new project makes starting an onchain business as simple as having an idea worth building."
\
M12, Microsoft's venture fund, led a $20 million investment into Space and Time in 2022, with a follow-on $20 million Series A in 2024. The thesis then was enterprise data infrastructure for smart contracts. Dreamspace is the same tech meeting a different audience.
\ Michael Stewart, Managing Partner at M12, Microsoft's Venture Fund, said,
\
"Space and Time has spent years building infrastructure capable of supporting the most demanding financial applications in AI and blockchain. Dreamspace puts that foundation to work for a completely different kind of builder, and that range is exactly what we believed in when we invested."
\ The move fits where the market is going. The no-code AI platform market is projected to grow from $6.56 billion in 2025 to $75.14 billion by 2034, a 31.13% CAGR. Gartner expects 70% of new applications to use no-code or low-code tools by 2026, up from under 25% in 2020. Most of that growth has been offchain until now.
\
The current no-code universe, meaning Bubble, Adalo, Glide, stops at the Web2 edge. Billing runs through Stripe, identity runs through Firebase, and royalties are impossible once a user leaves the platform. Dreamspace shifts that plumbing onchain, which means the rules of the app and its revenue logic live in a contract anyone can read.
\
For builders in emerging markets, the cost curve is the real story. A creator in Jakarta or Lagos who cannot pass a KYC check for a U.S. payment processor can accept low-fee transactions on Base from day one. The Indonesian school pipeline of 140,000 students is an early preview of what that distribution looks like at scale.
\
Dreamspace is the first time the three layers of the new stack have been bundled in a way a non-engineer can actually use. AI generates the code. Verifiable data makes the app trustworthy. Base makes the unit economics work. Most AI and crypto launches solve one of those three. Dreamspace bundles them and hides the wiring, which is the harder problem to ship.
\ The 34,000 apps already built in beta and the 140,000-student pipeline in Indonesia say the distribution is real. What happens next is a question of how far natural-language app creation can push into revenue businesses. A creator in Jakarta spinning up a tipping app, a student in Mumbai launching a token-gated study group, an artist in Lagos selling one-of-one edits, each one is now a few sentences away from a live product. That is the bet Holiday, M12, and Base are making, and the infrastructure finally looks ready to carry it.
\ Don’t forget to like and share the story!
2026-04-24 03:00:14
If you’re still managing vendor risk through spreadsheets, email chains, and manual follow-ups, you already know the cost. Your team spends hundreds of hours chasing documents and compiling reports, only to get point-in-time snapshots that go stale the moment they’re completed. Meanwhile, regulations like the Digital Operational Resilience Act (DORA) and Cybersecurity Maturity Model Certification (CMMC) now call for continuous proof of vendor oversight.
For example, a vendor might pass a security review in Q1, but introduce a new critical vulnerability or misconfigured S3 bucket in Q2 that goes completely unnoticed until the next assessment cycle.
The right third-party risk management (TPRM) software replaces manual burden with automation, continuous monitoring, and AI-powered analysis that keeps pace with growing vendor ecosystems. Instead of chasing vendors for SOC 2 reports over email or tracking evidence in spreadsheets, modern platforms automatically collect documentation, flag expired reports, and alert you when a vendor’s security posture changes (e.g., new vulnerabilities, expired certificates, or breach indicators).
Below, we compare six leading TPRM platforms to help you find the one that fits your specific compliance needs, team size, and risk priorities.
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<th class="table_header">Top 6 TPRM software platforms</th>
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<tbody class="table_body">
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<td class="table_cell"><ul><li>Vanta</li><li>Optro (fka Auditboard)</li><li>OneTrust</li><li>SecurityScorecard</li><li>UpGuard</li><li>BitSight</li></ul></td>
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Vendor risk is only growing. More than half of organizations have had a vendor experience a data breach in the past year, putting them at risk of compliance issues, revenue loss, and reputational damage. At the same time, manual, spreadsheet-based vendor assessments can’t keep up. Teams spend hours chasing vendors and updating reports that are outdated almost immediately—like emailing a vendor for their latest SOC 2, tracking the response in a spreadsheet, and setting a reminder to check back months later.
That’s why continuous monitoring is now the baseline. As AI adoption grows and data sharing expands, organizations need real-time visibility into vendor risk—to catch issues early and stay compliant without slowing the business down.
