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AI integration for existing apps
AI integration means adding capabilities like chat, semantic search, summarization, or document understanding to an app you already run, grounded in your own data so the answers are real, not guessed. Most engagements take 2 to 6 weeks.
How AI integration fits into your stack
What's included
- A short discovery of your codebase and data to find where AI actually moves a metric, not where it looks impressive.
- Retrieval-grounded features (RAG) so the model answers from your data, not from memory.
- Evaluation harnesses so we can measure quality and catch regressions before users do.
- Cost and latency budgets set up front, with model choices that fit them.
- Production wiring: auth, rate limits, logging, and a fallback path when a model is slow or down.
How it works
- 01
Discovery
We read the codebase and the data, then pick the one or two AI features with the clearest payoff and the least risk.
- 02
Grounded build
We wire the feature to your data with retrieval, so answers are sourced and checkable, and add an eval suite to keep quality honest.
- 03
Hardening
Cost ceilings, latency budgets, rate limits, and graceful failure when a model is unavailable. The boring parts that keep it usable.
- 04
Handover
You get the feature, the evals, and the runbook. You can extend it without us.
Most AI integrations run 2 to 6 weeks, depending on how clean the data is.
Common questions
Will the AI make things up?
That is exactly what grounding prevents. We wire features to your data through retrieval, so the model answers from the source or admits it does not know, instead of inventing a confident wrong answer.
Which model do you use?
Whichever fits the job, the budget, and your data-residency needs. We set cost and latency budgets first, then choose the model, and keep the option to swap it later.
How do you know it actually works?
We build an evaluation suite alongside the feature, so quality is a number we can track, not a vibe. That is what catches a regression before your users do.
Does our data go to a third party?
Only if you want it to. We design around your data-residency and privacy constraints, including self-hosted or EU-only model options where that matters.
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