Data, AI & agents
From a clear use case to an operated workflow
We define one process, measure its baseline and build a controlled production slice — typically in 4–8 weeks. Evaluation, acceptance criteria and the agreed data and operating boundaries determine whether and how it goes live.
Start with a measurable workflow, not a demo
We begin with the process baseline, accountable people and a narrow scope. Together we define allowed inputs, acceptable outputs and the points at which a person must take over. This lets us compare the production slice with today's process instead of merely presenting an impressive demo.
What the first production slice includes
The deliverables include a data and access matrix, a representative evaluation set with acceptance criteria, human approvals and fallbacks, monitoring and tracing, and an operating and rollback runbook. The controlled slice is a limited real workflow — not an isolated proof-of-concept demo and not a blanket go-live guarantee.
Decide from measured results
We compare the baseline and production slice using the agreed measures: cycle time, acceptance and correction rate, exception and escalation rate, cost per completed workflow, and quality and operating metrics. The accountable people then decide whether to expand, adjust or stop.
Review data and service boundaries per use case
Before implementation, we document the concrete data flow, participating Microsoft and third-party services, processing regions, subprocessors, retention and access. The permitted setup depends on the chosen service, region and your requirements; we therefore make no blanket tenant, geo or compliance promise.
Deliverables & controls
- Process baseline, narrow scope and accountable people
- Data and access matrix covering services, regions and subprocessors
- Representative evaluation set and testable acceptance criteria
- Human approval, fallback and defined escalation paths
- Monitoring and tracing for quality, errors, latency and usage
- Operating and rollback runbook with clear responsibilities
Agreed metrics
- Cycle time per case: baseline and result in the slice
- Acceptance and correction rate for proposed outputs
- Exception and escalation rate to accountable people
- Cost per completed workflow including model and platform consumption
- Quality against the agreed evaluation set
- Operating metrics for latency, errors, availability and usage
How we work
We build a narrowly bounded production slice, typically in 4–8 weeks. Before the build, we agree the baseline, scope, acceptance criteria and data access. We then test the evaluation set, human approvals, fallbacks and operating setup. Go-live happens only after documented evaluation and approval — not because a demo looked convincing and not as a blanket timing promise.
Steps
Microsoft & related
These consultants lead projects in this area — they're who you'd actually work with.
Typical project sizes
Orientation, not a quote. Final scope and price are fixed after the Discovery phase — when we both know what actually needs to be built.
1 use case (e.g. invoice extraction, Q&A bot)
Multiple use cases, governance, monitoring
Platform setup, custom models, MLOps
FAQ
Available as
Five ways to start — from a focused assessment to ongoing support.
Let's talk about your Data, AI & agents initiative.
30 minutes is enough to clarify scope, tier and effort. We then send an indicative quote — no slide deck.