Turn product requirements into executable work
Capture application scope, architecture, stack, database, authentication and feature requirements before generating editable workstreams and tasks.
InfraLenses
Reduce developer cost across application planning, delivery and production fixes
InfraLenses does not replace developers. It reduces time spent on architecture handoffs, task breakdown, runtime evidence collection and repetitive fix preparation, while your team keeps review, merge and deployment decisions.
Key outcomes
- Less planning overhead
- Task-based code generation
- Faster runtime diagnosis
- Validated draft PRs
What InfraLenses gives you
Connect repositories when the team is ready
Save and approve the complete task plan before GitHub, GitLab or Bitbucket setup, then map each workstream to its repository to start development.
Move from runtime exception to draft PR
Correlate application logs and HTTP evidence, analyze the relevant source code, validate the targeted patch and open a draft pull request without automatic merge.
Workflow
- Describe the application, project shape, architecture and technology stack.
- Review, edit, approve and optionally group the generated development tasks.
- Connect repositories and start task-based application development.
- Collect runtime logs and HTTP evidence after deployment.
- Analyze a production exception and create a validated draft PR for human review.
Search intent coverage
- AI application development platform
- build an application from requirements
- automated runtime code fix
- turn production errors into GitHub pull requests
- reduce software developer costs
FAQ
Can InfraLenses create an application plan before a Git repository is connected?
Yes. Teams can complete and approve the architecture, workstreams and task plan first, then connect a repository when they are ready to start development.
Does InfraLenses automatically merge generated code fixes?
No. The code fix workflow creates a branch and draft pull request with evidence and validation results. A person remains responsible for review and merge.
What evidence is used for a runtime code fix?
InfraLenses can correlate application logs, stdout, incoming HTTP requests, outgoing responses, exception fingerprints and the mapped repository before analyzing a fix.