Your government jobs are the ones you can't use AI on
Your commercial teams may already use AI to read specs, draft RFIs and summarize submittals. Then a federal or government job comes in with contract terms and data-handling requirements that keep drawings, specs and project records off hosted AI services. So the jobs with the heaviest paperwork, the longest submittal registers and the strictest documentation get none of the help.
The fix is to bring the model to the data instead of sending the data to the model.
- Contract and data-handling terms that rule out hosted AI for some project data
- Heavy submittal, RFI and daily report volume on government jobs
- Two ways of working: one for commercial jobs and one for government jobs
- Uncertainty about what's allowed, so teams avoid AI entirely
Self-hosted AI, built for project work
Self-hosted model environment
Open-weight language models deployed on infrastructure you control, on-premise or in your own cloud environment, with no calls out to hosted AI services for restricted data.
Document tools for government projects
Search and summarize specs, submittal registers, RFIs, daily reports and contract modifications inside the private environment. Draft RFI responses and submittal transmittals for your team to review.
Clear separation of workloads
Commercial jobs can use hosted enterprise AI. Restricted jobs use the private environment. We help you set rules for which data goes where, and build the tools so people don't have to guess.
From restriction to working tool
Step 1: Understand your requirements
We review the data-handling requirements your contracts and compliance team have identified. Your team owns the interpretation of those requirements and any compliance framework that applies.
Step 2: Choose models and hosting
We test open-weight models against your real document types and pick what fits the work and your hardware or cloud setup.
Step 3: Build inside the boundary
We deploy the model and tools in your environment with least-privilege access to project data. Access is logged.
Step 4: Operate and update
We monitor performance, update models as better open-weight options come out and add tools as your teams find new uses.
Works with systems inside your environment
- Procore
- Trimble Viewpoint Vista
- SharePoint and on-premise file shares
- Bluebeam
- Microsoft 365
Open-weight model R&D for restricted project data
We run self-hosted and open-weight model R&D for clients whose data can't go to hosted models, including government and federal work. We'll tell you what open-weight models do well on construction documents today, and where they still fall short of hosted models.
- Self-hosted and open-weight LLM R&D for restricted data
- Least-privilege access and client-controlled infrastructure
- Reference: the Vista MCP server we built for a regional contractor, whose scoped, least-privilege connection pattern carries over to models running inside your environment
Common questions
Are you FedRAMP authorized or CMMC certified?
No. We don't hold FedRAMP authorization or CMMC certification. Your organization owns its compliance program and decides what environment meets your contract requirements. We build self-hosted AI that runs inside the environment you've approved.
Are open-weight models as good as hosted ones?
For some tasks, close enough to be useful. For others, not yet. We test against your actual documents during discovery and give you a straight answer before you commit to a build.
Can we use the same tools on commercial and government jobs?
Often, yes. We can build one set of tools that points to a hosted enterprise AI plan for commercial work and to your private models for restricted work, with clear rules for which data goes where.