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AI integration for existing platforms, without a rebuild

Your platform already works. We plug intelligence into it. Invoice extraction, document review, smart search, summaries, classification, all added to your existing Next.js, Node, PHP or Python codebase with schema validation, retries and fallback models so the feature degrades gracefully instead of taking your product down with it.
Get an estimatefrom $5,000 · 3 weeks

Sound familiar?

The rebuild nobody can afford

Every AI agency wants to start from scratch. You have paying customers on the current platform and a roadmap that cannot pause for six months while someone rewrites what already works.

Demos that break at real volume

A prompt that looks perfect on ten sample documents fails on the eleventh layout. Without validation, retries and test sets, AI features embarrass you in front of customers.

Costs that nobody forecast

Model bills climb with usage and nobody owns the number. Features ship without caching, token budgets or model routing, and finance finds out when the invoice arrives.

What you get

  • Integration architecture doc
  • Extraction and validation pipeline
  • Schema-validated model outputs
  • Retry and fallback-model logic
  • Accuracy test set and reports
  • Streaming UI components
  • Usage and cost dashboard
  • Handover and runbooks

Stack and tools

  • Claude API
  • OpenAI API
  • Next.js
  • Node.js
  • NestJS
  • Python
  • Zod
  • PostgreSQL
  • Prisma
  • Redis
  • Sentry

How we do it

  1. 1

    Map the seam

    We read your codebase and data flows, then pick the smallest surface where AI adds value. The integration plan names every endpoint, model call and failure path before code starts.

  2. 2

    Build with test sets

    Real documents and records become the test set. Every prompt or model change runs against it, with field-level accuracy checks, before anything reaches your staging environment.

  3. 3

    Harden

    Outputs are validated against schemas, calls get retries, timeouts and a fallback model, and usage is metered per feature so cost and latency stay inside the budget we agreed.

  4. 4

    Ship and watch

    The feature goes live behind a flag, we monitor accuracy and spend for two weeks, tune, then hand over documentation and runbooks your team can maintain without us.

Starting at

from $5,000

Typical timeline 3 weeks. One feature, production-ready, with tests and monitoring.

Get an exact quote

Related work

AI Integration: questions people ask

Further reading

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Let's scope your ai integration project.

Tell us what you are building or what is slowing you down. We reply within one business day.

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