01 · Frame
Define
Name the decision, user, data source, and measurable outcome.
AI/ML & Data Management
Turn governed data into a decision.
We connect governed information and Microsoft's Azure AI platform to the workflows federal teams already rely on — search, document processing, and the data layer underneath both.
Signal monitor● Human accountable
Source quality VerifiedConfidence 0.92
Interactive workbench
Choose the capability to explore.
Search, document processing, and the data foundation underneath both — each built on Microsoft's Azure AI platform.
Make the corpus navigable.
Azure AI Search and Azure OpenAI Service turn dispersed documents, records, and policy into a permission-aware place to start.
- Index content with useful metadata and taxonomy.
- Respect identity, permissions, and retention rules.
- Return sources with every answer.
Extract the work hiding in documents.
Azure AI Document Intelligence, Vision, Language, Speech, and Translator convert high-friction inputs into structured signals.
- Classify and route incoming documents.
- Capture fields, entities, tables, and exceptions.
- Keep a review queue for uncertain results.
Govern the source before you build on it.
Structured data in SQL Server, semi-structured XML and JSON in Cosmos DB, and unstructured files in Blob Storage — kept accurate through regular audits, validation checks, and cleanup, including FOIA tracking and document management.
- Structured, semi-structured, and unstructured data each in the right store.
- Regular audits, validation checks, and cleanup.
- FOIA tracking and document management built in.
Delivery loop
Govern the signal before it scales.
A model is one component. Data quality, controls, and adoption stay visible from the first workshop through operations.
02 · Prepare
Harden
Clean, classify, permission, and document the source material.
03 · Prove
Evaluate
Test accuracy, exceptions, latency, and user acceptance.
04 · Operate
Improve
Monitor drift, feedback, access, and the result in production.
Trust architecture
Useful intelligence, with guardrails.
A result is easier to adopt when the controls are visible. Every engagement leaves the team with a source, a review path, and an operating measure.
Defined question
A named decision and user before a model is selected.
Governed source
Metadata, identity, retention, and access considered up front.
Human review
Exceptions and low-confidence results have an explicit handoff.
Measured outcome
Accuracy, time, adoption, and mission impact are tracked.
- Stack
- Applied to
- Natural language processing, image recognition, predictive analytics, and workflow automation, scoped to the agency's own data.
- Credentials
- Proven on
- Moving DHS Into the Cloud