What it is
Most products don’t need to be rebuilt around AI. They need one or two well-chosen features that make a common task faster: answering questions over your documentation, summarising long records, drafting text in the right format, or turning unstructured input into clean data.
We build those features inside your existing product, working alongside your engineering team, so they ship on your release process and stay maintainable after we leave.
Who it’s for
- SaaS companies whose customers keep asking “can it do this with AI?”
- Product teams with a clear use case but no in-house experience running LLMs in production.
- Companies with large knowledge bases, support histories or document libraries that are hard to search.
How we deliver
- Pick the right feature. We look at your usage data and support tickets to find a task that is frequent, tedious and tolerant of the occasional imperfect answer. Then we write down what “good” looks like.
- Evaluate before polishing. We build a quick prototype against a test set drawn from your real data and measure answer quality, latency and cost per request. If the numbers don’t work, we say so before you spend more.
- Build retrieval properly. For RAG features, most of the quality comes from ingestion and retrieval rather than the model. We handle document parsing, chunking, metadata, hybrid search and permissions so users only see what they are allowed to.
- Integrate cleanly. We work in your repository, follow your conventions and open pull requests your team reviews.
- Instrument everything. Traces, feedback buttons and cost dashboards go in with the feature so you can see how it performs after launch.
What you get
- A production feature in your product, behind a feature flag if you want a staged rollout.
- An evaluation suite your team can run whenever you change models or prompts.
- Observability for quality, latency and spend per request.
- Clear documentation of prompts, retrieval settings and known limitations.
- Provider-agnostic code, so switching models is a configuration change rather than a rewrite.
