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Save your project before problems reach production
Context-aware AI code review that understands your entire codebase and business logic.
- Detect inconsistencies between code and business logic
- Continuously assess code quality and risk associated
- Automatically generate and validate relevant QA test cases
Measured Outcomes We Deliver
15 – 30%
improvement in delivery predictability
20 – 35%
earlier risk detection across code, models, and workflows
15 – 25%
reduction in rework caused by late-stage quality issues
30 – 45%
better visibility across projects, teams, and stakeholders
Everything you need to manage the full development lifecycle of an AI project
The Project at a Glance
A centralized snapshot of your project’s health, goals, and progress — combining operational insights with AI-driven evaluation to keep teams aligned and focused.
- Key project details, timeline, members, and overall progress in one view.
- Sprint-by-sprint AI evaluation to track performance and improvement.
- Ticket distribution across workflow stages for instant clarity.
- AI-flagged tasks that may fall outside the project scope.
Trusted by teams building real impact
Chosen by brands who care about quality
The Umaku Process
How we help you build better software, step by step.
1
Project Setup & Context Definition
Define project charter, goals, tech stack, and standards. Connect GitHub and key resources.
2
Team Onboarding & Access Control
Invite team members, assign roles, and configure permissions
3
Sprint Execution & AI-Guided Delivery
Plan sprints, assign tickets, submit code, and receive AI-powered validation.
4
Monitoring, Reporting & Continuous Improvement
Track bugs, analyze AI scores, detect risks, and generate automated sprint review reports
