What is Clears AI?
Clears AI is a platform that uses AI agents to automate the software development lifecycle. Connect your backlog and instantly identify tasks ready for autonomous execution. The AI analyzes requirements, asks clarifying questions, breaks work into subtasks, writes the code, and opens pull requests. All tasks stay in two-way sync with your integrated ticketing system.
How It Works
Clears AI follows an AI-SDLC (AI Software Development Lifecycle) approach. Instead of manually writing specs, assigning tasks, and waiting for implementation, you:
- Write a story describing what you want built
- Answer a few clarifying questions the AI asks about your requirements
- Review the pull requests the AI creates in your GitHub repositories
The platform handles everything in between: analyzing your codebase, generating a detailed specification, decomposing the work into subtasks, implementing each subtask with code changes, and creating PRs for your review.
Key Capabilities
Autonomous Story Execution
Create a story on the Board, and the AI agent automatically:
- Explores your codebase to understand the existing architecture
- Generates clarifying questions to refine requirements
- Produces a detailed specification with definition of done
- Breaks the story into implementable subtasks
- Writes code for each subtask and commits to feature branches
- Opens pull requests ready for your review
Intelligent Memory
Clears AI learns from every execution. The memory system captures patterns, conventions, and decisions from your repositories, making each subsequent story smarter and more aligned with your codebase.
Real-Time Visibility
The Board gives you a kanban-style view of all your stories, with live status updates as the AI works. Watch branches get created, commits land, and PRs open, all in real time.
Flexible Integration
Connect Clears AI to your existing tools:
- GitHub for code repositories and pull requests
- Jira for syncing stories from your existing backlog (optional)
- Slack for notifications and Q&A interactions (optional)
AI-SDLC vs Traditional SDLC
| Aspect | Traditional SDLC | AI-SDLC with Clears AI |
|---|---|---|
| Story analysis | Manual spec writing | AI-generated specification with Q&A |
| Task decomposition | Manual breakdown by tech lead | Automated subtask generation |
| Implementation | Developer writes code | AI agent implements with code changes |
| Code review | PR created manually | PR auto-created, human reviews |
| Knowledge capture | Tribal knowledge | Automated memory and learnings |
Next Steps
Ready to get started? Continue to Account Setup to create your account and configure the onboarding wizard.