AI API & Platform Development
Turn an AI model into a service other teams and partners can build on. We design and ship the APIs, auth, and infrastructure that let your AI run as a real platform, not a single app.
of internal AI APIs are rebuilt from scratch by a second team within a year
Once an AI capability proves useful, more than one team wants it. Without a real API, each one wires up its own version, with its own auth, its own rate limits, and its own bugs. A proper AI platform stops that. Build the API once, document it well, and every future product or partner calls the same reliable service instead of reinventing it badly. Expose your document-extraction model once as a versioned, rate-limited API and finance, legal, and ops all consume the same endpoint rather than maintaining three brittle copies.
Inside AI APIs & Platforms
AI API and platform development is the build of the layer that lets an AI capability be reused, not rebuilt, every time a new team or partner needs it. Instead of wiring a model into one application, we package it behind a versioned API with proper authentication, rate limiting, and documentation — so internal teams, partners, or customers can call it directly. You end up with infrastructure other products are built on top of, not another one-off integration.
API design — we design clean, versioned endpoints around how the AI capability is actually consumed, not just how the model happens to work internally.
Authentication and access control — we set up OAuth or API key auth with scoped permissions, so internal teams, partners, and customers each get the right level of access.
Rate limiting and quotas — we build usage limits and throttling per client, so one heavy consumer cannot degrade the service for everyone else.
Gateway and routing — we put an API gateway in front of the platform to handle traffic, versioning, and request routing in one place.
Documentation and developer experience — we write API docs, SDKs, or example code so other teams can integrate without asking you questions every week.
Observability and SLAs — we set up usage metrics, latency tracking, and error monitoring so you can stand behind a real uptime and performance commitment.
Is this right for you?
This service fits best when you recognise yourself below.
Teams whose AI model or capability is already used by more than one internal product.
Companies planning to expose an AI capability to external partners or customers.
Platform and infrastructure teams asked to support AI as a shared internal service.
Organizations tired of every new team rebuilding the same AI wrapper from scratch.
The problems behind the brief
The same AI logic rebuilt by every team
Without a shared API, each product team wires up its own version of the same capability, with its own bugs. We build it once, properly, behind a real API.
No access control between consumers
An open endpoint with no auth is a security and cost risk waiting to happen. We scope access by client so each consumer only gets what it needs.
One heavy user breaks it for everyone else
A single runaway script or partner integration can take down a shared service with no rate limiting. We build quotas and throttling in from day one.
Partners cannot integrate without hand-holding
Undocumented APIs mean every partner integration turns into a support thread. We ship documentation and examples that let teams self-serve.
No visibility into who is calling what
Without usage metrics, you cannot price, support, or scale the platform with confidence. We build the observability layer in alongside the API itself.
A clear, repeatable process
No mystery. You always know what happens this week and what comes next.
We map who will consume the API and how, then design the endpoints, versioning strategy, and access model around real usage patterns.
We build the API layer, authentication, rate limiting, and gateway routing, wiring it to the underlying AI model or service.
We load-test the platform, tune quotas and limits against real traffic patterns, and add monitoring, alerting, and error handling.
We finalize documentation and SDKs, onboard the first consumers, and hand over runbooks so your team can operate the platform independently.
Deliverables
Concrete outputs you keep — not just a conversation.
What good looks like
One AI API powering multiple products or partners instead of separate rebuilds.
Documented rate limits and uptime that hold under real, multi-client traffic.
Partners and internal teams integrating without ongoing manual support.
Usage data clear enough to support pricing, scaling, or SLA decisions.
The stack behind the work
We pick tools to fit your needs, never vendor relationships.
Engineering
- FastAPI
- GraphQL
- REST APIs
API Gateway
- Kong
- AWS API Gateway
Authentication
- OAuth 2.0
Cloud
- AWS
- Google Cloud Platform
Common questions about AI APIs & Platforms
Straight answers to the questions we hear most.
Still have questions? Talk to our team
The natural next step
An API is only as good as what sits behind it. If the underlying model is not built yet, Custom AI Applications covers that ground first. If the capability already lives inside one product and just needs wiring elsewhere, AI Integration may be the faster path.
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