An AI agent that plans and executes software tasks with explicit user approval.

The platform enables teams to decompose releases into actionable items with estimates and assignments. It maintains a memory graph that accumulates context from ongoing work, allowing the agent to reason over historical decisions and team activity. GitHub synchronization keeps code changes aligned with tracked tasks through two-way updates on pull requests and issue status. Automations can be defined as code or visual workflows to handle routine events without manual intervention. Users retain full oversight as high-impact actions require review, and all steps are recorded in an audit trail for traceability and accountability.
Prompt the agent to decompose releases into sprints that generate subtasks, estimates, and assignees for review and approval before execution.
Combine issues, docs, files, and GitHub data into one graph that the agent reasons over while accumulating team context in the memory graph.
Use two-way sync so GitHub issues and PRs update work items automatically, with YAML-defined automations handling status changes and backlog triage.
Pricing model: Freemium. Plan details are indicative — check the site for current prices.
Our take: Lithora is a solid productivity choice. It's valued for user retains full control via approval gates and audit trails and context-aware agent operates directly on the work graph. The main trade-off is public beta release. A good pick if you want capable AI without a high upfront cost.
A runtime that plans work from prompts, presents detailed action plans for approval, and executes only within user permissions while logging every step.
Lithora is a solid productivity choice. It's valued for user retains full control via approval gates and audit trails and context-aware agent operates directly on the work graph. The main trade-off is public beta release. A good pick if you want capable AI without a high upfront cost.
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