AI features that survive contact with real users — scoped, evaluated, and wrapped in guardrails.
Book a callAnswers grounded in your documents and records — retrieval done properly, with citations, so the assistant says "I don't know" instead of inventing.
Extraction, classification, and summarization over the PDFs, emails, and forms your team processes by hand — with structured, validated output landing in your systems.
Multi-step work — triage, drafting, reconciliation — executed by an agent that pauses for approval where the cost of being wrong is real.
The answer to "where is that documented?" — search and synthesis over your wikis, tickets, and files, scoped by permission.
The feature your roadmap already wants — summarize this, draft that, flag these — engineered into your product with cost and latency budgets designed in.
Grounding a model in your data beats teaching it your data in almost every business case — cheaper, auditable, and it updates when your data does.
A test suite of real cases scores every change to prompts, models, or retrieval. "It seems better" is not a deployment criterion.
Model responses are schema-validated before they touch your systems. The failure case is designed first: fallbacks, escalation to a human, and visible confidence.
Find where AI earns its keep in your workflow — and where it does not. Feasibility spike on your real data.
Weekly increments with evals running from week one; the demo is never ahead of the measured quality.
Monitor quality and cost in production, iterate on the eval failures, or hand over the harness.
The one your constraints pick — quality bar, latency, cost, and data policy. We are provider-agnostic and design so the model is a swappable part, not a foundation.
No training on your data. Provider agreements, retention settings, and the exact data flow are documented as a deliverable — including what never leaves your systems.
It sometimes will be — so that case is engineered first: schema validation, confidence thresholds, human checkpoints where errors are expensive, and evals that catch regressions before users do.
Thirty minutes, no deck, no obligation. We'll tell you honestly if it's not a fit.
Book a call