Tamvate Corporate diagnoses AI opportunities using the CPMAI methodology — classifying the real problem, sequencing only the work it actually needs, and telling you honestly when a simpler solution beats a model.
Every engagement starts the same way: a rigorous diagnostic before any technical commitment. From there, scope depends entirely on what your problem actually needs.
We classify your problem against the seven recognized AI patterns and confirm whether AI is genuinely warranted — before recommending a single tool.
Data readiness assessment, build-vs-buy-vs-integrate analysis, and a technical approach matched to your actual constraints, not the latest trend.
Bias testing, privacy safeguards, and accountability documentation built in from day one — not retrofitted after a launch goes wrong.
Deployment planning, monitoring, and the governance structure to keep a model trustworthy long after launch day.
We follow the CPMAI six-phase methodology — but we scope in only the phases your specific engagement needs. A project with clean, governed data doesn't repeat work it doesn't need.
We confirm this is genuinely an AI problem before we confirm anything else.
We find out what data you actually have, and what state it's really in.
We get that data into a shape a model can actually learn from.
We build, fine-tune, integrate, or buy — whichever is honestly the right call.
We validate performance, fairness, and operational readiness before go-live.
We deploy, monitor, and govern — because launch day is the start, not the finish.
A few honest answers gives us everything we need to prepare before we talk — so when we do connect, we spend the time on solutions, not discovery. Takes about 6–8 minutes.