Context and code. Connected.
One secure AI workspace where engineering teams retrieve corporate knowledge, trace historical context, and onboard new developers faster.
Trusted by modern engineering teams syncing
Interactive onboarding path
Click each phase to see the developer experience in action.
Sync corporate knowledge
Connect your team's existing workflow tooling via simple OAuth scopes. Lem AI automatically indexes corporate knowledge across Slack channels, wiki databases, and git histories to build an initial mapping of organizational decisions.
No code changes or database migrations required. Secure, isolated vector nodes are created in minutes.Deploy the workplace bot
Instead of wasting time repeating historically resolved bugs, new developers query our intelligent workplace bot directly from their dev channels or terminal consoles. They retrieve answers instantly from company context.
Speeds up context retrieval by 10x, keeping senior devs focused on delivering production code.Submit first pull request
New hires make their first production pull request with complete confidence. The built-in guard checking ensures their branches match active Jira tickets and verify system design specifications.
No more broken webkit wrapping, replica database errors, or security leakages reaching production.Onboarding pillars for scaling teams
How our internal knowledge base software captures corporate knowledge and increases developer velocity.
Retain corporate knowledge
Every Slack thread, Jira ticket, PR discussion, and meeting transcript is indexed into a permanent, searchable knowledge graph. We index corporate knowledge automatically as discussions happen.
Self-serve developer cockpit
Developers run queries from Slack or their terminal to instantly resolve roadblocks. Senior engineers focus on writing code instead of repeating historical context.
Deploy workplace bots
Ask our Slack workplace bot questions directly in team channels. Get responses cited with precise code rationales and references to avoid channel noise.
Compared to manual wikis
While legacy databases rot quickly, Lem AI uses AI algorithms to maintain active code mappings, operating as a superior knowledge management tools alternative for fast teams.
AI-powered knowledge base
Build an active, secure, and permission-aware AI-powered knowledge base that updates itself in real-time as changes are merged into production.
Internal knowledge base software
Leverage modern internal knowledge base software that respects repository roles and prevents security configuration leaks across cross-functional scopes.
Onboarding ingestion pipelines
Unified semantic mapping links disconnected development assets into a single developer view.
// Ingesting and syncing workspace context...
$ get-lem-ai setup --token=••••••••
✔ GitHub repository linked (get-lem/api-kore)
✔ Slack channel listener active (#engineering)
Syncs Slack decisions to GitHub commits, auto-updating outdated wikis.
Tenant-isolated vectors
Your company vector indices are hosted in secure, isolated database layers. Fully protected under local encryption parameters.
Platform specifications
Lem AI core engine v2.4Retrieval & Ingestion
Lem AI functions as a fast enterprise search engine that indexes historical context across Confluence, Jira, and Slack. It acts as a secure internal knowledge base software for engineering teams.
Security & context verification
Enforce strict information security best practices. Our workplace bot delivers tenant-isolated vector isolation and real-time credentials monitoring across all query boundaries.
Connect your team memory today
Start retaining engineering rationale, onboarding developers faster, and optimizing context search velocity.