UDX Boundary
AI coding for teams that
can't break the boundary.
A private repository deployed inside your org. A governed AI gateway. Every line of code visible. Nothing leaves the boundary.
Schedule a Demo# 1. Clone the private repo we deployed in your org
$ git clone git@github.com:your-org/udx-boundary.git
$ cd udx-boundary && node cli.js
udx-boundary v2.0.0 | model: anthropic.claude-sonnet-4 | region: us-gov-west-1
directory: ~/infra-terraform | files: 47 (loading up to 50) | depth: 4
Commands: read <file> | cd <dir> | setup | clear | exit
# 2. Ask a question — it reads your entire codebase for context
udx> refactor the VPC and ECS configs into reusable modules
Reading 12 files (.tf, .tfvars)...
Context: 47 files, 283k chars loaded. Analyzing structure...
Proposed changes:
+ modules/vpc/main.tf (new — 84 lines)
+ modules/vpc/variables.tf (new — 23 lines)
+ modules/ecs/main.tf (new — 67 lines)
~ main.tf (edited — 47 lines replaced with module calls)
- vpc.tf (content moved to modules/vpc/)
Apply all changes? [y/N] █
# 3. You approve each change — nothing happens without your say-so
✓ Created modules/vpc/main.tf (run git add to track)
✓ Created modules/vpc/variables.tf (run git add to track)
✓ Created modules/ecs/main.tf (run git add to track)
✓ Edited main.tf
ℹ vpc.tf — remove manually after verifying module works
# 4. Follow up with anything — it remembers the full conversation
udx> scan the project for hardcoded secrets or security issues
Scanning 47 files for credentials, keys, and policy violations...
⚠ deploy.sh:14 — AWS_SECRET_ACCESS_KEY hardcoded in script
⚠ config/database.yml:8 — plaintext DB password
△ terraform.tfvars:3 — AWS account ID exposed (low risk)
Recommendation: Move secrets to AWS Secrets Manager. Want me to
generate the refactored files?
udx> █
Your stack.
Your boundary.
Your code.
We deploy a private repository into your org and provision a governed AI gateway. Your developers clone it, run it, and build on it.
Private Repo
Deployed in your org. Every line of code visible.
AI Gateway
Governed Bedrock proxy with policy, audit, & metering.
Track which developer, project, and team uses what models at what cost. Chargeback-ready.
Restrict models, set token limits per team, enforce coding standards in every prompt.
Immutable log of all AI interactions. CloudWatch & CloudTrail integration out of the box.
Auto-route to the right model based on complexity. Nova for simple, Claude for complex.
What your developers see
A fast terminal assistant that understands their codebase.
- ✓ Clone, run, ask questions in natural language
- ✓ Context-aware — reads .tf, .yaml, .py, .go, 40+ file types
- ✓ Proposes edits, you approve or reject each one
- ✓ Full source code — read it, fork it, extend it
What your security team sees
A complete AI audit trail with centralized control.
- ✓ Every Bedrock call logged with user, project, tokens, cost
- ✓ Policy enforcement — model restrictions, token budgets
- ✓ Zero data exfiltration — only talks to your Bedrock endpoint
- ✓ Git-safe — refuses edits outside repo, requires approval
The mandate is here.
DoD is actively seeking CLI-based AI coding tools for tens of thousands of developers. The infrastructure to deliver it is ready. Every department must adopt AI.
The infrastructure is ready
- $50B committed starting 2026 for AI infrastructure across the federal government (source)
- Amazon Bedrock: FedRAMP High authorized
- Claude & Nova in GovCloud: IL-4/IL-5
- Over 11,000 agencies already on AWS — Bedrock is a config change, not a migration
The Pentagon is actively buying this
- CDAO actively soliciting CLI-based agentic coding tools for DoD-wide deployment
- Targets tens of thousands of DoD developers
- Estimated contract: $5M–$25M
- Army Open Solicitation via ACC-Aberdeen Proving Ground
Reference: SAM.gov W9128Z-25-S-A002 (CDAO_26-01)
Every department must adopt AI
- Pentagon AI strategy (Jan 2026) mandates priority AI projects in every department
- Must support FedRAMP High / IL5 environments
- Must work in air-gapped / disconnected networks
- Human oversight required for all autonomous coding
How it compares.
| Alternative | Setup time | UDX Boundary |
|---|---|---|
| Claude Code + Bedrock | Hours | Minutes. Private repo, no phone-home |
| Continue IDE + CDK Stack | Days/weeks | Minutes. No infrastructure, any terminal |
| Build Your Own | Weeks/months | Already built. Clone and extend |
| Sanitize & Copy Between Machines | Every time | Zero manual steps. Everything in boundary |
| Run a Local Model | Days + hardware | Cloud speed. Claude & Nova, FedRAMP High |
| No AI at All | — | Full AI assistant in the terminal |
Boundary: Minutes. Private repo, no phone-home.
Boundary: Minutes. No infrastructure, any terminal.
Boundary: Already built. Clone and extend.
Boundary: Zero manual steps. Everything in boundary.
Boundary: Cloud speed. Claude & Nova, FedRAMP High.
Boundary: Full AI assistant in the terminal.
How we engage.
Three phases. No surprise costs. You own everything we build.
Deploy
- Provision AI gateway in your GovCloud
- Deploy private repo to your GitHub/GitLab
- Configure authentication with your IdP
- Connect audit pipeline to your SIEM
Validate
- Pilot with 5–10 developers
- Tune model routing and policies
- ATO documentation package reviewed
- Measure developer productivity delta
Scale
- Roll out to full engineering org
- CI/CD pipeline integration
- Usage metering and cost attribution
- Quarterly model and policy updates
Fixed-price deployment. Per-seat monthly for ongoing support. No lock-in — you own the repo and infrastructure.
What gets built.
Terraform Refactoring
Without: Manually read 12 .tf files, refactor by hand, hope nothing breaks.
With Boundary: "Refactor to modules" → 3 files proposed, review and approve.
Code Review & Debugging
Without: Print statements, manual stack trace reading.
With Boundary: "Why is this failing?" → Root cause identified, fix proposed.
Config Generation
Without: Copy a YAML, edit 30 fields, miss a naming convention.
With Boundary: "K8s deployment matching our conventions" → exact patterns.
Documentation
Without: Read every source file, write docs from memory.
With Boundary: "README for this service" → contextual docs from actual code.
Security Review
Without: Manual grep for secrets, one file at a time.
With Boundary: "Any hardcoded credentials?" → full scan across project.
Developer Onboarding
Without: Outdated wiki, bother teammates, days of ramp-up.
With Boundary: "What does this project do?" → instant answers from code.
Built for the most
restrictive environments.
What it does NOT do
Compliance Alignment
Bedrock in GovCloud is FedRAMP High authorized
DoD provisional authorization in GovCloud
No CUI processing outside the accredited boundary
Access control, audit trail, least privilege enforced
Complete AI usage logging and attribution through your existing AWS observability stack.
Gateway authentication integrates with your existing IdP. Enforce MFA, role-based access, and session policies through standard federation protocols.
Full offline operation supported. The CLI, gateway, and model inference all run within your network. No internet connectivity required after initial provisioning.
Run Boundary non-interactively in your pipeline. One-shot prompts, auto-apply mode (-y), and exit codes designed for automated workflows.
One repo. One gateway.
Zero data outside the boundary.
Everything above lives inside your GovCloud VPC. The CLI talks to the gateway. The gateway talks to Bedrock. Nothing else.
Your info stays with us. No spam.
We'll be in touch within one business day.
Usability Dynamics — Service-Disabled Veteran-Owned Small Business