Agentic Release Assurance Control Tower

Inspiration

Every enterprise technology team knows the pressure of a production release. Requirements keep changing, ServiceNow change requests move quickly, testers are trying to understand what changed, developers are waiting for feedback, and leaders need a confident Go/No-Go decision.

We observed this type of challenge while working with enterprise customers who are modernizing testing, improving release confidence, and adopting agentic automation at scale. At qBotica, our innovation focus, UiPath partnership, and in-house testing and automation expertise helped us explore how agentic workflows can solve this problem in a practical enterprise context. Learn more about qBotica’s Agentic AI Workflows: qBotica Agentic AI Workflows.

These release challenges often create avoidable defects, manual follow-ups, testing gaps, late-night release calls, and unclear release confidence. Manual testing and traditional automation help, but they do not fully solve the end-to-end release assurance problem.

That inspired our team — Logesh, Prashanth, Harikishore, and Akhil — to build Agentic Release Assurance Control Tower: an autonomous, governed, and traceable release assurance solution powered by the UiPath Platform.

Our team brought strong real-world UiPath, testing, automation, and enterprise implementation experience into this project. Logesh is a two-time UiPath Test Cloud MVP with 14+ years of experience guiding enterprise customers through testing and automation journeys. Akhil is also a two-time UiPath MVP with deep UiPath Platform expertise. Prashanth and Harikishore have strong experience supporting enterprise UiPath automation development, deployment, platform implementation, and community contributions. This helped us design the solution not just as a hackathon demo, but as a practical enterprise release assurance pattern.

What it does

Agentic Release Assurance Control Tower helps enterprises move from reactive testing to intelligent release confidence.

In simple terms, it acts as an AI-powered quality gate that helps teams decide whether a release is safe to ship, what needs to be fixed, and when human approval is required.

The solution starts from a ServiceNow change request or GitHub pull request. AI agents analyze the requirement, identify impacted applications, assess release risk, select the right Test Cloud test cases, execute tests, and triage failures.

If the issue is a product defect, the system creates or updates the defect and blocks the release. If it is an environment issue, it routes the issue appropriately. If it is an automation failure, Coding Agents analyze the broken automation, repair the script, create a pull request, route it to testers for review and approval, merge the approved fix, and re-run only the impacted tests.

The final Go/No-Go decision is based on evidence: test results, risk score, failure classification, approvals, logs, screenshots, PR history, and audit trail. Humans are involved only when judgment, approval, or governance is required.

How we built it

We built the solution using the UiPath Platform as the orchestration and governance layer.

Key technologies used:

• UiPath Maestro BPMN for end-to-end process orchestration
• UiPath Test Cloud and Test Manager for test case management and execution
• AI agents for requirement analysis, risk assessment, failure triage, and release readiness
• Test Robots for test execution
• API workflows for system-level automation
• Integration Service connectors for ServiceNow, GitHub, and enterprise integrations
• UiPath Studio for automation development
• Orchestrator for deployment, monitoring, and governance
• UiPath Apps for human-in-the-loop approvals
• Coding Agents using UiPath CLI, Claude Code, and UiPath skills for automation repair and pull request creation

The process is designed as a single orchestrated flow: change comes in, agents reason, tests execute, failures are classified, automations self-heal, testers approve, tests re-run, and the release decision is generated with traceability.

Challenges we ran into

The biggest challenge was designing the right enterprise flow. This was not just about running tests or fixing broken automation. We had to think through the full release lifecycle, including requirement changes, risk scoring, test selection, failure classification, automation repair, human approval, re-execution, and Go/No-Go governance.

We also had to make sure the solution was realistic for enterprise adoption. That meant adding clear quality gates, approval points, retry loops, exception handling, auditability, and traceability.

Another challenge was connecting different systems and roles into one story: testers, developers, release managers, ServiceNow changes, GitHub PRs, Test Cloud execution, Coding Agents, and human reviewers.

Accomplishments that we're proud of

We are proud that we built a solution that addresses a real enterprise problem in quality assurance and software delivery.

This project shows how UiPath can bring together testing, automation, AI agents, orchestration, integrations, governance, and human-in-the-loop approvals into one enterprise-ready release assurance pattern.

We are especially proud that the solution demonstrates the UiPath Platform not as a single testing tool, but as an enterprise orchestration layer for agents, tests, approvals, integrations, automation repair, and release governance.

We are also proud of the self-healing automation loop: when automation fails, Coding Agents can repair the script, create a pull request, route it for tester approval, merge the approved fix, and re-run the impacted tests. This can reduce late-night testing effort, manual defect tracking, and repeated automation maintenance.

Most importantly, the solution turns release decisions from guesswork into evidence-based, auditable Go/No-Go decisions.

What we learned

We learned that enterprise-ready agentic testing needs more than AI agents. It needs orchestration, governance, secure integrations, human approval, monitoring, audit trails, and trust.

We also learned how quickly UiPath can accelerate this kind of solution. Maestro gave us the orchestration layer, Test Cloud gave us the testing foundation, Integration Service connected enterprise systems, Apps enabled human approvals, Orchestrator provided governance, and Coding Agents accelerated automation repair and future test development.

The biggest learning was that the future of testing is not just automated testing. It is autonomous release assurance, where agents reason, robots execute, humans govern, and the platform orchestrates everything.

What's next for Agentic Release Assurance Control Tower

Next, we want to pilot this pattern with real enterprise release streams, starting with ServiceNow change validation, GitHub pull requests, and Test Cloud regression suites.

We also want to expand the solution with Delegate for Testers, so testers can monitor release stages, ask questions, review evidence, approve decisions, and manage exceptions through a natural language AI assistant.

In the future, Coding Agents can help accelerate the full SDLC by designing, building, testing, fixing, validating, and improving test automation coverage. Customers can start small with one release stream and scale across applications, teams, and business units.

Our vision is simple: no more late-night release confusion, scattered defect tracking, blind Go/No-Go meetings, or broken automation blocking release confidence.

Agentic Release Assurance Control Tower helps enterprises deliver faster, safer, and more reliable software with the power of UiPath.

Built With

• ai-agents
• and
• api-workflows
• app-test-developer
• app-test-runtimes
• claude-code
• coding-agents
• github
• github-pull-requests
• human-in-the-loop
• integration-service-connectors
• javascript
• llm-reasoning
• oauth-2.0-authentication
• orchestrator
• servicenow
• test-manager
• test-manager-apis
• test-robots
• uipath-apps
• uipath-cli
• uipath-maestro-bpmn
• uipath-skills
• uipath-solutions
• uipath-studio
• uipath-test-cloud