From finance to defense, new regulations impact how teams manage vendor risk—and raises the stakes.
New regulations require continuous oversight of third-party vendors, making legacy tools built around annual reviews no longer enough. These frameworks expect real-time visibility and faster response times, with real consequences for organizations that don’t have ongoing monitoring in place.
The average enterprise now relies on hundreds of third-party vendors, each representing an ever-evolving attack surface. According to Verizon's 2025 DBIR, third-party involvement in breaches doubled to 30%, highlighting how attackers exploit smaller, less-secured vendors to access larger organizations. One example: teams might onboard new AI tools for customer support or analytics without formal security review, creating unmanaged vendor risk.
This risk compounds as organizations adopt more SaaS and AI services. Vendor ecosystems are growing faster than security teams can keep up. KPMG's 2026 survey found 83% of executives plan to expand partner networks in the next one to three years. Shadow IT—tools adopted without formal procurement approval—introduces constant blind spots. Without continuous monitoring, these risks remain invisible until they become incidents.
We assessed leading TPRM platforms based on how well they help security and GRC teams slash manual effort, streamline vendor onboarding, and maintain compliance across SOC 2, ISO 27001, and HIPAA. Specifically, we looked at how platforms perform across real workflows like onboarding a new vendor, responding to an audit request, or identifying a newly introduced vendor risk.
The criteria below focus on the capabilities that drive real outcomes, not just features.
| Criterion | Why it matters | Questions to ask vendors | |----|----|----| | Automated vendor discovery and classification | Shadow IT vendors that bypass procurement create hidden risk exposure you cannot manage, like unsanctioned SaaS tools connected via SSO or expense data. | How do you detect shadow IT vendors that have not gone through formal procurement? What triggers your vendor intake process? | | Continuous vendor monitoring | Quarterly snapshots go stale immediately. You need real-time alerts when vendor security posture degrades, such as expired certificates or newly disclosed vulnerabilities. | How frequently do you monitor vendor security posture? What triggers automatic alerts, and how quickly does your platform surface them? | | Evidence collection automation | Manual follow-up for vendor documents consumes hundreds of hours per year—especially when tracking expiring reports or missing artifacts. | What percentage of vendor evidence collection runs automatically? How do you handle evidence validation and expiration tracking? | | Integration depth with existing tools | Fragmented tools create blind spots when TPRM data cannot flow between systems like procurement, ERP, and cloud infrastructure. | How many integrations do you offer, and how deep is the data sync? How do you connect to procurement and cloud infrastructure tools? |
| Criterion | Why it matters | Questions to ask vendors | |----|----|----| | Risk scoring and prioritization framework | With hundreds of vendors, intelligent scoring helps you focus limited resources on the highest-impact relationships, like prioritizing critical infrastructure providers over low-risk tools. | How does your platform calculate and prioritize vendor risk scores? How can we customize risk weighting based on our business context? | | Inherent vs residual risk tracking | Tracking both inherent and residual risk shows your true exposure after controls are applied, such as how requirements like MFA reduce vendor risk over time. | How do you differentiate between inherent and residual risk? How can we track risk reduction over time as controls are implemented? | | Risk to asset mapping | Mapping vendors to specific assets and data flows reveals business impact—for example, identifying which vendors access sensitive customer or production data. | How do you map vendor relationships to specific assets, data types, and business processes? |
| Criterion | Why it matters | Questions to ask vendors | |----|----|----| | AI-powered security review automation | AI-driven document analysis replaces hours of manual review per vendor, such as summarizing lengthy security reports into key risks. | How does your AI analyze vendor security documentation? What is the accuracy rate and how much human review is still necessary? | | Questionnaire automation and intelligence | Adaptive questionnaires that reuse prior answers and scale by risk tier eliminate repetitive work across assessment cycles. | How does your platform auto-populate questionnaires from previous responses? How do you tailor questionnaire depth based on vendor risk tier? | | Vendor portal and collaboration tools | Self-service vendor portals reduce delays from email-based evidence collection by enabling direct document submission and tracking. | Do you provide a vendor-facing portal for document submission? How do you track vendor response times and automate follow-ups? | | Review cycle time reduction | Faster review workflows accelerate procurement timelines—for example, shortening vendor onboarding from weeks to days. | What time reduction do customers typically see in review cycles? How do you surface metrics on pre- and post-implementation cycle times? |
