AI-driven API integrations

Turn signed merchants into live merchants — faster.

Every merchant integrating your API hits a wall. inaigai reads your codebase and hands them the exact fix — in the response itself, whether it failed or just quietly didn't work. They go live faster. Your team gets its time back.

See the live demo → Become a design partner

Your API's responsea 200 that isn't success

HTTP 200
{
  "payment_id": "pay_QoT4x…",
  "status":     "requires_payment_method"
}

+ _ainothing failed — and nothing was charged

{
  "issue":  "confirm:true with no payment method",
  "why":    "authorises at creation — none supplied",
  "fix":    "send payment_method_data, or drop confirm",
  "source": "api_models/payments.rs:1226",
  "confidence": 0.94
}

Grounded in your code — not guesswork Sandbox-only — never in production Your code stays private

What just changed

Your codebase can finally answer for itself.

Until recently the only thing that could explain your API was a person who had read it — so that knowledge lived in one engineer's head, and arrived on that engineer's schedule.

Until now

"Why was this rejected?"

→ a ticket · a thread · a call

→ an engineer who has read the code

→ tomorrow, maybe

Now

"Why was this rejected?"

→ answered from the code that rejected it, in the response

Where integrations stall

Merchants don't stall on your docs. They stall waiting for your engineers.

Docs and guides are reference material. What a developer integrating your API actually needs is someone who knows your code and your best practices — and that person has a queue.

Where the weeks actually go — one merchant, one integration

Their engineer

Yours

Reads the docs, builds the first call 1–2 days—
Response comes back wrong — or right, but nothing happened blocked—
Re-reads the docs. The field involved is listed as optional half a day—
Raises a ticket, and stops waiting30–60 min to reproduce
Waits for the reply 1–3 dayscontext switch
Then hits the next surprise × 4–6 per integration× every merchant

— of their calendar spent waiting rather than building

— of your senior engineers' time, per merchant, answering the same things

Conservative mid-points of the ranges above, not a benchmark — adjust them against your own onboarding and the arithmetic still holds.

So what does that cost you? Use your own numbers.

Merchants signed a year Average contract value Weeks from signature to live

—

of signed revenue sitting behind integration at any moment

—

pulled forward for every two weeks you take out

Your figures, your arithmetic — merchants × contract value × (weeks ÷ 52). We make no claim about how many weeks we remove; that is what the design partnership is for.

Watch it happen

A 200 that wasn't success — explained in the response.

No error to search for. No ticket. Answered where it happened.

POST /payments

Merchant request

{ "amount": 6540, "currency": "USD", "confirm": true }

Response

sending…

HTTP 200 — looks fine
{ "status": "requires_payment_method" }

+ inaigai · grounded in your code

issue   confirm:true, but no payment method was sent
so      the intent is parked at requires_payment_method — nothing charged
fix     include payment_method_data now, or drop confirm and confirm later
basis   your own field docs · confidence 0.94

Caught before it became a support ticket.

A merchant fires a call at your API…

days → minutes

To resolve one error

self-served

Tickets never raised

weeks sooner

To first revenue

The solution

Every merchant gets an engineer who knows your code, from their first call.

It reads your codebase and works two ways: live on every API response, and on demand in the Assistant. Same engineer. Same grounding.

Grounded in your code, not your docs

Docs are what you meant. Code is what you shipped. The hard integration problems live in that gap — and inaigai answers from the code.

It never touches production

Sandbox only, additive by design. Your API contract is untouched, and your production path is never in scope.

Right or silent — never a guess

Every answer traces to a specific line of your code. When it can't be certain, it says so and escalates. A confident wrong answer is worse than none.

Ready for the agents, too

A developer reads it today. An agent consumes it tomorrow. An agent working against an API it doesn't understand needs grounded truth more than a human does — not less.

