Engineering agent
Works from approved repositories and documentation to produce code, tests, diagnostics, or migration evidence under review.
Custom AI agents · human-supervised AI employees
Give a repeatable workflow to an agent—without giving away accountability.
MiReVerse designs custom AI employees around a defined job, approved information, controlled integrations, measurable evaluations, and explicit human approval. The result is an operational role—not a generic chatbot or an autonomy promise.
Start with one job and one accountable owner
The best first agent handles a frequent, evidence-based workflow whose inputs, expected output, escalation conditions, and reviewer are already understood.
Review and QA agent
Checks pull requests, test evidence, cross-layer consistency, required controls, and known failure patterns.
Documentation agent
Maintains source-grounded technical guides, onboarding material, decision records, and release documentation.
Knowledge and support agent
Answers from an approved knowledge base, drafts responses, classifies cases, and escalates outside-confidence requests.
Operations coordinator
Collects evidence across permitted systems, prepares status updates, routes work, and requests human approval before action.
Workflow-specific AI employee
A custom role built around one repeatable business process, its tools, approval points, quality measures, and owner.
What gets designed
Role, objective, users, and accountable owner
Approved source material and data boundaries
Tools, integrations, credentials, and allowed actions
Human approval and prohibited-action rules
Evaluations, stop conditions, logs, and escalation
Deployment, onboarding, maintenance, and version ownership
What is not promised
Unsupervised production or mainnet authority
Access to every company system by default
Perfect answers outside approved sources
Replacement of legal, financial, security, or management accountability
A one-time prompt that never needs evaluation or maintenance
Hidden actions without evidence and ownership
Assess, configure, evaluate, then expand
Workflow assessment
Map current work, systems, volume, quality failures, permissions, risk, and the human who owns the outcome.
Controlled pilot
Configure a representative workflow and compare agent evidence with the team's existing quality standard in shadow mode.
Approved operation
Expand only after evaluations pass, reviewers agree, access is scoped, and monitoring and escalation are documented.
Which repeated workflow consumes capable people today?
Bring one concrete process, the systems it touches, typical inputs, expected output, and the person who reviews it.