| Criterion | Why it matters | Questions to ask vendors | |----|----|----| | Multi entity and business unit support | Organizations with multiple entities or regions need segmented vendor risk views with centralized reporting across business units. | How does your platform support multiple legal entities with separate vendor populations? How do you provide both segmented and consolidated reporting? | | Role-based access and workflow customization | Granular permissions ensure the right teams review the right vendors, with workflows that route higher-risk vendors through additional scrutiny. | How flexible is your role-based access control? How can we customize approval workflows based on vendor risk tier or business unit? | | Framework compliance mapping | Automatic mapping of vendor controls to frameworks like SOC 2, ISO 27001, and HIPAA eliminates manual cross-referencing during audits. | How does your platform map vendor security controls to specific framework requirements? How do you track vendor compliance across multiple frameworks simultaneously? |
| Criterion | Why it matters | Questions to ask vendors | |----|----|----| | Executive and board-level reporting | Clear risk summaries—like top vendor risk exposures and trend lines—enable leadership to make informed decisions about risk and investment. | What executive dashboards and board-ready reports does your platform provide? How can we customize reporting to highlight the metrics leadership cares about? | | Fourth-party risk visibility | Visibility into your vendors’ vendors reveals hidden concentration risk, such as multiple providers relying on the same subprocessor. | What visibility into fourth-party relationships do you provide? How do you map and monitor your vendors' critical dependencies? | | Threat intelligence integration | External breach and vulnerability data ensures vendor risk scores reflect real-world threats as they emerge. | How do you incorporate external threat intelligence into vendor risk scores? What sources do you use, and how quickly are new threats reflected? | | Customizable risk categories | Custom risk categories address industry-specific concerns, such as handling sensitive data types or regulated information. | How can we create custom risk categories and assessment criteria? What pre-built risk scenarios do you offer for our industry? | | Vendor volume scalability | Your platform must scale to hundreds or thousands of vendors without performance issues or steep cost increases as your ecosystem grows. | How many vendor relationships can your platform manage? How does pricing change as our vendor population grows? |
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<div style="overflow-x:auto;-webkit-overflow-scrolling:touch;">
<div class="table_vendor-evaluation">
<table class="table_component" cellpadding="10" style="min-width: 50%;">
<thead class="table_head">
<tr class="table_row no-border">
<th class="table_header">Criterion</th>
<th class="table_header">Why it matters</th>
<th class="table_header">Questions to ask vendors</th>
</tr>
</thead>
<tbody class="table_body">
<tr class="table_row">
<td class="table_cell" colspan="3" style="background-color:#e6e6e6; font-weight:bold; text-align:center;">Automation and continuous monitoring</td>
</tr>
<tr class="table_row">
<td class="table_cell">Automated vendor discovery and classification</td>
<td class="table_cell">Shadow IT vendors that bypass procurement create hidden risk exposure you cannot manage, like unsanctioned SaaS tools connected via SSO or expense data.</td>
<td class="table_cell"><ul><li>How do you detect shadow IT vendors that have not gone through formal procurement?</li><li>What triggers your vendor intake process?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Continuous vendor monitoring</td>
<td class="table_cell">Quarterly snapshots go stale immediately. You need real-time alerts when vendor security posture degrades, such as expired certificates or newly disclosed vulnerabilities.</td>
<td class="table_cell"><ul><li>How frequently do you monitor vendor security posture?</li><li>What triggers automatic alerts, and how quickly does your platform surface them?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Evidence collection automation</td>
<td class="table_cell">Manual follow-up for vendor documents consumes hundreds of hours per year—especially when tracking expiring reports or missing artifacts.</td>
