Hazyl

Human judgment. Agent execution.

Command and control for the AI workforce.

Hazyl is the command layer that makes enterprise AI ops possible: specialized AI agents operating inside explicit mission processes, where every step, branch, and human gate is versioned like doctrine and executed exactly as written.

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The problem

Every hand-off, pause, and gap costs hours.

At every echelon, information arrives as disparate inputs: sensors, reports, emails, partner feeds. Turning them into a decision means briefs, hand-carried packets, and decision-makers with competing priorities.

Agents can read, fuse, and draft at machine speed. What has been missing is the layer that tells them which process to follow, where to stop, and who decides.

Disparate inputs

  • SENSORnew emitter, 52.1N 26.0E
  • REPORTarmored column, M-6 highway
  • EMAIL"Re: Re: readiness roll-up (v7 FINAL)"
  • PARTNER40+ UAS contacts, bearing 270

Today's hand-offs

  1. Email
  2. Spreadsheet
  3. Slide
  4. Brief

Synthetic scenario. No operational data.

Overview

See a mission process run under command.

Four minutes: an indications-and-warning process authored in the builder, commanded from chat, challenged by a reviewing agent, and approved by a human.

Synthetic scenario. No operational data.

How it works

Author it once. Command it from chat. Keep the record.

  1. Author the process

    Operators draw the mission process in a visual builder. Each step states its goal, inputs, and outputs. Every step, branch, and gate is versioned and executed exactly as written.

  2. Assign agents and gates

    Per step, operators set which agent leads, which agents review, and where a human must approve. Dozens of agent roles ship today; mission-specific roles are authored the same way.

  3. Command from chat

    Operators start and steer a run from the chat client they already use. When an agent is blocked, it asks a targeted question in the thread.

    Microsoft Teams shown. Slack also supported.

  4. Agents challenge each other

    For critical decisions, a drafting agent and a reviewing agent challenge each other before a human sees the result. They can run on different models.

  5. A human decides

    The recommendation arrives in the thread as an approval request. The run waits at the gate until a human answers.

  6. Everything is on the record

    Every discussion is documented. Every decision is recorded with its approver and time, alongside the runtime events of the run.

Product screens show a synthetic exercise scenario. No operational data.

What is different

The command and control layer above the AI workforce.

Agent frameworks give you agents. Hazyl gives you command of them: the process they follow, the gates they stop at, and the record they leave.

Command and control layerHazyl · above the AI workforce
Plane 1OrchestrationProcesses, steps, gates, versions
Plane 2AgentThe AI workforce: roles, teams, providers
Plane 3IntegrationChat, repositories, issues, cloud
Plane 4GovernanceApprovals, records, evidence

Why alternatives fall short

  • Do-it-yourself agent frameworks

    Every unit rebuilds its processes, its audit trail, and its compliance from scratch.

  • Closed vendor stacks

    One model, one vendor, no doctrine portability.

  • Hazyl

    One command layer: explicit processes, human gates, and evidence that carry over as models and tools change.

Built to absorb change

Models and endpoints change. Doctrine and evidence carry over.

  • Model-agnostic on purpose

    Runs today on Anthropic, OpenAI, Google Gemini, Mistral, and xAI. Bring your own keys and choose a model tier for each step.

  • Provider failover

    If a provider falters on a transient error, Hazyl fails over to another and the run continues.

  • Durable execution

    If infrastructure drops, durable execution resumes where it stopped. Runs survive restarts without losing state.

  • Supervised self-healing

    When a process fails, a recovery process researches the failure, then retries or recommends human action.

  • Cybersecurity as pipelines

    Dynamic scanning gates promotion today. Static, dependency, secret, and container scans are in preview.

  • Swap endpoints, keep the process

    Repoint a step to a new model, tool, or chat endpoint when the operator gives the order. The process and the record above it do not change.

Runs today on
  • Anthropic
  • OpenAI
  • Google Gemini
  • Mistral
  • xAI
Works with
  • Microsoft Teams
  • Slack
  • GitHub
  • GitLab
  • Jira
What Hazyl needs
An available AI model, a cloud tenancy (AWS today), and your existing chat and tooling accounts.

Roadmap

  1. Ask SageGovernment AI platform integration
  2. Government cloudHazyl deployed in a government cloud region
  3. On-premisesSingle-tenant install inside a command's own stack

Evidence

What every run leaves behind.

Cybersecurity runs as pipelines too, and every run produces evidence that supports continuous ATO. The record is a product of the work, not a report written after it.

  1. Scan reportsdynamic scans today; static, dependency, secret, and container scans in preview
  2. Approvalswith approver and time, from the chat thread
  3. Decision recordsevery gate, every answer, every YES
  4. Runtime eventstool calls, retries, failover, resume
  5. Token accountingper run, per step, per provider

Evidence artifacts that support an assessment and authorization package. Authorization remains a government decision.

Proof

Hazyl's first customer is Hazyl.

For six months, Hazyl has built itself with the same agentic framework it offers potential clients: nearly one governed release per working day, each with a human gate before production.

  • 116governed releases, from v0.6 on 25 Mar 2026 to v0.39.3 on 10 Sep 2026
  • 26minmedian from requirement approval to merged pull request
  • 1,007merged pull requests
  • 493automated test files

Source: Hazyl release history, repository, and run history (internal data), counted 30 Sep 2026. The median covers completed Single Issue to Feature runs from 3 to 29 Jul 2026, n = 10. It measures internal software delivery.

Software delivery was the first mission under command.

Requirements, code, tests, security scans, and promotion to production all run as Hazyl processes with human gates. The same builder, agents, and record carry any other mission process.

Working prototype, demonstrated: first defense-scenario prototypes were shown to a federal contracting audience in July 2026 on representative data. Not an operational deployment.

See how Hazyl builds software

Company

A veteran-owned team of senior practitioners.

Hazyl is a Service-Disabled Veteran-Owned Small Business: a small, entirely U.S.-based team of senior technology, business, and compliance practitioners with experience across the DoW and commercial sectors.

Hazyl's CEO is retired from the U.S. Marine Corps Reserve, with over 25 years of business and technology leadership experience, an M.S. in Technology Leadership (Brown), an M.S. in Spatial Information Science and Engineering (UMaine), and a B.S. in Computer Science (Siena).

Contact

Request a briefing.

Tell us which mission process you want under command. We will walk you through Hazyl on a synthetic scenario and answer your questions directly.