Run rule-based and planner-driven workflows across Azure Boards, Repos, Pipelines, Test Plans, Wiki, and release processes. Trigger agents manually, from Azure DevOps events, or on a schedule. Set approval boundaries, verify outputs, and inspect every run.
Governed agent execution, native to Azure DevOps
Every run begins with a defined trigger and scope, loads the permitted Azure DevOps context, acts within its allowed tools, verifies the result, and records what happened.
A request, ADO event, schedule, or API call starts the run.
It loads the permitted work items, code, runs, results, and policies.
It applies versioned rules or plans a sequence within scope.
It analyzes, drafts, updates data, or invokes an approved operation.
Actions with side effects pause for the right reviewer.
Post-action checks confirm the expected result exists.
The run record captures inputs, actions, approvals, and outcome.
Chat may be one way to start work. But the product is the controlled run — scoped context, approved tools, permitted actions, approval rules, verification, and history.
Start with the outcome your team needs. Each workflow defines its trigger, Azure DevOps context, execution method, actions, approval boundary, verification, and run record.
Backlog readiness, acceptance criteria, epic decomposition, duplicate detection, requirements quality, dependencies, and change impact.
PR review, work-item linkage, code-owner routing, defect investigation, code change impact, security findings, and follow-up work.
Pipeline diagnosis, run comparison, config audit, remediation, deployment readiness, release planning, notes, rollback, and approval checks.
Test generation, coverage gaps, test-run execution, failed-test triage, flaky-test diagnosis, defect creation, regression, and sign-off reports.
Incident investigation, change correlation, runbook maintenance, status updates, approved remediation, and recurring operational checks.
Traceability audits, baseline checks, branch and approval controls, standards mapping, validation readiness, and evidence-package assembly.
Discover the product by the work it executes — not by an agent count. Browse workflows & industry packs →
Automate routine work without giving every agent unrestricted access — or treating every task as an open-ended prompt.
See what an agent can access, what it can change, and where approval is required.
The trust story is built on observable execution facts — the data flow, permission boundary, approval controls, verification, and run history for every run.
Actions with defined side effects pause for the appropriate reviewer before execution.
A completed run isn't treated as successful until the expected state, link, or result is confirmed present.
Each run captures the trigger, inputs, actions, approvals, outputs, errors, and verification result.
Existing Azure DevOps permissions, product roles, project scope, and tool permissions are enforced per run.
Industry packs configure terminology, classification logic, traceability relationships, review gates, standards mappings, and evidence structures. Agents prepare and validate the work; qualified people retain the final decision.
15 industry packs — from general software delivery to the most heavily regulated programmes.
No. Chat may be one way to start work, but the product story is the controlled run: a defined trigger, scoped context, approved tools, permitted actions, approval rules, verification, and execution history.
Yes — within scope. Deterministic execution agents can update structured fields; planner-style agents prepare or analyze work and request approval before write actions. The exact action matrix is published per your configuration.
No. Agents remove repetitive analysis, maintenance, and coordination work. Qualified people retain responsibility for architecture, safety, compliance, certification, and go/no-go decisions.
By execution capacity, not per user. Credits are consumed by model tokens, tool calls, orchestration steps, and execution time — so you can invite everyone who needs visibility. See plans & credits →
Bring a failed pipeline, active pull request, backlog-quality problem, test failure, release gate, or traceability gap. The demo shows the trigger, context, execution path, approval point, verification result, and run record.