<td class="table_cell"><ul><li>What percentage of vendor evidence collection runs automatically?</li><li>How do you handle evidence validation and expiration tracking?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Integration depth with existing tools</td>
<td class="table_cell">Fragmented tools create blind spots when TPRM data cannot flow between systems like procurement, ERP, and cloud infrastructure.</td>
<td class="table_cell"><ul><li>How many integrations do you offer, and how deep is the data sync?</li><li>How do you connect to procurement and cloud infrastructure tools?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell" colspan="3" style="background-color:#e6e6e6; font-weight:bold; text-align:center;">Intelligence and reporting</td>
</tr>
<tr class="table_row">
<td class="table_cell">Executive and board-level reporting</td>
<td class="table_cell">Clear risk summaries—like top vendor risk exposures and trend lines—enable leadership to make informed decisions about risk and investment.</td>
<td class="table_cell"><ul><li>What executive dashboards and board-ready reports does your platform provide?</li><li>How can we customize reporting to highlight the metrics leadership cares about?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Fourth-party risk visibility</td>
<td class="table_cell">Visibility into your vendors’ vendors reveals hidden concentration risk, such as multiple providers relying on the same subprocessor.</td>
<td class="table_cell"><ul><li>What visibility into fourth-party relationships do you provide?</li><li>How do you map and monitor your vendors' critical dependencies?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Threat intelligence integration</td>
<td class="table_cell">External breach and vulnerability data ensures vendor risk scores reflect real-world threats as they emerge.</td>
<td class="table_cell"><ul><li>How do you incorporate external threat intelligence into vendor risk scores?</li><li>What sources do you use, and how quickly are new threats reflected?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Customizable risk categories</td>
<td class="table_cell">Custom risk categories address industry-specific concerns, such as handling sensitive data types or regulated information.</td>
<td class="table_cell"><ul><li>How can we create custom risk categories and assessment criteria?</li><li>What pre-built risk scenarios do you offer for our industry?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Vendor volume scalability</td>
<td class="table_cell">Your platform must scale to hundreds or thousands of vendors without performance issues or steep cost increases as your ecosystem grows.</td>
<td class="table_cell"><ul><li>How many vendor relationships can your platform manage?</li><li>How does pricing change as our vendor population grows?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell" colspan="3" style="background-color:#e6e6e6; font-weight:bold; text-align:center;">Scalability and enterprise readiness</td>
</tr>
<tr class="table_row">
<td class="table_cell">Multi entity and business unit support</td>
<td class="table_cell">Organizations with multiple entities or regions need segmented vendor risk views with centralized reporting across business units.</td>
<td class="table_cell"><ul><li>How does your platform support multiple legal entities with separate vendor populations?</li><li>How do you provide both segmented and consolidated reporting?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Role-based access and workflow customization</td>
<td class="table_cell">Granular permissions ensure the right teams review the right vendors, with workflows that route higher-risk vendors through additional scrutiny.</td>
<td class="table_cell"><ul><li>How flexible is your role-based access control?</li><li>How can we customize approval workflows based on vendor risk tier or business unit?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Framework compliance mapping</td>
<td class="table_cell">Automatic mapping of vendor controls to frameworks like SOC 2, ISO 27001, and HIPAA eliminates manual cross-referencing during audits.</td>
<td class="table_cell"><ul><li>How does your platform map vendor security controls to specific framework requirements?</li><li>How do you track vendor compliance across multiple frameworks simultaneously?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell" colspan="3" style="background-color:#e6e6e6; font-weight:bold; text-align:center;">Vendor assessment and review efficiency</td>
</tr>
<tr class="table_row">
<td class="table_cell">AI-powered security review automation</td>
<td class="table_cell"><a href="https://help.vanta.com/en/articles/11345366-best-practices-for-using-ai-in-security-reviews">AI-driven document analysis</a> replaces hours of manual review per vendor, such as summarizing lengthy security reports into key risks.</td>
