Data Engineering & Analytics
The pipelines and warehouses that make everything downstream trustworthy: dashboards, models, reporting.
- ETL / ELT pipeline design and modernization
- Data warehousing and lakehouse architecture
- Mission-facing dashboards and recurring reporting
- Data quality, lineage, and governance frameworks
Applied AI & Machine Learning
Models built for a specific mission outcome, with the documentation an oversight board will actually ask for.
- Use-case triage, including when AI is the wrong tool
- Model development, evaluation, benchmarking, and error analysis
- Retrieval-augmented systems over agency documents and data
- LLM application work: prompting, tool use, grounding, guardrails
- Responsible AI review aligned to the NIST AI RMF
- Human-in-the-loop deployment and drift monitoring
- Scoped pilots with measurable, pre-agreed success criteria
AI Training & Enablement
Working sessions on your systems and your data, so the capability stays after the engagement ends.
- Hands-on workshops for engineers, analysts, and data teams
- Practical LLM use: what works, what fails, how to tell the difference
- Building an evaluation habit: writing test sets, reading results
- Responsible and secure AI use: data handling, review, disclosure
- Executive and program-level sessions on realistic scope and risk
- Runbooks and handover training so operations stay in-house
API Engineering & Integration
The interface layer other teams build against, designed so a change on your side doesn't break theirs.
- Contract-first design with OpenAPI and JSON Schema
- REST, GraphQL, and event-driven interfaces
- Gateway policy: authentication, authorization, throttling, quotas
- OAuth 2.0 / OIDC and mTLS for service-to-service identity
- Versioning, deprecation paths, and consumer contract tests
- Idempotency, retry, and backpressure behavior under load
- Developer documentation and sandbox environments
Security Engineering
Security treated as a design input, so the assessment confirms what's already true instead of discovering it.
- Threat modeling and architecture risk review
- SAST, DAST, dependency, and container scanning wired into CI
- Secrets management, key custody, and rotation
- Least-privilege IAM and network segmentation
- Encryption in transit and at rest, with key ownership documented
- Audit logging, log integrity, and detection use cases
- Control mapping against NIST SP 800-53 and OWASP ASVS
- Vulnerability triage and remediation workflow
Technology Consulting & Advisory
Sometimes the useful deliverable is a decision. We give you a neutral technical read, in writing.
- Architecture and code review with written findings
- Modernization roadmaps and sequencing
- Build, buy, or extend recommendations with tradeoffs named
- Technical risk assessment ahead of a major release
- Engineering process and delivery-practice review
- Second opinion when a program has competing technical positions
Legacy Modernization & Systems Integration
Getting off a brittle system without breaking the mission that depends on it.
- Mainframe and monolith decomposition
- API-first re-platforming
- Data migration with reconciliation and rollback plans
- Integration across existing agency systems and vendors
Cloud & DevSecOps
Environments built to pass a security review the first time, not the third.
- ATO-ready environment design (GovCloud / Azure Government)
- CI/CD pipelines with embedded security scanning
- Continuous monitoring and POA&M support
- Infrastructure as code and cost governance
The practices that stay the same across every service line
Findings in writing
Assessments, architecture decisions, and tradeoffs are documented as we go, so the reasoning survives staff turnover on both sides.
Small increments, working software
Progress is demonstrated on a running system rather than reported as percent-complete against a plan.
Handover is part of the work
Documentation, runbooks, and training are built during delivery, not assembled at the end. If you want to bring the system fully in-house, that should be a decision, not a negotiation.
We scope the engagement to the outcome you need, not to the number of people we'd like to keep busy.
Not sure which service line fits?
Send us the problem, not the procurement language. We'll map it to the right scope.