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Risk managementfor autonomous enterprise operations.

Hootleash is the risk OS for Human-out-of-the-Loop AI. Set the boundary, quantify every action in dollars, remediate inline, and produce audit-grade evidence for the EU AI Act, NIST AI RMF, and ISO/IEC 42001.

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Built for the world's most regulated industries

Financial servicesHealthcareManufacturingEnergy & utilitiesPublic sector

control.hootleash.com · concept preview

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Agents on leash

—

continuous discovery

24h VaR · per action

$

quantified inline

Auto-remediated

—

throttle · reroute · halt

Boundary

default-deny · cross-border data egress

enforced

Risk quantified

VaR · 99.5% confidence · next 24h

within tolerance

Boundary breach

Agent → unapproved counterparty

graceful degradation

Evidence sealed

EU AI Act · Art. 9–17 · WORM

audit-ready

Cross-walked to every framework your auditors live in

EU AI ActNIST AI RMF 1.0ISO/IEC 42001ISO/IEC 23894SOC 2 Type IIISO/IEC 27001SR 11-7PRA SS1/23EU DORAHIPAA / HITRUSTNERC CIPFedRAMP HighNYDFS 23 NYCRR 500IEC 62443GDPROMB M-24-10

The four pillars

Everything an enterprise needs to put a leash on autonomous systems.

Hootleash isn't a thin policy layer bolted onto your stack. We're building a fully-integrated risk OS that sits between every autonomous agent and the real world.

Boundary Governance - The Leash

Define default-allow and default-deny zones. NIST-aligned controls map and measure risk before it occurs, setting the physical and digital boundaries for every autonomous agent.

  • Policy-as-code with versioning, simulation, and blast-radius previews
  • Geo, data-class, counterparty, currency, model and tool-level boundaries
  • Real-time intent-vs-policy diff at sub-second latency
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Risk Quantification as a Service

Plug into your ERM framework and assign financial and operational consequence to every autonomous action. Convert qualitative fears into quantitative logic an algorithm can process.

  • Monte-Carlo VaR, EVT tail-risk, and reputational-impact scoring
  • Dollarized stop-loss thresholds enforced at the agent layer
  • Live exposure dashboards by business unit, agent, and counterparty
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Autonomous Remediation

Instead of flagging an issue for a human to review, Hootleash routes tasks and self-corrects in real time. When a system hits a boundary it triggers graceful degradation or a safe shutdown.

  • Tiered playbooks: throttle → reroute → degrade → halt
  • Sub-second kill-switch with provenance & rollback
  • Closed-loop learning that hardens the leash after every incident
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Audit-Ready Compliance

One-click evidence generation for regulators - the EU AI Act, NIST AI RMF 1.0, ISO/IEC 42001, SOC 2, SR 11-7, and your internal model risk committee.

  • Tamper-evident event log, sealed in WORM storage
  • Mapped to 24 control frameworks out of the box
  • Auditor portal with read-only, time-boxed access
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Design targets · v1

What "good" looks like - in our spec.

We're pre-launch. These are the operating targets the first release of Hootleash is being engineered to meet - and the bar design partners are evaluating us against.

Time-to-evidence

Minutes

From breach to defensible audit packet. Sealed at the source, not reconstructed.

Remediation

Sub-second

Detect → decide → enact in the same trip the agent was already making.

Policy lifecycle

Git-native

Branch, diff, simulate the leash against historical traffic. Ship like software.

Framework coverage

Crosswalked

EU AI Act, NIST AI RMF, ISO/IEC 42001, SR 11-7 - mapped, not afterthought.

The HOOTL Philosophy

Why we're building Hootleash.

Hootleash isn't a product looking for a market. It's a set of beliefs about how autonomous AI should be governed inside serious enterprises - and the platform we're building to make those beliefs operational.

In private design partnership · early access 2026

Tenet 01

Default-deny is the only honest starting position.

Every leash should start at zero authority. Permissions widen with evidence, not optimism. The most autonomous workflow in your enterprise should also be the most constrained - until it earns more rope.