<td class="table_cell"><ul><li>How does your AI analyze vendor security documentation?</li><li>What is the accuracy rate and how much human review is still necessary?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Questionnaire automation and intelligence</td>
<td class="table_cell">Adaptive questionnaires that reuse prior answers and scale by risk tier eliminate repetitive work across assessment cycles.</td>
<td class="table_cell"><ul><li>How does your platform auto-populate questionnaires from previous responses?</li><li>How do you tailor questionnaire depth based on vendor risk tier?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Vendor portal and collaboration tools</td>
<td class="table_cell">Self-service vendor portals reduce delays from email-based evidence collection by enabling direct document submission and tracking.</td>
<td class="table_cell"><ul><li>Do you provide a vendor-facing portal for document submission?</li><li>How do you track vendor response times and automate follow-ups?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Review cycle time reduction</td>
<td class="table_cell">Faster review workflows accelerate procurement timelines—for example, shortening vendor onboarding from weeks to days.</td>
<td class="table_cell"><ul><li>What time reduction do customers typically see in review cycles?</li><li>How do you surface metrics on pre- and post-implementation cycle times?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell" colspan="3" style="background-color:#e6e6e6; font-weight:bold; text-align:center;">Risk assessment and prioritization</td>
</tr>
<tr class="table_row">
<td class="table_cell">Risk scoring and prioritization framework</td>
<td class="table_cell">With hundreds of vendors, intelligent scoring helps you focus limited resources on the highest-impact relationships, like prioritizing critical infrastructure providers over low-risk tools.</td>
<td class="table_cell"><ul><li>How does your platform calculate and prioritize vendor risk scores?</li><li>How can we customize risk weighting based on our business context?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Inherent vs residual risk tracking</td>
<td class="table_cell">Tracking both <a href="https://help.vanta.com/en/articles/11345560-inherent-risk-rubric-customization">inherent and residual risk</a> shows your true exposure after controls are applied, such as how requirements like MFA reduce vendor risk over time.</td>
<td class="table_cell"><ul><li>How do you differentiate between inherent and residual risk?</li><li>How can we track risk reduction over time as controls are implemented?</li></ul></td>
</tr>
<tr class="table_row">
<td class="table_cell">Risk to asset mapping</td>
<td class="table_cell">Mapping vendors to specific assets and data flows reveals business impact—for example, identifying which vendors access sensitive customer or production data.</td>
<td class="table_cell">How do you map vendor relationships to specific assets, data types, and business processes?</td>
</tr>
</tbody>
</table>
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\ \n Disclaimer: To help you find the best TPRM software, we’ve researched and ranked a selection of leading platforms. While we may be biased about Vanta being the top option, we aim to provide a comprehensive view so you can choose the right fit for your organization.
The following platforms represent different approaches to third-party risk management. We evaluate each on positioning, key capabilities, ideal use cases, and how they perform against the standardized criteria above.
Vanta is the leading Agentic Trust Platform that unifies compliance, risk, and customer trust workflows in a single system. Unlike point solutions that address only vendor risk, Vanta connects TPRM to your broader compliance program so vendor assessments stay current alongside your internal controls, evidence, and policies.
For TPRM, specifically, Vanta swaps spreadsheets and point-in-time reviews with continuous, automated vendor monitoring. AI-powered security reviews analyze vendor documentation and flag key risks automatically, while continuous monitoring tracks changes in vendor security posture and sends real-time alerts. Vanta supports multiple risk registers with enterprise roll-ups for organization-wide visibility, flexible risk scoring you can customize to your business context, and risk-to-asset mapping that connects vendor relationships to the data and systems they access.
Vanta builds vendor risk management into the same platform that automates compliance across SOC 2, ISO 27001, HIPAA, HITRUST, and GDPR. The vendor evidence you collect for risk assessments maps directly to framework requirements without duplicate work. With a customizable vendor risk rubric, centralized vendor portal, and continuous monitoring alerts, Vanta gives you the visibility to prioritize high-impact vendor risks and the automation to act on them efficiently.
Enterprise and mid-market teams seeking unified trust management where TPRM connects to broader compliance and risk programs.
