Readiness assessment
One week. Map data quality, access controls, and system architecture against a realistic AI use case.
- Data quality scorecard
- Access + policy review
- Use-case shortlist
- Go / no-go recommendation
For companies that are AI-curious but hesitant to execute, we scope practical integrations tied to real workflows, risk controls, and measurable outcomes. We can lead end-to-end, co-deliver with your existing team, or ship an AI project your team can use and operate with confidence.
Most "free consultations" are 60-minute sales calls. Ours isn't. The hour is structured so you walk away with a tailored deliverable — a use-case shortlist, a risk register, and a go / no-go decision — not a recycled deck.
You walk us through your stack — data, design, access. Schema and a few PII-stripped sample rows is all we'll ever take away.
We synthesize a representative dataset from your schema and ship a tailored notebook — no production data leaves your perimeter.
15-min presentation of the notebook, 15-min discussion. You leave with a scoped pilot proposal — or a clear "not yet".
We don't sell pilots that never reach production. Every AI engagement is scoped against a defined production rollout from day one — even if the pilot fails the evaluation framework and gets killed.
One week. Map data quality, access controls, and system architecture against a realistic AI use case.
4–6 weeks. Build a scoped pilot against a single workflow. Evaluation framework + governance guardrails included.
4–8 weeks. Hardening, observability, on-call setup. Handoff to your team with runbooks and a 30-day office-hours window.
Practical, workflow-tied AI integrations. We avoid demoware. Every use case below maps to a measurable outcome — throughput, ticket resolution, time-to-answer, or cost reduction.
An LLM-based assistant that answers metric questions in plain English by routing through your certified semantic entities — not raw warehouse SQL.
An LLM agent reviews dbt PRs for lineage impact, policy violations, and breaking-change risk before they reach a human reviewer. Cuts review queue time >60%.
A scoped, governed chat surface inside your product that lets customers ask questions of their own data — behind your row-level security and your usage metering.
30–60 minutes with a senior engineer. We'll map your use case to a realistic production path or tell you it isn't one yet.