Tenet 02

Risk has to be a dollar number.

Heat-maps are stories humans tell each other. Algorithms can't read them. Until every autonomous action has a price tag the system itself respects, you don't have a leash - you have a hope.

Tenet 03

Humans are scarce. Stop wasting them on routine.

Putting a person in the path of a high-frequency autonomous loop either blocks throughput or gets rubber-stamped. Use humans for direction, not for click-through approvals on every routine event.

Tenet 04

Remediation must be autonomous.

If your boundary requires a human to be awake, online, and reading Slack, it isn't a boundary - it's a wish. Throttle, reroute, gracefully degrade, halt. The system handles its own correction. Humans read the post-mortem.

Tenet 05

Audit is a query, not a project.

Compliance shouldn't be a quarterly scramble through Slack threads and Confluence pages. Every action an agent takes should produce audit-grade evidence the moment it happens - defensible, signed, queryable.

How Hootleash works

Five disciplined steps from chaos to control.

Engineered for the way enterprise AI actually rolls out - incrementally, across business units, under the eyes of risk, legal, and the board.

  1. 01 · Discover

    Inventory every autonomous agent.

    Hootleash auto-discovers humans, RPA bots, model endpoints, and agentic chains across cloud, on-prem, and SaaS. We classify each by autonomy level, data class, and blast radius.

  2. 02 · Map

    Set the boundary in policy-as-code.

    NIST AI RMF Map activities ship pre-modeled. Write default-allow / default-deny zones in YAML or our visual graph; simulate before you deploy.

  3. 03 · Quantify

    Dollarize every possible action.

    Plug into your ERM model. Hootleash assigns financial, operational, and reputational consequence to each branch of the agent's decision tree.

  4. 04 · Remediate

    Autonomous response, no human paged.

    Tiered playbooks - throttle, reroute, degrade, halt - run inline. The agent stays productive inside the leash; humans get the post-mortem, not the alert.

  5. 05 · Prove

    Audit-ready evidence on demand.

    Sealed WORM event log, cross-walked to EU AI Act, NIST AI RMF 1.0, ISO/IEC 42001, SR 11-7, and your internal MRM. Export a defensible packet in seconds.

Built for regulated, high-stakes enterprises

A tiered leash, calibrated to every industry's tail risk.

Hootleash ships pre-built risk profiles, evidence templates, and remediation playbooks for the industries where 'eventually consistent' is not an option.

Financial services

Autonomous trading, treasury, KYC and tax operations under SR 11-7, DORA and EU AI Act.

Read the playbook

Healthcare & life sciences

Agentic claims, clinical decision support, and pharmacovigilance with HIPAA + EU AI Act guardrails.

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Manufacturing & supply chain

Autonomous OT, MES, and supplier orchestration with IEC 62443 + NIST AI RMF.

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Energy & utilities

Grid-scale autonomous dispatch and trading with NERC CIP and ISO 42001 evidence.

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Public sector & defense

Mission-critical agentic systems with FedRAMP High, IL5, and NIST AI RMF profiles.

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One platform, every framework

Audit-ready by design. Cross-walked, not bolted on.

Hootleash maps every control to every framework your auditors live in. Generate defensible evidence packs in seconds - and let regulators self-serve through a read-only auditor portal.

EU AI Act

Articles 9–17 + GPAI

High-risk obligations from 2 Aug 2026

NIST AI RMF 1.0

Govern · Map · Measure · Manage

Core functions mapped to controls

ISO/IEC 42001

AI management system

First international AIMS standard

SR 11-7 / SS1/23

Model risk management

Tiered model risk inventory

SOC 2 Type II

Trust services criteria

Continuous attestation

DORA

Operational resilience (EU)

Critical third-party register

Ready when you are

Help us put a leash on autonomous AI.

We're building Hootleash in private design partnership with a small number of regulated enterprises. If you run autonomous AI in production, get in touch.

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Pre-launch · design partner program open · early access 2026