| Pros | Cons | |----|----| | Unified platform: Vendor risk management sits alongside your compliance and trust workflows, so TPRM isn’t siloed from the rest of your GRC program. | Enterprise onboarding: Organizations with highly custom legacy GRC workflows may need dedicated implementation support to migrate existing processes. | | Continuous monitoring: Automated alerts surface vendor risk changes in real time, replacing point-in-time assessments that quickly go stale. | Vendor adoption: Vendors unfamiliar with portal-based evidence submission may require initial guidance to adopt the self-service workflow. | | AI automation: AI reviews vendor security documentation and highlights key risks, cutting down manual review time for each vendor. | Specialized ERM: Organizations looking for standalone enterprise risk management platforms with capabilities beyond third-party risk may need integral tooling. |
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<td class="table_cell"><strong>Unified platform:</strong> Vendor risk management sits alongside your compliance and trust workflows, so TPRM isn’t siloed from the rest of your GRC program.</td>
<td class="table_cell"><strong>Enterprise onboarding:</strong> Organizations with highly custom legacy GRC workflows may need dedicated implementation support to migrate existing processes.</td>
</tr>
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<td class="table_cell"><strong>Continuous monitoring:</strong> Automated alerts surface vendor risk changes in real time, replacing point-in-time assessments that quickly go stale.</td>
<td class="table_cell"><strong>Vendor adoption:</strong> Vendors unfamiliar with portal-based evidence submission may require initial guidance to adopt the self-service workflow.</td>
</tr>
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<td class="table_cell"><strong>AI automation:</strong> AI reviews vendor security documentation and highlights key risks, cutting down manual review time for each vendor.</td>
<td class="table_cell"><strong>Specialized ERM:</strong> Organizations looking for standalone enterprise risk management platforms with capabilities beyond third-party risk may need integral tooling.</td>
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Optro is a connected risk platform spanning internal audit, IT compliance, SOX, and operational risk management. It provides capabilities for organizations that need TPRM as part of a broader internal audit and risk management program, with strong cross-functional risk visibility.
The platform provides limited out-of-the-box continuous monitoring for vendor risk, with fewer pre-built integrations and a more manual approach to evidence gathering compared to platforms designed around continuous automation.
Internal audit teams looking to consolidate SOX, IT compliance, and vendor risk into one audit-focused system.
| Pros | Cons | |----|----| | Audit integration: Deep integration with internal audit and SOX compliance workflows for unified audit management. | Manual workflows: Primarily relies on point-in-time evidence collection instead of continuous monitoring. Out-of-the-box monitor templates are limited and require manual setup and threshold configuration. | | Cross-functional visibility: Connects vendor risk to broader operational risk metrics across the organization. | Implementation time: Can require significant time and resources to deploy across an enterprise environment. | | Reporting depth: Strong executive reporting capabilities for traditional risk management metrics and audit findings. | Security monitoring: Provides only point-in-time visibility for device monitoring and has limited out-of-the-box vulnerability management integrations without real-time detection capabilities |
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<td class="table_cell"><strong>Audit integration:</strong> Deep integration with internal audit and SOX compliance workflows for unified audit management.</td>
<td class="table_cell"><strong>Manual workflows:</strong> Primarily relies on point-in-time evidence collection instead of continuous monitoring. Out-of-the-box monitor templates are limited and require manual setup and threshold configuration.</td>
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<td class="table_cell"><strong>Cross-functional visibility:</strong> Connects vendor risk to broader operational risk metrics across the organization.</td>
<td class="table_cell"><strong>Implementation time:</strong> Can require significant time and resources to deploy across an enterprise environment.</td>
</tr>
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<td class="table_cell"><strong>Reporting depth:</strong> Strong executive reporting capabilities for traditional risk management metrics and audit findings.</td>
<td class="table_cell"><strong>Security monitoring:</strong> Provides only point-in-time visibility for device monitoring and has limited out-of-the-box vulnerability management integrations without real-time detection capabilities.</td>
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OneTrust is a broad privacy, governance, and risk management platform offering privacy-centric TPRM capabilities. It serves organizations with heavy regulatory requirements around data privacy, such as GDPR and CCPA, with extensive vendor lifecycle management features.
Built through acquisitions rather than as a unified architecture, the OneTrust platform is a compliance automation module that offers limited monitoring frequency compared to platforms with continuous, hourly testing. Evidence gathering also relies more heavily on manual processes, creating workflow challenges compared to natively built platforms designed for continuous trust management.
Privacy and legal teams that prioritize data privacy regulations over continuous security monitoring.
