MITHRILDATA GROUP
Approach

How an engagement runs

Four stages, in order. Each one ends with something your team can use, whether or not you continue to the next.

  1. Assess

    Map your sources, jobs and dependencies. Measure data quality. Agree on what success looks like and how it will be measured.

    You receive

    • System and dependency inventory
    • Data quality findings, ranked by impact
    • Prioritized roadmap with effort estimates

  2. Modernize

    Migrate and rebuild pipelines in the cloud. Run old and new side by side, and reconcile until the numbers match.

    You receive

    • Migrated databases and integration jobs
    • Reconciliation reports for every wave
    • Signed-off cutover

  3. Operationalize

    Automate schedules, add monitoring and alerting, and hand over documentation your team can run without us.

    You receive

    • Automated schedules with service levels
    • Monitoring and alerting in place
    • Runbooks and a knowledge-transfer session

  4. Enable AI

    Pilot an AI use case on the governed data, test it against real questions from real users, and scale what works.

    You receive

    • A working pilot on your own data
    • Test results against agreed questions
    • A plan to scale, or a clear reason not to
A good place to start

AI Readiness Assessment

The Assess stage, packaged as a fixed-scope engagement. Scope and price are agreed before work starts. You leave with a clear picture of what is ready for AI today, what needs work, and a prioritized plan to get there.

It stands on its own. If you choose to do the work with another firm or your own team, the plan still holds.

  • Inventory of sources, pipelines and schedules
  • Data quality and governance gaps, ranked by impact
  • Cloud migration path and effort estimate
  • One AI use case scoped for a pilot
  • Executive summary and a working session to walk through it
Principles

How we work on every project

Reconcile before cutover

No system is switched off until the new one produces the same numbers, row for row.

AI only on governed data

If we can't trace where an answer came from, it doesn't go into production.

Document as we go

Models, mappings and decisions are written down while the work happens, not at the end.

Your team owns the result

Every engagement ends with a handover your people can run without us.

Start with the assessment.

Tell us about your systems and what you want AI to do. We'll suggest a scope.

Start a conversation info@mithrildata.com