Government & enterprise
Bring AI into a controlled environment without starting a compliance fight
We modernize workflows inside real constraints: CUI, NIST 800-171, CMMC, FedRAMP boundaries, and a security team that has heard promises before. Everything is documented for the people who have to sign off.
Built for
- Program managers modernizing a process without reopening an ATO
- Government contractors handling CUI under NIST 800-171 or CMMC
- Capture and proposal teams drowning in compliance matrices
- Enterprise IT that has to say yes or no to an AI request this quarter
- Security leads who need the data-flow question answered in writing
Government work is contract-vehicle dependent. We work as a sub or through prime relationships, and pricing follows the vehicle: T&M, FFP, or a task order under an existing IDIQ. As a rough shape, assessments and boundary analysis run $4,500–$9,000 fixed fee, modernization efforts run $6k–$40k per workflow, and compliance-aware AI builds run $15k–$75k. Enterprise engagements outside a vehicle run on the same commercial ranges. Tell us the vehicle and we’ll tell you the honest fit.
The problem
The tech is the easy part. The approval is the project.
A program manager can see exactly what should be automated. The blocker isn’t technical. It’s that any new system means a data flow diagram, a security review, an argument about where CUI ends up, and a vendor who can’t answer whether the model trains on inputs. Six months later the answer is no, and the process is still manual.
Meanwhile the commercial AI pitch doesn’t survive first contact with your environment. “Just upload your documents” is a non-starter when the documents are controlled. What you need is someone who leads with the boundary diagram instead of the demo, and who knows the difference between FedRAMP Moderate and a marketing page that says “government-ready.”
What it buys you
The outcomes we hold ourselves to.
- The security conversation starts on day one
- Data flow diagrams, boundary definitions, and control mappings are deliverables from the first sprint, not paperwork bolted on at the end. Your ISSO gets the artifact they need while there’s still time to change the design.
- CUI stays where it’s supposed to
- We architect to the boundary you already have. If a workflow would move controlled data across a line it shouldn’t cross, we redesign it or scope it out and say so in writing. That answer arrives in week two, not month five.
- Compliance matrices in an afternoon
- Section L and M parsed into a requirements matrix with cross-references and owners. The work that eats a senior person’s week during every proposal cycle gets reviewed instead of built from scratch.
- Past performance you can actually find
- A decade of proposals, CPARS, and technical volumes indexed by vehicle, agency, and NAICS, with citations. Capture stops rewriting narratives that already exist and already won.
- It fits your pipeline, not around it
- Builds land in your GitLab or Azure DevOps, run through your scanning gates, and deploy through your existing process. Nothing gets a special exemption, because the exemption is what kills the project at the review board.
- Documentation your auditor will accept
- SSP-ready language, control mappings, logging design, and access model, all written in the register the people who read them expect. If it can’t be handed to an assessor, it isn’t finished.
Deliverables
What you actually receive.
Written, handed over, and yours to keep, whether or not we work together again.
Security and compliance artifacts
- Data flow diagrams showing every system, every boundary crossing, and what data is in each
- Control mappings against NIST 800-171 and, where relevant, NIST 800-53 and CMMC Level 2 practices
- SSP-ready narrative language for the components we build
- Access model with role definitions and least-privilege justification
- Logging and audit design: what’s recorded, retained how long, reviewable by whom
Workflow modernization
- Process assessment covering current state, handoffs, and cycle time
- Automation of internal review, routing, and approval chains
- Document processing for contract deliverables, mods, and CDRLs
- Data management: consolidating what lives across SharePoint, file shares, and personal drives
- Reporting that assembles from source systems instead of by hand
Compliance-aware AI
- Knowledge bases scoped to the enclave the documents already live in
- Compliance matrix generation from solicitations
- Past performance and resume retrieval with citations to the source volume
- Model deployment options mapped to your posture, including FedRAMP-authorized paths where required
- Human-in-the-loop by design on anything that touches a submission
DevSecOps integration
- Pipelines in your GitLab, Azure DevOps, or GitHub Enterprise, not ours
- SAST, dependency, and container scanning wired into the gates you already run
- Infrastructure as code, reviewed like any other change
- Deployment through your existing approval path, with rollback documented
- Handover to your team with the runbook written before we leave
Process
How the engagement runs.
No surprises, no scope drift you didn’t agree to. Each phase ends with something you can read or use.