| Pros | Cons | |----|----| | Privacy focus: Excellent alignment with data privacy laws like GDPR and CCPA for privacy-first organizations. | Platform complexity: The broad feature set can make the platform difficult to navigate for focused security teams. | | Data mapping: Strong tools for mapping vendor data flows and consent management across the vendor lifecycle. | Integration gaps: TPRM features can feel disconnected from other security workflows and compliance programs. | | Template library: Extensive library of regulatory compliance templates for various industries and frameworks. | Cost scaling: Pricing can scale quickly as you add different modules and capabilities to the platform. |
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<td class="table_cell"><strong>Privacy focus:</strong> Excellent alignment with data privacy laws like GDPR and CCPA for privacy-first organizations.</td>
<td class="table_cell"><strong>Platform complexity:</strong> The broad feature set can make the platform difficult to navigate for focused security teams.</td>
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<td class="table_cell"><strong>Data mapping:</strong> Strong tools for mapping vendor data flows and consent management across the vendor lifecycle.</td>
<td class="table_cell"><strong>Integration gaps:</strong> TPRM features can feel disconnected from other security workflows and compliance programs.</td>
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<td class="table_cell"><strong>Template library:</strong> Extensive library of regulatory compliance templates for various industries and frameworks.</td>
<td class="table_cell"><strong>Cost scaling:</strong> Pricing can scale quickly as you add different modules and capabilities to the platform.</td>
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SecurityScorecard is a security ratings and external risk monitoring platform that’s great for outside-in risk assessment. It evaluates vendors based on externally visible signals, such as open ports, patching habits, and past breaches without requiring vendor input.
This approach provides valuable visibility but operates in isolation from broader GRC programs, creating data silos that unified platforms eliminate.
Security operations teams that want to monitor the external attack surface of their vendor ecosystem without relying on questionnaires.
| Pros | Cons | |----|----| | Outside-in visibility: Assesses vendor security posture without requiring vendor participation or cooperation. | Data isolation: Operates separately from internal compliance and risk register workflows, creating integration challenges. | | Continuous scanning: Provides real-time updates on externally observable security flaws and vulnerabilities. | Context limitations: Cannot assess internal controls, policies, or compliance framework adherence without vendor input. | | Threat intelligence: Integrates external breach data into vendor risk scores for real-world threat context. | False positives: External scans can flag issues that are mitigated by internal compensating controls you cannot see. |
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<td class="table_cell"><strong>Outside-in visibility:</strong> Assesses vendor security posture without requiring vendor participation or cooperation.</td>
<td class="table_cell"><strong>Data isolation:</strong> Operates separately from internal compliance and risk register workflows, creating integration challenges.</td>
</tr>
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<td class="table_cell"><strong>Continuous scanning:</strong> Provides real-time updates on externally observable security flaws and vulnerabilities.</td>
<td class="table_cell"><strong>Context limitations:</strong> Cannot assess internal controls, policies, or compliance framework adherence without vendor input.</td>
</tr>
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<td class="table_cell"><strong>Threat intelligence:</strong> Integrates external breach data into vendor risk scores for real-world threat context.</td>
<td class="table_cell"><strong>False positives:</strong> External scans can flag issues that are mitigated by internal compensating controls you cannot see.</td>
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UpGuard combines vendor risk management with attack surface management, blending outside-in monitoring with inside-out vendor assessments. It offers data leak detection and external security ratings alongside traditional questionnaire-based assessments for comprehensive third-party visibility.
Teams must manually integrate UpGuard's findings into central GRC systems to connect vendor risk with internal compliance programs.
Security teams looking for a dedicated tool that combines external security ratings with automated vendor questionnaires.
| Pros | Cons | |----|----| | Hybrid approach: Combines external scanning with internal questionnaire data for comprehensive vendor assessment. | Integration effort: Requires manual work to connect findings to broader GRC and compliance programs. | | Leak detection: Strong capabilities for finding exposed data on the public internet and dark web. | Limited scope: Lacks deep internal audit and compliance framework mapping capabilities. | | Risk quantification: Provides clear, quantifiable cyber risk scores for vendor prioritization. | Scalability challenges: Managing complex, multi-framework compliance programs can be difficult outside a unified platform. |
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<td class="table_cell"><strong>Hybrid approach:</strong> Combines external scanning with internal questionnaire data for comprehensive vendor assessment.</td>
<td class="table_cell"><strong>Integration effort:</strong> Requires manual work to connect findings to broader GRC and compliance programs.</td>
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<td class="table_cell"><strong>Leak detection:</strong> Strong capabilities for finding exposed data on the public internet and dark web.</td>
<td class="table_cell"><strong>Limited scope:</strong> Lacks deep internal audit and compliance framework mapping capabilities.</td>
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<td class="table_cell"><strong>Risk quantification:</strong> Provides clear, quantifiable cyber risk scores for vendor prioritization.</td>
<td class="table_cell"><strong>Scalability challenges:</strong> Managing complex, multi-framework compliance programs can be difficult outside a unified platform.</td>
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BitSight is built for enterprise teams that need an outside-in view of vendor risk. It scores vendors based on external signals and is particularly useful for turning cyber risk into financial impact for board-level conversations, with strong insight into fourth-party and supply chain risk.
