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The Independent Enforcement Layer for Human and AI Execution.

Scale with Trust.

Move work forward across people, AI agents, and enterprise systems—with independent verification and control.

Technology in Development. Supported by Two Published U.S. Patent Applications (not granted patents).

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How work moves forward with HubCop
    • People & partners
    • AI agents
    • Enterprise systems

  2. HubCop independent verification

    Evidence checked across systems. Progression controlled.

  3. Verified work moves forward

    Most work, at speed.

    Exceptions get attention

    Only the gap.

Conceptual design, in development. Not a live integration.

From work to verified progress

How it works

  1. 1. Work moves

    People and AI agents do the work.

  2. 2. Activity captured

    Evidence gathered from connected systems.

  3. 3. Independent verification

    No actor certifies its own work.

  4. 4. Progress or intervene

    Verified steps advance; gaps get targeted attention.

  5. 5. Scale with trust

    Grow volume without growing oversight.

Deeper detail: what the proposed design adds
  • Predefined, configurable milestones. You choose which business steps require evidence.
  • Continuous scoring. Evidence would be rescored as records change or expire.
  • Monitoring and rerouting. Stalled or conflicting items would route to the right person.
  • Cross-system handoffs. Work would pass between people and AI agents with the record in place.

Planned capabilities, in development. Not deployed functionality.

Three ideas, in plain terms

Proposed design. Conceptual diagrams, not a working integration.

1. Activity is captured for you
  1. Connected email, calendar and systems
  2. Activity logged automatically
  3. Authorized record updates, e.g. CRM
2. Evidence decides the next step
  1. Independent evidence
  2. Proceed: evidence qualifies
  3. Hold: evidence missing
  4. Escalate: conflict or timeout
3. Humans and AI hand off safely
  1. Person or AI agent finishes a step
  2. Same evidence check for both
  3. Next person or AI agent takes over
See the Difference: 30 examples
Conceptual Operating Model

Proposed model, not an integrated or operational HubCop system. All three conditions are necessary.

  1. Condition 1

    Independent qualifying evidence

    Authorized access to evidence from sources independent of the performing actor, available for independent qualification.

  2. Condition 2

    Defined milestone policies

    Explicit rules define which evidence qualifies completion and when progression must wait or be reassessed.

  3. Condition 3

    Enforceable workflow control point

    An actual control point in the connected workflow can enforce the decision before the next step executes.

Independent qualification could govern progression at that control point

Advance
Evidence qualifies under the milestone policies; permit the next step.
Hold
Required evidence is insufficient; the controlled step waits.
Reassess
Evidence conflicts or time runs out; review before further progression.

Without all three conditions, independent enforcement cannot be asserted. Evidence access alone, policies alone or a completion claim alone is not enforcement.

Same workflow, two ways to progress

Proposed, illustrative workflow. Example data.

Today

  1. AI agent reports “Completed”.
  2. The workflow may advance on that self-report, or on configured rules and manual checks.
  3. Unsupported handoffs can pass downstream; people re-verify later.

With HubCop · proposed

  • AI agent reports “Completed”. Recorded as a claim; it cannot qualify itself.

  • Independent cross-system signals Records from systems other than the agent are checked against the defined milestone.

  • PASS Evidence qualifies; the next step is permitted.

  • HOLD Evidence insufficient; the step waits at the configured control point.

  • ESCALATE Signals conflict or time runs out; a person decides, with the reason.

Only the configured next step is held, where HubCop is integrated; it does not block other systems.

What is at stake

  • Fewer unsupported handoffs reaching downstream teams.
  • Less manual verification of work already evidenced elsewhere.
  • Confidence to let autonomous AI agents act at scale.

Potential benefits for a pilot to validate. Nothing has been measured yet.

Proposed architecture

Human or AI acts

Completion is a claim, not self-certification.

Other systems provide signals

Independent records of what happened.

HubCop Evidence Gate

Checks the evidence this milestone requires (its Evidence Recipe) against defined rules.

Checks origin · identity · context · timing

Qualifies evidence, then determines permission to progress.

PASS → PROGRESS
Permit the next step.
HOLD → WAIT
Required evidence is missing.
ESCALATE → REVIEW
Conflict or timeout needs judgment.

Proposed integration-mediated control: where integrated, HubCop would govern permission to progress and the connected system executes the action. It does not unconditionally block third-party systems.

The consequence, by design: if the required independent evidence does not qualify the milestone, the configured next step is held; conflicts or timeouts escalate to a person. No actor certifies its own work. This describes the proposed design, not deployed functionality.

Compare with your existing stack

Supported by Two Published U.S. Patent Applications

US20260179008A1US20260179101A1

Published June 25, 2026. Published applications, not granted patents; no exclusivity or claim scope is implied.

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Gene Doubleday, Founder & CEO, HubCop, Inc.

Explore the HubCop Prototype