Praxis
IMTAS’s applied AI lab. Every solution we engineer is designed to run inside secure federal cloud enclaves — ATO-aware from day one, not retrofitted for authorization after the fact.
Designed for the enclave. Not retrofitted for it.
Every solution out of the lab is engineered against federal authorization boundaries from day one — ATO-aware architecture, NIST AI RMF alignment, FedRAMP-ready deployment patterns. Built in, not bolted on.
Mission outcomes from every angle — strategy, leadership, delivery, growth.
Four pillars define our practice. They map to how federal AI work actually has to be done.
Practice Architecture & Strategy
A defined portfolio, not a catalog of capabilities. Our AI solutions strategy spans data, analytics, automation, and generative AI — grounded in federal compliance reality. Pragmatic build, buy, and partner decisions with responsible AI guardrails aligned to the NIST AI RMF.
Client-Facing Solution Leadership
We translate federal mission needs into architecturally sound AI solutions. Advising agency CIOs, CTOs, CISOs, and program managers with independent credibility on AI adoption, change management, and organizational readiness.
Technical Architecture & Delivery
Production AI inside federal cloud enclaves — not POCs. ATO processes, FedRAMP-authorized platforms, AWS GovCloud and Azure Government enclaves, and data classification controls. End to end.
Growth & Go-to-Market
Win and deliver, end to end. Win strategies, technical proposal volumes, and direct client engagement during solutioning. We build and mentor AI and analytics practitioners capable of delivering confidently and independently.
Five repeatable solutions. Engineered for the enclave.
What the lab is building. Each one is designed to run inside a federal cloud enclave from day one — not retrofitted for one after the fact.
AI-Augmented Cybersecurity Operations
LLM-driven reverse engineering, AI-powered SOC analytics, and intelligent automation embedded in federal cybersecurity workflows. Designed to run inside federal cloud enclaves.
- LLM-driven reverse engineering for mobile and binary artifacts
- ML-driven SIEM analytics — Splunk MLTK, Enterprise Security
- Incident response automation with mandatory human approval gates
- RAG-enabled threat intelligence with citation provenance
- AI governance: model risk management, explainability, audit trails
GRC Automation & cATO
AI-driven control mapping, evidence collection, and continuous ATO workflows. RegScale-anchored, NIST AI RMF aligned, designed for agencies operating under continuous monitoring mandates.
- AI control mapping against NIST 800-53, NIST AI RMF, CMMC
- Continuous evidence collection — audit cycles compress from quarterly to real-time
- SSP narrative generation — ISSMs review, not write from scratch
- POA&M intelligence with risk-weighted prioritization
- cATO posture dashboard for AOs and SCAs
- Purpose-built NIST AI RMF module for AI/ML systems
AI Service Operations Modernization
LLM-driven triage, knowledge retrieval, and intelligent automation integrated into federal-grade ITSM workflows. Elevates service desk delivery from ticket throughput to mission outcomes.
- LLM-driven ticket triage — classification, priority, routing in seconds
- Citation-grounded knowledge retrieval (RAG)
- Live AI agent assist during ticket handling
- Intelligent self-service for routine requests
- Agentic workflows for provisioning, change requests, approvals
- Drops into your existing ITSM — no re-platform required
Mission-Ready Generative AI
RAG-enabled mission applications, AI copilots, and agentic workflows designed for deployment inside federal cloud enclaves with embedded CI/CD and responsible-AI guardrails.
- RAG knowledge bases with full provenance on every response
- Role-specific AI copilots embedded in existing workflows
- Agentic workflows on MCP integration patterns with human approval gates
- Multi-model abstraction: Anthropic Claude (Bedrock), Azure OpenAI Government, on-prem open models
- Document understanding for contracts, regulations, briefings, intelligence reports
- Responsible AI engineering: NIST AI RMF Govern / Map / Measure / Manage embedded in the build
Intelligent Automation Practice
UiPath, agentic AI, intelligent document processing, and process orchestration — with precedent-setting federal ATO experience the rest of the market lacks.
- UiPath implementation and ATO — authorization-aware architecture, control evidence design
- Agentic AI workflows on MCP integration patterns
- Intelligent document processing for federal documents
- Process orchestration across ITSM, ERP, identity, and custom federal systems
- RPA-to-agentic migration without disrupting current automation value
- Financial management automation: invoice processing, CPSR preparation, audit support
Every Praxis solution is engineered compliance-native. Aligned to NIST 800-53 Rev 5, NIST AI RMF, and FedRAMP boundary requirements — and built to operate inside AWS GovCloud, Azure Government, and DoD IL5 / IL6 environments.
Get the AI working. Then try to get it accredited.
Most firms treat ATO as a downstream review — a compliance hurdle to clear after the system is built. That assumption fails inside federal boundaries. POCs that can’t survive authorization review never reach mission use, no matter how polished the demo.
Start with the authorization boundary.
We design solutions we can actually build. Each Praxis offering has a reference architecture, a defined delivery model, a partner ecosystem, and a team trained to deliver it — engineered against federal authorization boundaries from day one, not pitched as a slide deck.
We value solutions that are secure, explainable, and scalable over impressive demonstrations that cannot survive an ATO or an agency change-management process.
Contact Us
Stephen Renner
Director of Solutions · Field CTO