The context engine for Knowledge.
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.
Onboarding search, implementation.md on branches, and compliance logs—in security, healthcare, ecommerce, and more.
Engineering teams use Lem AI to search past context, generate implementation.md from tickets, and record compliance decision logs.
Search is the base. On top of it: onboard new engineers with real history, generate implementation.md from tickets, and record compliance decisions on every change.
Onboarding & memory
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.
Implementation Agent
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.
Continuous compliance
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.
Context is scattered across Slack, Jira, GitHub, and meetings—not in one person's head. New hires ask Lem AI about any decision, code, or task and get cited answers from every source.
Hey, why did we use a custom debounce here instead of lodash?
Junior dev context-switches to another task while corporate knowledge stays trapped in chat history.
Why did we use a custom debounce here instead of lodash?
Sarah and Mike decided this in the Oct 12 Architecture Meeting to handle high-frequency IoT pings. Lem AI turns that thread into searchable corporate knowledge.
Match a branch to a Jira or ClickUp ticket and Lem AI compiles meeting notes, Slack, ticket copy, and Confluence or Drive docs into one file—ready for Cursor, Claude, Antigravity, or any coding agent.
Install globally so your workspace can sync with the institutional memory graph—search, implementation, and compliance from the terminal.
npm install -g get-lem-aiConnect Slack, Jira, GitHub, and Confluence so Lem AI can answer onboarding questions and stitch context across every source.
get-lem-ai setup --token=••••••••Checkout a branch that matches your Jira or ClickUp ticket—Lem AI gathers meetings, Slack, tickets, and docs into implementation.md for your LLM.
git checkout -b feature/Lem-412Branch Lem-412
Workflow triggered
Lem-412
Ticket Status: Done
Auth Logic
Use HMAC or RSA?
Security Sync
Stick with HMAC for now.
Verification
Updating policy v2.4.
Meeting Summary
Consolidated context
Output
1. Define TTL (12h)
2. HMAC-SHA256 logic
3. Update Redis store
4. Sync PR #142
Branch "fix-login" does not match pattern feature/*.
Commit "fix" (3 chars) is below the 10-character SOC 2 requirement.
PR #142 missing mandatory context field for change management audit.
Lem AI agent has verified that branch feature/Lem-321 follows the SOC 2 SOP Protocol with 100% recall.
Unlinked branches, new node modules, weak PR descriptions, or code that drifts from the ticket trigger an SOP—your team documents why, and Lem AI stores an audit-ready trail for compliance.
Generate standard operating procedures (SOPs) from your team's actual development patterns and organizational history.
Intercepts non-compliant actions like undocumented packages and requests mandatory justification before risky work ships.
Ensure every pull request and commit message supports SOC 2 traceability, ISO 27001 change management, and enterprise search and information security.
We will help in get you compliance in SOC2 type 1 and 2.
Lem AI is enterprise search software that reads Slack, Jira, Asana, Monday.com, ClickUp, Trello, GitHub, Confluence, and Google Meet—one internal knowledge base for onboarding search, implementation.md, and compliance checks.
Search for Slack channels and index threads for enterprise search, implementation.md, and SOP checks.
Meeting notes linked to tickets, branches, and compliance logs in your knowledge management search solution.
Docs pulled into onboarding answers and implementation.md as part of your corporate knowledge layer.
Ticket IDs tie to branch names, context, and compliance rules across your enterprise search tools.
Sync Asana projects into workspace search—employee knowledge management tools with cited task context.
Monday boards indexed for AI-powered knowledge management and ticket-linked implementation workflows.
ClickUp teams and tasks feed enterprise search best practices—branch names match ticket IDs automatically.
Trello boards and cards indexed at workspace scope for scalable enterprise search across large teams.
Branches, PRs, and commits monitored for implementation and SOPs in your internal knowledge base software.
Same integrations feed onboarding search, implementation.md, and compliance checks—one enterprise search index, three products.
Your task stack
Connect Jira, Asana, Monday.com, ClickUp, or Trello—Lem AI indexes tasks with corporate knowledge retrieval and ticket-linked branch workflows.
One-click OAuth. No credentials stored.
Auto-link Jira boards, repos, and Slack channels.
Enforce enterprise search best practices in real time.
Full corporate knowledge of every architectural choice.
Examples of what continuous compliance catches: new packages without rationale, branches without ticket IDs, and decisions that never made it into a log.
When package.json changes, Lem AI intercepts the PR and asks for the architectural "why". No more mystery libraries in enterprise search software.
[Info] PR #247 detected: +1 new dependency
[Lem AI] lem: "Why was lodash added? Document rationale."
[ Ok] Dev response linked → Decision captured ✓
Lem AI matches Jira task IDs to branch names, then attaches the relevant Slack thread to the code for future enterprise search use cases.
[Info] Branch: feat/Auth-221-sso-flow
[Info] Linked: Jira Auth-221 → Slack #dev-auth (3 threads)
[ Ok] Context graph updated ✓
Lem AI joins Google Meet calls, identifies technical decisions in real time, and updates your internal knowledge base software automatically.
[Info] Meeting: weekly architecture review
[Lem AI] Decision detected: "Migrate auth to OIDC"
[ Ok] Wiki updated → ADR-0058 created ✓
OAuth for GitHub, Slack, Jira, Asana, Monday.com, ClickUp, Trello, and Confluence. Lem AI indexes existing history so onboarding search and implementation.md have data on day one.
Lem AI is reading 12,847 items across repositories, boards, and documentation for AI-powered enterprise search.
Preserve corporate knowledge when senior engineers leave. New hires can ask: “Why did we choose this DB in 2023?” and get the exact Slack conversation and meeting transcript instantly.
Every decision is captured and indexed automatically.
Not weeks. New devs get answers from employee knowledge management tools.
150+ teams securing corporate knowledge with Lem AI.
Why did we choose Postgres over DynamoDB in 2023?
Based on the architecture review meeting on March 15, 2023 and Slack thread #backend-infra, the team chose Postgres for its JSONB support and existing team expertise.
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.
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.
DetailsRun 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.
DetailsLem 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.
DetailsModel enterprise search use cases for fragmented context, tribal knowledge wait times, onboarding delays, and audit preparation across your engineering organization.
Slack wait times
Estimated 2.0 hrs spent waiting for tribal knowledge from senior devs.
Context switching
Lost productivity due to fragmentation across 4+ platforms (Jira, Slack, Meet).
Legacy exploration
Time wasted decrypting code logic that is not documented in a knowledge graph.
$210,000
Lem AI reclaims ~70% of engineering time lost to context hunting with AI-powered knowledge management.
Lem AI pays for itself if it saves your team 15 mins a week.
Lem AI is built from the ground up for enterprise search and information security. We safeguard your institutional memory with rigorous controls for regulated engineering teams.
Enterprise-grade controls for enterprise search and information security. We will help in get you compliance in SOC2 type 1 and 2.
All data encrypted with AES-256 at rest and TLS 1.3 in transit.
Your code and conversations are never used to train global models.
Available on-prem and private cloud for AI enterprise search clients.
All infrastructure is hosted on globally distributed, security-hardened AWS regions with multi-layer redundancy.
Onboarding, Implementation Agent, compliance, and enterprise search—for engineering teams.
For teams comparing enterprise search software and AI-powered knowledge management, Lem AI scales from onboarding search to implementation.md and compliance when you are ready.
Enterprise search software for high-performance engineering teams, with full access to compliance tools.
Custom enterprise search software for larger organizations that need unlimited scale and private deployment.
Join the future of context-aware engineering. Connect your repository, activate AI-powered knowledge base search, and ask your first question in under 2 minutes.