The _ai enrichment block — one grounded truth, rendered for its consumer

● Diagnostic · grounded fact

The currency field was rejected. You sent "Dollars", but the validator requires an ISO-4217 code — send "USD". This is the root cause; the two downstream errors resolve once it's fixed.

source · billing/validators.rb:42 · confidence 0.94

Optimisation · advisory

You're creating charges one at a time. For more than five items, /charges/batch cuts the round-trips — based on the journeys that actually succeed in your sandbox.

evidence · observed_journeys · confidence 0.81

Suggested request · you apply it

A corrected payload is ready — currency changed from "Dollars" to "USD", sandbox-verified to pass. Never applied for you: auto_apply: false.

tier · correction · sandbox_verified: true

"_ai": {
  "schema": "rfc7807+ext",
  "issues": [                     // reactive — what is wrong
    { "class": "validation_error", "root_cause": "field_format_invalid",
      "field": "currency", "expected": "ISO-4217", "received": "Dollars",
      "is_root": true, "confidence": 0.94,
      "source_refs": ["billing/validators.rb:42"] }
  ],
  "optimizations": [              // proactive — what could be better
    { "type": "endpoint", "suggestion": "use /charges/batch for >5 items",
      "evidence": "observed_journeys", "confidence": 0.81 }
  ],
  "suggested_request": {          // materialised, never auto-applied
    "changes": [ { "field": "currency", "from": "Dollars", "to": "USD",
                 "reason": "ISO-4217 required", "tier": "correction" } ],
    "sandbox_verified": true, "auto_apply": false
  },
  "journey": { "name": "subscription_create", "step": 3 },
  "confidence": 0.92
}

One canonical truth, produced once. A human reads it as prose; an agent consumes the structured core. Same grounding, different surface.

What changes

Faster go-lives, a lighter support load, and nothing changed in your API.

Every integration is felt three times: by the developer who is stuck, by the engineer answering them, and by the revenue waiting on both.

1 · The developer

Every developer gets a senior engineer on call

The fix arrives inside the response they just got — grounded in your code, never a guess.

They stay in flow and keep moving. No ticket, no waiting.

2 · Your team

Your engineers stay on the roadmap

The same questions get answered before they reach your inbox — from the same code your engineer would have quoted.

Your senior engineers ship product instead of repeating themselves.

3 · Revenue

Merchants start earning sooner

Integrations activate in days, not weeks. Every merchant you sign reaches revenue faster.

Every go-live pulls payback forward.

Merchants choose the API that respects their time. And they stay.

Nothing changed in your API

Verbatim in, verbatim out.

Your API's behaviour never changes. inaigai adds one namespaced _ai block on the way back — and nothing else.

Merchant calls your API endpoint

inaigai forwards the payload verbatim

Your sandbox responds as it always does

Verbatim response + _ai block appended

● Verbatim

Body, status and headers come back untouched. The enrichment is additive, in a namespaced _ai key.

● Non-intrusive

inaigai never mutates the call. It observes, grounds, enriches. Nothing else.

● Failsafe

If inaigai is down, calls route straight to your API. The block is simply absent. Nothing breaks.

See it in action

Watch a rejected call, and an opaque success, explain themselves — on a real open-source codebase

Open the live demo →

Proof

Don't take our word for it.

We have no customer logos to show you yet. What we have is something better for an engineer: a demo running on a real codebase you can inspect yourself.

A real codebase, not a mock

The demo runs on HyperSwitch — an open-source payments platform. Every answer it gives comes from that repository, not from a script we wrote for the demo.

Measured, not asserted

Accuracy is scored against real, labelled integration failures with known causes — and against a baseline with no codebase access — before anything ships.

Read the code in front of you

Watch it index a codebase and answer from it live, then judge whether it would hold up on yours.

See it on a real codebase

Watch a rejected call, and an opaque success, explain themselves.

Open the live demo →

What inaigai is — and what it is not

What it is

A codebase-grounded truth layer for your API's integration path
Sandbox-only, single-tenant, read-only
A dedicated, isolated deployment in your region — or in your own cloud if your compliance requires it
Your code and data are never shared with anyone and never used to train a model
Additive — your API contract is never touched
Built for two consumers: a developer today, an agent tomorrow

What it is not

An API gateway Kong, Apigee

Gateways route and govern in production. inaigai enriches in the sandbox.

An iPaaS Celigo, Workato

An iPaaS connects apps to each other. inaigai makes your own API easier to integrate with.

A unified API Merge, Nango

Those hide your API behind theirs. inaigai keeps your API exactly as-is, and makes it smarter.

A coding assistant Cursor, Copilot

Those understand code in general. inaigai understands your API's real errors and the sequences that actually succeed.

In your production path ever

inaigai is sandbox-only — at go-live your merchants point straight at your production endpoint. If inaigai is ever down mid-call, the request routes straight through.

Interested?

Ready to see it on your own API?

A dedicated deployment, grounded in your codebase, across your sandbox path. You get a lighter support load, faster go-lives, and a hand in the roadmap.