Requirements keep changing. TrustBound maps every rule you answer to, gets it approved in plain English, enforces it on every AI tool and agent, and keeps the receipt.
Manage policy changes in one workspace.
Queue policies and changes.
Turn source text into rules.
Review topics, resolve questions.
Get the right people’s sign-off.
Publish versions by environment.
Enforce policies where agents act.
Four integration methods.
Set each action’s requirements.
Hold actions for human decisions.
Guide agents to correct actions.
Enforce rules without internet.
Spot issues and trace decisions.
See agents and their operators.
Flag sensitive access.
Record actions and outcomes.
Investigate recurring denials.
Trace decisions to policy sources.
AI can read your policy. The harder part is turning it into reviewed, approved rules that consistently guide supported AI actions.
Pending policy reviews can stall adoption or leave AI use with uneven oversight.
Teams lack a reviewed answer.
Decisions wait on the right people.
AI use may move ahead of clear checks.
Constant changes arrive faster than teams can review and update their policies.
Federal, state and city rules.
Industry, regulators and internal teams.
Updates must be interpreted and approved.
Scattered records make decisions hard to trace and turn audits into manual work.
Actions, approvals and sources live apart.
Which rule applied—and who approved it?
Teams piece the record back together.
Bring policies and regulations into one workflow: create clear rules, get the right approvals, check supported AI actions, and trace decisions back to their source.
Bring regulations, guidance and internal policies into one review process.
Work through requirements together and turn them into clear policy rules.
Review the rules in plain English and publish an approved version.
Enforce approved policy before supported AI actions run, on your systems.
Connect actions and outcomes to the rules, approvals and sources behind them.
TrustBound connects requirements in your source documents to rules your team can review and approve, then assembles them into executable policy versions.
Keep each requirement connected.
Bring regulations and policies into review.
Review the rules with your team and counsel.
Assemble approved rules into a policy version.
Regulations + organization policies
Concrete clause → Rule 04
Open term → Open Definition 04
Approved rules assembled into v1.2
Enforce the approved policy
Agents · AI tools · people
Review the same rule in plain English, logic, or a decision flow, with its source alongside. Compliance checks it, calls in counsel if needed, and once approved, that rule is ready to use, no translation step.
For any further copies requested by the data subject, the controller may charge a reasonable fee based on administrative costs.
As the organization, we may charge the proposed fee where copies are further copies, data subject requested them, and reasonable copy fee holds.
Turn legal and policy requirements into concrete, clause-by-clause checks. Give each task to the right person and see what is still to do, in progress or done.
Move policy checks through review.
Give each clause check to the right person.
Review topics and resolve questions.
Share a review link with outside counsel.
See what is to do, in progress or done.
Review a policy with your team and optional counsel. Once approved, it guides Gatekeeper checks across agents, AI tools and people.
Bring the right people into the decision.
Work through the policy with your team.
Send policies to your chosen approvers and track their decisions.
Use the approved policy for Gatekeeper checks.
Gatekeeper intercepts supported agents’ tool calls before execution and checks the deployed policy locally, even offline with a cached version. It returns a verdict and any requirements for connected systems: allow, deny, wait for a person, or revise and retry.
Check supported AI actions locally.
Evaluate supported agents’ tool calls before they run.
Keep checking offline with a cached policy version.
Allow, needs review, revise or deny—with requirements.
Codex. Read file. Arriving
Explore reported AI actions, the policy version checked and the rule behind each verdict. Reporting is opt-in and configurable; the activity below is sample data.
Explore the decisions you choose to report.
See the AI action and its verdict.
Inspect the policy version and relevant rule.
Reporting is opt-in and configurable.
10:00–12:00Selected range
Drag to move the two-hour window. Use left and right arrow keys for 15-minute steps, or the earlier and later buttons for 30-minute steps. Home and End move to the first and last range.
50 decisions in this range
No events in this range.
·Tool call
The destination is prohibited by the checked policy.
TrustBound connects human review to software enforcement. Your teams can inspect a rule, agree on its meaning, and put that same logic into use.
One rule, written for human review.
Two more views of that same rule.
Review and enforce the same rule.
Link each decision to its rule.
Know which version governed it.
Trace the rule to its original source.
Actions checked in your environment.
Policy checks on standard CPUs.
Deterministic checks. No LLM judge.
We're working with a small group of design partners in regulated industries, starting with legal services and insurance. Bring a real policy and the AI workflows you want to govern. Work with us to shape how TrustBound supports them.
Map policy or regulation into rules to review and approve.
Enforce approved policy on your chosen supported AI tools and agents.
Work with the product team to help shape what comes next.
Bring a real policy or regulation for us to work through.
Choose someone responsible for compliance to lead the review.
Share what you learn from putting TrustBound to use.
See how your policy, the people responsible for it and the tools doing the work can stay connected.
