MITHRILDATA GROUP
Services

Data work that AI can stand on.

Four services, each one built on the same idea: get the data right, move it where it needs to be, keep it running, and then put AI to work on it.

Cloud

Cloud data migration

Move databases and ETL workloads from on-premises servers to Microsoft Azure or Amazon Web Services, or from one cloud to another, such as AWS to Azure.

Old and new run side by side until the numbers match row for row. Cutover happens only when the reconciliation says it's safe.

What you get

  • Inventory of databases, jobs and dependencies, grouped into migration waves
  • Parallel runs with row-level reconciliation reports
  • Cutover and rollback plan for each wave
  • Decommission checklist for the systems left behind

Typical platforms

OracleSQL ServerDB/2Microsoft AzureAWSPowerCenter → IDMC
Foundations

Data modeling & AI readiness

Conceptual, logical and physical data models, with a focus on canonical models: one shared definition of a customer, product or transaction that every system and every AI tool can use.

Then profile and clean the data, and document where it comes from, so an AI answer can be traced back to its source.

What you get

  • Canonical, logical and physical models with a business glossary
  • Data profiling results and quality rules, ranked by impact
  • Lineage documentation from source to report
  • Governance definitions your data owners can sign off

Typical platforms

OracleSQL ServerDB/2InformaticaPython
AI

Generative AI & RAG solutions

Knowledge assistants that answer from your own documents and databases using retrieval-augmented generation (RAG). Every answer cites the source it came from.

They run in your own cloud tenant or on your own hardware, so your data stays under your control.

What you get

  • One use case scoped with the people who will use it
  • Retrieval design over your documents and governed data
  • Testing against real questions before rollout
  • Deployment in your Azure or AWS tenant, or on-premises

Typical platforms

LLM APIsVector searchPythonDockerAzureAWS
Integration

Orchestration & integration

Design the integration jobs, schedules and dependencies that keep data moving on time, across on-premises systems, cloud services and new AI workloads.

Add the monitoring and alerting that tell your team about a failed load before the business does.

What you get

  • Integration mappings and workflows built to your standards
  • Dependency maps and schedules with defined service levels
  • Monitoring, alerting and restart procedures
  • Runbooks your operations team can own

Typical platforms

Informatica PowerCenterInformatica IDMCPentahoStonebranch UAC
How we engage

Three ways to work with us

Pick the model that fits the work. Many clients start with an assessment and move to one of these.

Architecture lead

Architect-led projects

Assessments, migrations and data models led directly by Mithril's principal architect. Best for work where design decisions matter most and a small team moves fastest.

Added capacity

Delivery teams

For larger AI and integration builds, Mithril pairs its architecture lead with an experienced partner development team. Mithril holds the contract and manages delivery, so you have one point of accountability.

On your team

Contract resources

Experienced data, integration and ETL professionals placed on your team on contract, selected and supported by Mithril. Best when you have the plan and need hands.

Not sure where to start?

Most engagements begin with an AI Readiness Assessment. It tells you which of these services you need first.

About the assessment Start a conversation