How Lem AI works
Lem AI indexes your engineering tools, answers onboarding questions with sources, writes implementation.md when you branch from a ticket, and enforces compliance with SOPs and decision logs.
1. Onboarding & memory
Knowledge stays when engineers leave
Knowledge is in Slack, Jira, GitHub, meetings, and docs—not in one engineer's head. Lem AI indexes it. New hires ask about a decision, ticket, or code path and get answers with sources from every tool.
- — Search across Slack, Jira, GitHub, Confluence, Meet
- — Ask about past decisions with full context
- — Context remains after someone leaves
2. Implementation Agent
implementation.md on branch checkout
Run git checkout -b with a branch name that matches a Jira or ClickUp ticket. Lem AI pulls the ticket, Slack threads, meeting notes, and Confluence or Drive docs, then writes implementation.md for Cursor, Claude, Antigravity, or any LLM.
- — Branch name must match ticket ID
- — Pulls Slack, Jira, Meet, Confluence, Drive
- — One markdown file for your coding agent
3. Continuous compliance
SOPs and decision logs on every change
Lem AI flags changes that break process: branch not tied to Jira or ClickUp, new npm package without justification, PR description missing or off-topic, code not matching the ticket. The developer or manager answers; Lem AI stores a decision log for audits.
- — Unlinked branches and new dependencies
- — PR and code checked against the ticket
- — Decision log for compliance reviews
Data flow
Lem AI connects to Slack, Jira, ClickUp, GitHub, Confluence, Google Meet, and document stores. Events and content are indexed once. Onboarding queries read that index. Branch checkout triggers Implementation Agent. Git and package changes trigger compliance checks.