AI Engineering
AI Engineering for Defense and Federal Programs
Agentic AI, RAG and secure generative AI, deployed in environments you control.
Senior engineers who build AI systems for DoW and federal civilian programs, with the same modern software practice as everything else we ship, and a person in the loop where it matters.
What We Build
We build the AI systems that run inside government software, and engineer them to be reliable, reviewable and deployed where your data already lives.
Agentic AI systems: single- and multi-agent workflows that plan, use tools and hand off work, scoped to well-defined tasks.
Loop engineering: the agent loop (plan, act, observe, evaluate) with tool permissions, guardrails, evaluation harnesses and human-in-the-loop review checkpoints.
RAG & grounding: retrieval-augmented generation grounded in your documents and data, with cited sources so answers can be checked.
Secure LLM deployment: models deployed in environments you control, including Amazon Bedrock and AWS GovCloud (US), so prompts, data and outputs stay inside your boundary.
MLOps & LLMOps: versioning, evaluation and observability for model quality, latency, cost and drift in production.
Applied machine learning: production models with human feedback loops, such as threat-detection classification that analysts review and the model is retrained on.
Built by Thazen · Topsoil
Topsoil: The Private AI Coding Agent We Built and Use
Topsoil is Thazen’s private AI coding agent, and our own engineers use it every day. It runs in your own environment, so your code and data stay there. Every change it proposes arrives as a pull request for a person to review.
In Practice
AI Systems Our Engineers Have Delivered
Outcomes are described qualitatively; we publish metrics only with customer approval.
Federal Civilian · Production AI/ML
AI-Driven Threat Detection for the U.S. Courts
A machine-learning model that triages online content for threats, with analysts confirming results and retraining the model on their corrections.
Navy · GenAI Prototype
AI-Enabled Proposal Evaluation on Amazon Bedrock
RAG over past proposals with cited answers, serverless on AWS and designed for AWS GovCloud (US). NAWCTSD Prize Challenge semi-finalist.
DoW-Funded · GenAI Training
GenAI Roleplay and Performance Analytics
Persona-driven roleplay and rubric-based feedback for interpersonal-skills training, built side by side with Design Interactive.
Defense and federal work is delivered as a subcontractor or team member; the company we work through is named on Program Experience.
Technologies We Use
- Amazon Bedrock
- AWS GovCloud (US)
- Azure OpenAI
- LangChain
- RAG
- pgvector
- Evaluation Harnesses
- Guardrails
- AWS Lambda
- Step Functions
How to Bring Us In
Order through MDA SHIELD, use a HUBZone set-aside, or add Thazen to your team as a subcontractor. Our engineers work program-embedded, inside your team and your environment. See how to buy or team with us.
Frequently Asked Questions
Can the AI run inside our own environment?
Yes. We deploy models in environments you control, such as Amazon Bedrock in your AWS account or AWS GovCloud (US), so prompts, data and outputs stay inside your boundary.
How do you keep AI output reviewable?
We engineer the loop (plan, act, observe, evaluate) with guardrails and human review checkpoints. AI-generated work arrives as diffs and pull requests, and answers cite their sources so people can check the work rather than trust it.
What is Topsoil?
Topsoil is the private AI coding agent our engineers built and use. It runs in your own AWS account on Amazon Bedrock and proposes pull requests for a person to review.
Have an AI Idea That Has to Stay Inside Your Boundary?
We will help you scope it, build it and keep it reviewable.