However, it’s less robust when it comes to internal control mapping and deep compliance integrations compared to more all-in-one platforms.
Large organizations and financial institutions that need to quantify cyber risk financially for board-level reporting.
| Pros | Cons | |----|----| | Financial metrics: Translates cyber risk into financial metrics for executive leadership and board presentations. | Compliance gaps: Lacks deep integration with internal compliance frameworks like SOC 2 or ISO 27001. | | Supply chain visibility: Strong capabilities for mapping extended supply chain dependencies and fourth-party risk. | Internal blind spots: Cannot evaluate a vendor's internal security policies or access controls without questionnaires. | | Benchmarking: Allows organizations to compare vendor risk against industry peers for context. Start with your compliance scope. | Enterprise pricing: Enterprise-grade pricing that may be prohibitive for mid-market organizations. |
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<td class="table_cell"><strong>Financial metrics:</strong> Translates cyber risk into financial metrics for executive leadership and board presentations.</td>
<td class="table_cell"><strong>Compliance gaps:</strong> Lacks deep integration with internal compliance frameworks like SOC 2 or ISO 27001.</td>
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<td class="table_cell"><strong>Supply chain visibility:</strong> Strong capabilities for mapping extended supply chain dependencies and fourth-party risk.</td>
<td class="table_cell"><strong>Internal blind spots:</strong> Cannot evaluate a vendor's internal security policies or access controls without questionnaires.</td>
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<td class="table_cell"><strong>Benchmarking:</strong> Allows organizations to compare vendor risk against industry peers for context. Start with your compliance scope.</td>
<td class="table_cell"><strong>Enterprise pricing:</strong> Enterprise-grade pricing that may be prohibitive for mid-market organizations.</td>
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Selecting the right platform requires matching your compliance needs with the appropriate level of automation and integration.
Start by identifying which frameworks require vendor oversight—like SOC 2 or PCI DSS—and how much third-party risk your organization is comfortable taking on. This will shape the level of assessment and monitoring you need from your TPRM platform.
Take stock of how many vendors you manage, including which ones have access to sensitive data or critical systems. This helps you determine whether you need a platform built for dozens of vendors or thousands—and how much automation is necessary.
Look at the procurement, HR, cloud infrastructure, and security tools your TPRM platform needs to connect to. If integrations fall short, you’ll end up with the same manual workarounds you’re trying to avoid.
Consider whether vendor risk management should live in a point solution or as part of your broader compliance and trust program. Unified platforms can reduce duplicate evidence collection and keep vendor assessments aligned with your internal controls.
Instead of relying on a demo dataset, test each platform using your actual vendor assessment workflows. Pay attention to how it handles evidence collection, questionnaire automation, risk scoring, and reporting with real vendors and documents.
Consider how pricing scales with more vendors, additional users, and expanded framework coverage. A tool that fits your budget today but becomes too expensive later can create unnecessary migration risk.
As vendor ecosystems grow and regulatory requirements expand, the gap between what manual processes can handle and what your organization needs widens. The right TPRM software closes that gap by automating evidence collection, continuously monitoring vendor security posture, and connecting third-party risk to your broader compliance program.
Vanta unifies vendor risk management with compliance and trust workflows in a single platform, allowing you to see, prioritize, and act on third-party risk without adding headcount or managing disconnected tools.
Request a demo to see how Vanta automates TPRM.
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TPRM covers all third-party relationships—including contractors, partners, and suppliers—while vendor risk management focuses specifically on vendors. Most modern platforms bring both together into a single risk and compliance framework.
TPRM software automates vendor evidence collection and maps controls to SOC 2 and ISO 27001 requirements, helping ensure your audit evidence stays current, organized, and easy to report on.
AI can significantly reduce manual work by auto-populating responses and analyzing vendor data, but human review is still essential—especially for high-risk or complex vendors.
It depends on risk level: critical vendors often require continuous monitoring and quarterly reviews, while lower-risk vendors may only need annual reassessments. Continuous monitoring helps reduce reliance on fixed schedules.
