Product
Explore HELM
The first Mindburn system: a fail-closed execution boundary for AI agent tool calls.
AI CAN ACT NOW. EXECUTION NEEDS CONTROL.
We build execution boundaries for autonomous systems.
Mindburn Labs builds HELM, a fail-closed execution firewall for AI agent tool calls, and the research around governed autonomy.
First system: HELM checks authority before an agent tool call can touch code, data, money, or infrastructure.
Models propose. HELM decides. Evidence proves.
Execution boundary before side effects
- 01AI proposes
Intent, tool, target, and scope.
- 02HELM checks authority
Policy, risk, approval, and connector rules.
- 03Allow / Deny / Escalate
Side effects are cleared, stopped, or held.
- 04Receipt recorded
Decision, reason, and evidence reference.
Start here
Mindburn Labs is the company. HELM is the product path.
The company site should route visitors without exposing product SKU navigation. Product evaluators self-select inside HELM.
Research
Read research
Working papers and thesis material on execution authority, proof, and governed autonomy.
Company
Meet the team
Who is building Mindburn Labs and the public work attached to HELM and research.
Inbound
Contact Mindburn
For HELM evaluations, research conversations, investor or accelerator context, and serious collaboration.
Problem
AI has moved from answers to actions.
When AI sends emails, modifies code, touches data, deploys infrastructure, or triggers workflows, the question is no longer only whether the answer was good. The question is whether the action was allowed, and whether we can prove it.
Old risk
AI could say the wrong thing.
A bad answer could mislead a person, but the action still depended on a human operator.New risk
AI can do the wrong thing.
When agents send messages, touch data, trigger refunds, or change code, the boundary moves from text to execution.Missing layer
A deterministic boundary between reasoning and execution.
Autonomy needs policy, verdicts, and receipts before side effects leave the system.First system
Our first system is HELM.
HELM sits between AI agents and the tools they want to use. Every tool call passes through a deterministic policy engine with receipts, or it is blocked.
Policy checksFail-closed executionHuman approval gatesSigned receiptsReplayable evidenceTool-call control
Plain English
Air traffic control for autonomous systems.
AI agents are fast and capable, but consequential action needs clearance. HELM decides which actions are cleared, which require review, and which are denied.
The model can propose. HELM decides whether execution is allowed.
Differentiation
This is not another AI app.
Most AI toolsHELM
Help agents think or chat.Governs what agents can do.
Log what happened after the fact.Blocks unsafe actions before execution.
Depend on prompts and wrappers.Uses deterministic policy, receipts, and replayable proof.
Demo
Watch an AI agent try to do the wrong thing.
Run the Boundary / Refund Trap: scripted agent proposals, HELM verdicts, and real receipt tamper verification against static signed fixtures.
AgentRefund $4,900
HELMEscalate
ReasonExceeds approval threshold.
Receiptdemo.refund-trap.04
AgentExport customer list
HELMDeny
ReasonData scope violation.
Receiptdemo.refund-trap.05
Why now
The next bottleneck is not intelligence. It is execution authority.
Models are becoming stronger and cheaper. But companies cannot give autonomous systems unrestricted access to code, data, money, infrastructure, or customer operations.
Company knowledge is not authority. Agent interfaces are not control. Logs are not proof.
Where this goes
From AI agents to autonomous operations.
Today
Govern AI agents and tool calls.
HELM checks consequential actions before they execute.
Next
Coordinate approvals, policies, evidence, and workflows.
The commercial layer adds organizational workflow around the same kernel.
Long horizon
Compile organizational intent into governed autonomous execution.
Research explores how intent becomes policy-bound action without moving authority into the model.
Boundary
Speculation stays labeled.
Target-state ideas belong in thesis pages, not first-contact product claims.
Research and thesis
Research-backed infrastructure for governed autonomy.
The Execution Boundary
Why action authority belongs outside the model.
Why Logs Are Not Proof
Why mutable traces are weaker than signed receipts.
Autonomous Operations
How workflows change when agents can touch tools.
Long-Horizon Governance
Research on governed intent, kept separate from current product claims.
Build Log
Built in public where possible. Proven by artifacts.
2026-04-25
Execution receipt thesis published
The execution receipt working paper is published as a public research artifact.
- Why it matters
- It defines the public language for receipts before the site asks visitors to inspect a demo receipt.
- Verification
- Read the paper and its references to the receipt format and verifier protocol notes.
2026-04-15
HELM OSS v0.4.0 public line
HELM OSS version 0.4.0 is the public kernel line referenced by the company site.
- Why it matters
- The website can point to a concrete OSS artifact instead of asking visitors to accept a product claim.
- Verification
- Compare the artifact page with helm-oss/VERSION and the public repository README.
2026-04-02
Policy replay benchmark fixture
A sample policy replay benchmark fixture is published as a public artifact.
- Why it matters
- Replay fixtures help show that proof is an inspectable artifact, not a prose claim.
- Verification
- Open the artifact and confirm it is labeled as an example fixture.
Autonomy needs an execution layer. Mindburn Labs is building it.
For builders, researchers, operators, and investors working on autonomous systems that need boundaries.