Stigg is the usage runtime for AI products: the real-time enforcement and governance layer between your app and your billing stack. It decides what every customer, user, team, and agent can do, the moment they try. Millisecond credit checks, zero overdraft, enterprise governance, and modular BYOC. Metering, credits, entitlements, and governance in one runtime. Enforce in the request path instead of reconciling on the invoice. Free forever for AI startups.
Hi everyone, Dor here, co-founder and CEO of Stigg.
Four years ago, Anton and I started Stigg because building pricing and entitlements in-house was quietly eating engineering teams alive. Every pricing change was a deployment. Every enterprise deal became a custom integration.
We were right about the problem. Then the AI wave made it much sharper.
The most sophisticated AI companies started building their own billing and access-control infrastructure from scratch, because nothing on the market could decide in real time whether a request should proceed.
A frontier lab's head of financial engineering put it simply: what they needed was something close to real time that could answer one question - do you have credits or not?
When a single API call costs real money and agents spawn sub-agents in milliseconds, "we'll reconcile at month-end" stops being a strategy.
Stigg 2.0 is our answer: the usage runtime for AI products. It decides what every customer, user, team, and agent is allowed to do, the moment they try. Credits, metering, entitlements, and governance in one system that sits alongside the billing stack you already have.
It's free forever for AI startups, because we want you building your product, not rebuilding ours. When you land the enterprise deal that breaks your homegrown system, we'll already be there.
We're launching at the AI World Fair. We'd love your honest take, try it, push on it, and tell us what's missing.
Makes sense, the atomic hold is the answer I was hoping for. The bit I'd still watch is estimate drift: if you reserve worst-case output tokens per call, a 50-wide agent fan-out holds far more than it spends and can start false-blocking once the wallet is mostly reserved rather than actually spent. And a hold from a call that dies mid-stream leaks until something reaps it. Do you release the estimate-minus-actual delta on settle, and is there a TTL on orphaned holds?
Congrats on the launch. I hand-rolled entitlements for my own two-plan SaaS last week: one feature flag and a couple of can_use_x? methods (super simple). I assume it ends in tears somewhere around plan number four. Curious where you see the crossover in practice. Is it plan count, team size, or the first customer who asks for a custom contract?
Finally cracked our entitlement sprawl with this. Love that credit checks happen in the request path so we're not patching things together after the invoice fires. Setup was painless.
how does this handle usage coming from multiple agents or services hitting the same entitlement at the same millisecond without one of them getting blocked unexpectedly
How does the BYOC setup actually work in practice, does my billing data leave Stigg's infra at all or do you just push metering events into my own system?
Honestly impressed by how quick the credit checks are - the request path enforcement feels like the right call instead of wrestling with reconciliation after the fact.
how does the sub-millisecond credit check actually hold up when an agent is hammering the API in tight loops, does it queue or just drop the extra requests
love how you put governance right in the request path instead of patching it after the fact, such a clean architectural call for AI products
the modular BYOC split is interesting - usage governance running in my own VPC while the credits engine stays centralized. what happens during a network partition between the two, where my enforcement layer can't reach the central ledger for a stretch. does governance keep enforcing against its last known balance, or does that gap turn into the same fail-open risk people are asking about elsewhere in this thread
how does this actually handle the real-time enforcement without slowing down the request path, especially when billing data lives in a separate stack?
How does the BYOC setup actually work in practice, like do I keep my existing Stripe account and Stigg just sits in front of it, or does it want to own the billing pipeline end to end?
Pushed a couple of test requests through and the credit check really does come back instantly, no awkward wait before the request resolves. Clean DX overall, especially for wrapping it around an existing billing setup.
Tried Stigg on a small side project and was surprised how easy it was to wire credit checks right into the request path instead of patching things together later. The sub-millisecond thing actually held up in my testing.
How does the sub-millisecond credit check actually work under the hood when integrating with something like Stripe or a custom billing backend? Curious if there is extra latency added to the request path in practice.
Plugged the SDK in and the entitlement checks actually fire inside the request path, no more end-of-month reconciliation surprises. The credit burn updates feel instant too.
Love that it enforces in the request path instead of reconciling after the fact. The sub-millisecond credit checks actually feel invisible during testing, which is exactly what you want from this kind of layer.
Plugged it into a side project last night and was surprised how fast the entitlement checks land, basically no latency bump. The governance dashboard also made it obvious which test accounts were poking limits.
Putting enforcement in the request path instead of reconciling on the invoice is the right call, month-end reconciliation is how agent loops quietly torch a budget. My one operational worry is the dependency itself: when Stigg is slow or unreachable, does the check fail-open (let the request through and risk overdraft) or fail-closed (block the customer)? For a sub-ms hot-path gate that degradation default is the thing I'd need pinned down before putting it in front of live traffic.
About Stigg 2.0 on Product Hunt
“The usage runtime for AI products”
Stigg 2.0 launched on Product Hunt on July 1st, 2026 and earned 135 upvotes and 32 comments, placing #17 on the daily leaderboard. Stigg is the usage runtime for AI products: the real-time enforcement and governance layer between your app and your billing stack. It decides what every customer, user, team, and agent can do, the moment they try. Millisecond credit checks, zero overdraft, enterprise governance, and modular BYOC. Metering, credits, entitlements, and governance in one runtime. Enforce in the request path instead of reconciling on the invoice. Free forever for AI startups.
Stigg 2.0 was featured in Software Engineering (42.7k followers), Developer Tools (515.4k followers) and Artificial Intelligence (473.1k followers) on Product Hunt. Together, these topics include over 187.4k products, making this a competitive space to launch in.
Who hunted Stigg 2.0?
Stigg 2.0 was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Stigg 2.0 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Hi everyone, Dor here, co-founder and CEO of Stigg.
Four years ago, Anton and I started Stigg because building pricing and entitlements in-house was quietly eating engineering teams alive. Every pricing change was a deployment. Every enterprise deal became a custom integration.
We were right about the problem. Then the AI wave made it much sharper.
The most sophisticated AI companies started building their own billing and access-control infrastructure from scratch, because nothing on the market could decide in real time whether a request should proceed.
A frontier lab's head of financial engineering put it simply: what they needed was something close to real time that could answer one question - do you have credits or not?
When a single API call costs real money and agents spawn sub-agents in milliseconds, "we'll reconcile at month-end" stops being a strategy.
Stigg 2.0 is our answer: the usage runtime for AI products. It decides what every customer, user, team, and agent is allowed to do, the moment they try. Credits, metering, entitlements, and governance in one system that sits alongside the billing stack you already have.
It's free forever for AI startups, because we want you building your product, not rebuilding ours. When you land the enterprise deal that breaks your homegrown system, we'll already be there.
We're launching at the AI World Fair. We'd love your honest take, try it, push on it, and tell us what's missing.