Service
AI Integration
Practical AI features woven into your existing product, not bolted on as a demo.
We help teams identify where large language models actually move the needle, then ship production-grade integrations rather than one-off prototypes.
What we deliver
- Retrieval-augmented search and question answering over your own documents and data
- Document extraction pipelines that turn PDFs and scans into structured, validated fields
- Customer support copilots that draft grounded responses for human review
- Internal automation for the repetitive judgment calls that eat your team's week
- Evaluation pipelines, guardrails, and logging shipped with every integration
How the engagement runs
We start with a two-week feasibility sprint: real samples of your data, a working prototype against them, and honest numbers on accuracy, latency, and cost per request. If the numbers hold, we productionize — evals in CI, confidence thresholds with human-review routing, and a fallback path for every model call that fails or comes back uncertain. If they don't hold, you've spent two weeks learning that, not two quarters.
What we watch that demos ignore
Cost per request at your real volume, p95 latency under load, drift when the underlying model version changes, and what happens to the user experience when the model is wrong. Every one of those has killed a promising AI feature somewhere; none of them show up in a keynote demo.
Outcomes you can expect
- A working prototype on your data inside two weeks
- Accuracy and cost numbers you can defend to your board
- AI features with a measured failure mode instead of a surprising one
- A team that can tune prompts and retrieval without calling us back