Add AI to the app you already have.
Smart search, summarization, generation, embedding-based recommendation, structured extraction. Wired into your existing codebase, evaluated against your real data.
- Starting at
- $18k
- Structure
- Phase-by-phase quote, fixed bid
What you get for the work.
- 01
Real data, real evals
We test against your data, not synthetic prompts. Eval suite ships with the integration so you can detect regressions on model swaps.
- 02
Cost-aware by default
Token budgets per request, cheapest-model-first routing, caching where the input shape allows. The bill stays predictable.
- 03
Inside your codebase
We add the feature to the app you have. No separate "AI service" your team has to maintain in parallel. The seams live with the rest of the code.
- 04
Owned by you
Prompts, evals, API keys, observability all in your accounts. We don't run anything for you after handoff.
What we build it on.
- Claude Opus / Sonnet / Haiku
- Default. Routed by step based on cost and latency.
- OpenAI / Gemini
- When the work calls for a second provider or a router pattern.
- Postgres + pgvector
- Embeddings, retrieval, semantic search in the database you already have.
- Vercel AI SDK or direct Anthropic SDK
- Whichever fits your existing app surface.
- Langfuse / Helicone
- Trace every call, eval every output.
- Inngest / BullMQ
- Background jobs for batch or long-running calls.
$18k buys this. Bigger scope scales it.
Included at the floor
- One AI feature wired into your existing app
- Prompt scaffolding, structured-output schemas
- Token budget and cost-ceiling enforcement
- Eval suite with 20+ test cases against your data
- Observability dashboard for token spend per session
- Two-week support window after launch
What scales the number
- Multiple AI features sharing a common eval harness
- Embedding pipelines over large or live datasets
- Voice or vision integrations (image generation, OCR, transcripts)
- Fine-tuning or distillation onto cheaper models
- Customer-facing chat with retrieval and tools (see AI agents)
What a starter integration looks like
The $18k floor covers a single AI feature inside your app, with prompts, structured outputs, cost ceilings, an eval suite, and an observability dashboard. Two to four weeks. The point is the smallest feature that earns its keep, not a sweeping AI rebrand of your product.
Where the build scales
Adding features. Each new AI feature shares the eval harness and observability layer but has its own prompt design, output schema, and edge cases. Embedding pipelines over live data are a separate chapter (indexing, freshness, retrieval quality). Voice and vision change the cost and latency profile entirely.
What we will not build
AI features whose job is to write your marketing copy in your own voice (use Claude directly, save the integration cost). AI features with no eval. Anything where the success criteria is "feels smart" instead of a measurable lift.
Common questions.
- How is this different from AI agents?
- AI agents are a build, the whole product is the agent. AI integrations are a feature added to a product that already exists. Different scope, different floor price.
- We already use ChatGPT internally. Why this?
- That is sometimes the right answer. We tell you when it is. When the workflow needs to run inside your app on customer data with audit and cost control, an integration is the next step.
- How quickly do you ship?
- Two to four weeks from kickoff for a single integration at the $18k floor. Multi-feature integration work runs four to eight.
- What if our data is sensitive?
- Zero-retention modes on Claude and OpenAI by default. Self-hosted vector stores where compliance requires it. We design for the strictest data class in the system.
- Can you work in our existing codebase?
- Yes. We are comfortable in Next, Nuxt, Rails, Django, Laravel, and most TypeScript or Python stacks. We will ask for a read-only access window during discovery.
- Do you maintain it after launch?
- Two-week support window included. Beyond that we offer monthly retainers for model-update and eval-regression work, sized to the integration.
Pair this build with.
Build this with us.
Twenty minutes through the intake. A real reply within a work day.