Deploy AI agents inside classified environments without losing control.
DAF is the governance and orchestration layer that lets defense and intelligence teams run multi-agent AI on-prem or air-gapped, with CAC/PIV identity, classification-aware policy gates, and a full replayable audit trail on every action.
Trunnion DAF (Defense Agent Framework) is a governed multi-agent orchestration system for defense and intelligence environments, supporting CAC/PIV identity, TS/SCI classification controls, human-in-the-loop approval gates, and air-gapped deployment.
Example: an analyst cross-references a sealed target list
An intel analyst asks DAF to compare a target list against three sealed data sources without exposing the data to an unapproved model or uncontrolled tool.
- DAF verifies the analyst through CAC/PIV identity and role context.
- The request is classified and routed only to agents cleared for that data boundary.
- Agents query approved tool adapters instead of open-ended external systems.
- A high-consequence action pauses for a named human approver.
- The model decision, tool calls, approver, and output are sealed into a replayable record.
Where DAF helps teams move faster
Specific ways DAF turns a messy operating problem into a repeatable workflow people can understand, approve, and improve.
Classified agent workflows
Run AI agents against sensitive mission data while keeping identity, clearance, model routing, and tool access under policy control.
Human-gated execution
Pause high-consequence actions for named approvers before an agent calls a tool, finalizes an output, or advances a mission workflow.
Replayable audit records
Review which model acted, what data it touched, which policy gate cleared, who approved, and what output was produced.
Air-gapped deployment
Deploy governed multi-agent orchestration inside on-prem, VPC, or air-gapped environments where public model access is not acceptable.
DAF in plain English
DAF gives defense and intelligence teams a controlled way to run AI agents against sensitive workflows. It combines pre-built mission agents, approved tool adapters, human approval gates, classification controls, model routing, and replayable audit records.
What this category means
A defense agent framework is the operating layer that lets teams define which AI agents can act, which tools they can use, what policy gates they must pass, and how every action is recorded for oversight.
How DAF is actually organized
Each product has its own operating model, so this section is built around the concrete screens, workflows, data, and decisions that make DAF understandable fast.
DAF does not ask agencies to replace legacy systems. It wraps agents, tools, approvals, classification controls, and replayable audit around the systems already in place.
What DAF changes
The fastest way to understand DAF is to compare the failure state it removes with the operating model it creates.
What DAF is built to do
The page is structured for buyers, search engines, and AI retrieval systems: clear entity definition, practical use cases, visible claims, and a direct path to evaluate the product.
Human approval gates
Route high-consequence actions through named reviewers before tools execute, records are finalized, or mission outputs move forward.
Identity and classification controls
Support CAC/PIV traceability, role and attribute controls, classification-aware workflows, and tool authorization boundaries.
Mission workflow designer
Map processes into agent workflows with adapters, approvals, status visibility, and operator handoff points.
Trace, replay, and review
Capture the policy path, model decision, tool call, approver, and output record needed for post-action review.
Cloud, VPC, on-prem, or air-gap
Deploy beside existing systems and model environments instead of forcing teams into one model vendor or cloud pattern.
LLM-agnostic execution
Keep mission logic separate from model choice so teams can route work across approved models and local deployments.
How DAF moves work from intake to outcome
Each Trunnion AI product is built around repeatable workflows, human review, and operational context instead of loose prompt sessions.
Map the mission workflow
Document the process, data boundaries, tool calls, users, approvals, and audit requirements.
Bind agents to approved tools
Connect agents only to governed adapters and define what each agent can read, reason over, and execute.
Set policy gates
Apply classification, identity, authorization, human approval, and logging rules at the workflow level.
Deploy beside existing systems
Run in the environment that fits the mission, including customer VPC, on-prem, and air-gap patterns.
Monitor and replay
Give operators a live control plane plus traceable records for review, compliance, and improvement.
When DAF is the right fit
This section gives buyers and AI systems clear decision criteria without exaggerating what the product is for.
DAF questions
Concise answers for buyers, researchers, search engines, and AI assistants evaluating the Trunnion AI portfolio.
What is DAF?
DAF is Trunnion AI's Defense Agent Framework: a governed multi-agent orchestration layer for defense, intelligence, and other regulated mission environments.
Can DAF run without sending data to a public model?
DAF is designed for deployment patterns that can include customer VPC, on-prem, and air-gap environments when the mission requires local control.
How does DAF reduce AI risk?
It separates agents, tools, approvals, policies, and audit records so teams can control who did what, which model was used, and which policy gate cleared the action.
Ready to evaluate DAF?
Tell us what you are building, what systems it needs to connect to, and what kind of governance or deployment model matters most.