Plan with context
Organize specifications, milestones, features, and tasks with repository research to inform decisions.
AST repository mapping →
Plan your roadmap, explore your project with an AI consultant, and coordinate agent-assisted tasks—from the first breakdown to validation and evidence review.
Dependency-aware parallel execution with bounded filesystem writes.
Verify signature rotation
hmac_sha256 verify spec
Bounded ingest buffer
redis stream backpressure
Review the requested filesystem changes before the task continues.
Move from ambiguous intentions to concrete, validated software delivery with explicit checkpoints at every milestone.
Organize specifications, milestones, features, and tasks with repository research to inform decisions.
AST repository mapping →
Break larger goals into dependency-aware work and plan tasks in parallel waves before execution.
Dependency wave engine →
Use bounded tools and approval flows for sensitive operations, and follow task progress as work runs.
Granular sandboxing →
Validate task outcomes and retain evidence so teams can assess results and understand gaps.
Verifiable task evidence →
A structured progression that bridges conversational intent with verifiable code changes and evidence.
Describe the outcome and provide project or repository context. Let the assistant analyze your architecture before writing code.
Explore the project, refine specifications, and organize work into milestones and tasks with explicit dependencies.
Coordinate task runs, follow progress, and inspect validation findings and evidence before accepting the work.
Code Flare combines a visual project workspace with AI-assisted research and an orchestration service for planning, execution, and validation.
Connect supported hosted providers or local model services to fit your security requirements.
Use the web interface or desktop application to manage projects and follow engineering activity.
Local deployment (desktop)
In-process database & local workspace
Server deployment (self-hosted)
Configured service infrastructure
Inference routing
Choose local models or hosted APIs
Data control: Configure where project storage runs and which inference provider handles requests.
Code Flare stores project data in the database and workspace used by its service. The desktop app runs that service locally; a server deployment stores data on your configured infrastructure. You control whether AI inference uses local models or hosted APIs.
Experience AI-assisted orchestration built for technical teams who value precision and verifiable engineering evidence.
New accounts are currently invitation-only.
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