Agent Driven Workflows
and Product Development
Modern AI implementation with enterprise-grade governance, security, and compliance built for government workflows.
AI Principles
Our foundational principles ensure responsible AI deployment across all government workflows
Accountability & Governance
Every AI system has clear ownership, documented risks, and complete audit trails. We embed design reviews, pre-launch approvals, and incident response directly into federal delivery pipelines.
Fairness & Equity
Bias testing is standard practice. We generate comprehensive parity reports and disparate impact analyses that integrate seamlessly with Section 508 and Title VI compliance requirements.
Transparency & Explainability
Citizens deserve to understand automated decisions. Every API response includes human-readable rationales, and all model documentation is accessible through self-service dashboards.
Security & Privacy
Government data demands the highest protection standards. All deployments include encryption in transit and at rest, strict data retention policies, and FedRAMP-High controls where required.
Reliability & Safety
Government workflows cannot fail silently. We enforce continuous monitoring, automatic anomaly detection, and kill-switch capabilities that route to human backup systems when needed.
Human Oversight & Control
Humans remain in control of high-impact decisions. Every autonomous action logs its intent, awaits supervisory approval when stakes are high, and provides override capabilities at all levels.
Enterprise-grade AI infrastructure designed for government security and compliance
MCP Servers
Model Context Protocol enables secure, standardized communication between AI agents and government systems. MCP servers provide controlled access to databases, APIs, and tools while maintaining strict audit trails and access controls.
Tracing and Evals
Comprehensive monitoring and evaluation systems track AI decision-making processes in real-time. Every model output is logged, traced, and evaluated against performance benchmarks to ensure consistent quality and compliance.
Langchain
Enterprise-grade framework for building reliable AI applications with government-specific integrations. Provides structured workflows, memory management, and tool chaining while maintaining security and observability requirements.
Every ticket is treated as an executable contract
Executable Contracts
Every ticket is treated as an executable contract. GitHub Copilot Spaces converts a plain-language Issue into a runnable pull-request—title, description and tests included—within minutes.
Automated Bug Fixes
YC-backed Sweep goes a step further: when a bug report arrives it scans the repo, drafts the fix and opens a PR that responds to reviewer comments like a junior engineer.
Monorepo Intelligence
For large monorepos, Sourcegraph Cody embeds the entire code graph so suggestions stay coherent across hundreds of services.
Human Approval
Humans still approve the merge, but 70–80% of the typing disappears and every diff is traceable back to the original acceptance criteria.
These patterns keep prompts compact, failures contained and logs rich enough for audits or post-mortems
Think, then act
We adopt the ReAct prompting pattern so each step contains its own reasoning trace and tool call, cutting hallucinations in half.
Specialists over monoliths
Workflows are composed in Microsoft's AutoGen Studio, where planner, coder and tester agents cooperate through a no-code graph that is fully observable and debuggable.
Validate every output
Each tool invocation passes through Guardrails-for-LangChain schemas that check type, range and policy compliance before the response touches a user or database.
We align each project with the strictest rule that applies, keeping you ahead of both federal guidance and the first wave of state-level AI laws
| Framework / Regulator | What You Must Show | Key Dates |
|---|---|---|
| NIST AI RMF 1.0 NIST | Map-Measure-Manage-Govern tags across the pipeline; documented risk assessments; bias & robustness tests. | Voluntary, widely adopted since Jan 2023. |
| OMB Memo M-25-21 Federal | (Federal projects) Chief AI Officer, public system inventory, quarterly red-team reports. | Issued Apr 3 2025; checkpoints start FY 2026. |
| FTC AI Compliance Guidance FTC | Clear model disclosures, privacy controls, substantiated claims. | Updated Feb 2025; enforceable today under Section 5. |
| Colorado Artificial Intelligence Act Colorado | "Reasonable care" duty; impact assessments; incident reporting for high-risk systems. | Takes effect Feb 1 2026. |
| New York RAISE Act (pending) New York | Safety plans, public test disclosures, 24-hour incident notice for frontier models. | Passed Senate Jun 2025; awaiting signature. |
Ready to Build Agent-Driven Government Solutions?
Let Coa implement responsible AI workflows that meet the highest standards of governance, security, and compliance for your agency.