- 01
Map the boundary before the workflow
First question is always where controlled data lives and which lines it can’t cross. We produce the data flow diagram before we scope features. If the answer makes a workflow impossible, better to know in week one.
Weeks 1–2 - 02
Get your security people in the room early
ISSO, security lead, whoever writes the SSP: in the design sessions, not the readout. Their objections are cheapest to fix on a whiteboard. This is the step that decides whether the project ships or dies at review.
Weeks 2–3 - 03
Prove it on something small
One narrow workflow, deployed inside the real boundary, through the real pipeline. It answers the questions a slide can’t: where the logs go, what the access model looks like in practice, what breaks.
Weeks 4–8 - 04
Build the artifacts alongside the build
Control mappings and SSP language get written as the system takes shape, by the people who built it. Documentation written six months later by someone who wasn’t there is how findings happen.
Ongoing - 05
Scale and hand over
Extend to the next workflow, train your team, and leave the runbook, the pipeline, and the code in your hands. Your people should be able to run and change it without a call to us.
Months 3–9
Examples
The kind of work this turns into.
- Compliance matrix automation for a capture team
- A tool that ingests the solicitation, parses Section L and M into a requirements matrix with cross-references, and assigns first-pass owners, running inside the existing environment. What consumed a senior proposal manager for two days per bid became a morning of review, with nothing missed because it was hour six with a highlighter.
- Past performance retrieval inside a CUI boundary
- Twelve years of technical volumes and CPARS across two SharePoint sites, indexed with vehicle, agency, and NAICS filters, deployed with no controlled data leaving the enclave. Answers cite the source volume and page. The data flow diagram went to the ISSO in week two.
- Contract deliverable processing
- CDRL submissions checked against the contract’s stated format and due dates automatically, with exceptions routed to the CDRL manager. Full audit log of every check. The manager reviews flags instead of manually verifying every submission against a spreadsheet.
- Workflow modernization inside an existing ATO
- Internal review and approval routing rebuilt with automated handoffs and reminders, deployed through the program’s existing pipeline and scanning gates with no new boundary crossings. Because nothing needed an exemption, the security review was a conversation rather than a fight.
Questions
Before you ask.
Can we use AI with CUI at all?
It depends on the deployment, not on the word “AI.” CUI can be processed in an environment that meets your obligations, meaning the model endpoint, the storage, the logs, and the access model all sit inside the boundary you’re already assessed against. What you can’t do is paste it into a consumer chat tool. The first deliverable is a data flow diagram that answers this precisely for your case, and sometimes that answer is “not this workflow, not yet.”
Do you have a FedRAMP authorization?
Glasir is a consultancy, not a hosted product, so we aren’t the thing that gets authorized. What matters is where your workload runs. We deploy inside your authorized environment and select model endpoints and services with the authorization your posture requires. If a component you want doesn’t have the authorization you need, we say so before it’s in a design, not after.
Will this reopen our ATO?
The whole design goal is that it doesn’t. We build inside the existing boundary, through the existing pipeline, with no new external connections wherever possible. Where a change genuinely does trigger a significant change review, we flag it in week one with the reasoning, so it’s your decision with a number attached rather than a surprise at the review board.
Our security team will say no on principle.
They should — that’s the job, and most AI pitches deserve it. So we invite them to the design sessions on day one and hand them the data flow diagram and control mapping before they ask. Most “no on principle” is really “no on unanswered questions.” When the answers are in writing in week two, the conversation changes. When they’re still right to say no, we don’t argue.
How does this work with our prime, or with us as prime?
Both. We sub to primes on task orders and work directly for enterprises. Pricing and structure follow the vehicle: T&M, FFP, or a task order under an existing IDIQ. Tell us the vehicle and the shape of the work and we’ll tell you whether we fit, including when we don’t.
Will this replace analysts or program staff?
No. Everything that touches a submission or a deliverable is human-in-the-loop by design: the system drafts the compliance matrix, a person owns it. What goes away is the part where a senior person spends two days transcribing requirements out of a PDF, which is not why you hired them.
Other services
AI Consulting
A written plan that says which three things to automate first, what each one costs, and what you get back.
Business Automation
Your systems talk to each other. Quotes, invoices, and follow-ups happen without anyone retyping anything.
Custom AI Solutions
AI built on your own documents, your own history, and your own rules, so it gives real answers instead of confident guesses.
Let’s find the work worth automating.
A 30-minute discovery call. We map where your time actually goes and tell you what’s worth automating, and what isn’t. No deck, no pressure. You leave with a written summary either way.