AI Integration for Existing Apps

We integrate frontier model APIs into your existing web, mobile, or back-office systems with clean abstractions, sane cost controls, and the ability to swap providers without a rewrite.

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AI Integration

Add AI to apps you already have — without architectural drama.

A clean integration layer between your application and the LLM provider(s) — versioned, observable, and reversible.

Common signs your team is overdue for ai integration:

  • Direct OpenAI calls scattered across the codebase — impossible to swap or monitor
  • No retries, no timeouts, no fallbacks when the API hiccups
  • Surprise bills from runaway prompts and verbose responses
  • No tracing — when an answer is wrong, you can’t tell why

What we build for ai integration:

  • Provider-agnostic adapter (OpenAI, Anthropic, Bedrock, Vertex, Azure)
  • Prompt versioning with diffable history
  • Streaming, retries, timeouts, fallbacks across providers
  • Token-budget controls and per-feature cost dashboards
  • PII redaction and audit logs where required
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Capabilities

Smart places to start

Clean integration layer — outcomes our clients keep coming back for.

Smart drafting

Inline AI-assisted writing in your app — emails, descriptions, summaries.

Auto-classification

Tag, route, or prioritize incoming items using a small, cheap LLM call.

Semantic search

Replace keyword search with embedding-powered semantic search.

Structured extraction

Turn free-text inputs into validated JSON for your business logic.

How we deliver

Integration sprint

01

Audit

Review where AI fits in your app today (or could). Identify quick wins.

02

Architect

Design the abstraction layer, observability, and cost controls.

03

Implement

Ship the first feature behind a feature flag with full tracing.

04

Expand

Roll out additional features on the same foundation.

Tools & platforms we use:

OpenAI Anthropic AWS Bedrock Vertex AI Azure OpenAI Vercel AI SDK LangChain Node.js Python Langfuse

FAQ

Questions teams ask us about AI Integration

Can we keep using our current stack?
Yes. We integrate with whatever you have — Rails, Django, .NET, Node, Laravel, mobile native. The integration layer is small and unopinionated.
Will we be locked into one model provider?
No — that’s the point of the adapter. You can A/B test models and swap providers feature-by-feature.
How long does it take to get to production?
Most projects ship a real, usable system in 3–6 weeks. Discovery is 1–2 weeks; build sprints are weekly with demos.
Will my data be used to train models?
No. We default to enterprise tiers (OpenAI, Anthropic, Bedrock, Vertex) that don’t train on your data. For sensitive use cases, we deploy open-weight models on your infrastructure.
How do you control costs?
We design cost-aware from day one — model routing (cheap model first, escalate when needed), caching, batch processing, and per-user budgets with alerts.
Can you work with our existing engineering team?
Yes. We embed alongside your team, transfer ownership progressively, and document everything we build.