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Workspaces/Use cases/Cross-functional search
Cross-functional search

Bridge engineering silos with cross-tool search.

Support, product, and engineering should not block each other. Lem AI is an AI assistant for work that traces issues from Slack and Confluence back to GitHub commits—with permissions and citations.

Active search simulator

Click a preset query tag to see Lem AI trace results across GitHub, Slack, and Jira.

Connected sources
Slack archive#ops-alerts
GitHub repositoryget-lem/api-kore
Jira projectDEVOPS Board
Confluence docsSecurity Wiki
SYNC STATE:Active
TOTAL NODES:3,870
Workspace search

PR #394

Alex (Merged)

Fix Safari flex wrapping

Adjusted flexbox layout wrap properties to fix blank screens on Safari mobile devices.

#ops-alerts

David

Wrap bug resolved

David: Webkit css classes updated in main branch. Safari blank page issue is verified fixed.

Unified workspace search features

Trace active issues, synchronize conversation logs, and query documentation safely.

Enterprise AI search mappings

Utilize enterprise AI search protocols to link Slack, Jira, and GitHub. Trace client issues back to their origin commits dynamically.

Search for Slack channels

Connect Slack channels to repositories and wiki pages under secure workspace OAuth parameters using custom Slack applications.

Enterprise search vs web search

Query private Slack and Jira—not the public web. Permission-segregated search boundaries keep customer data inside your workspace.

Reviewing enterprise search use cases and comparing legacy enterprise search platforms with modern enterprise search systems.

Access segments mapping

Granular authorization maps trace user privileges to protect credentials and keys.

Restricted

Support access scope

Tier 1 support queries trace ticket statuses and release timelines. Sensitive code details and private decryption configurations are hidden.

Access boundaries
Jira tickets & CommentsAllowed
Slack discussion archivesAllowed
Production repositoriesBlocked
Private security keysBlocked
Standard

Product scope

Product managers trace ticket-commit connections to track feature deployments and release velocity without asking engineers.

Access boundaries
Ticket-commit connectionsAllowed
Release timelines & PRsAllowed
Feature flag mappingsAllowed
Production data replicasBlocked

Platform specifications

Retrieval & 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.

Ingestion latency< 5.0 seconds
Vector dimensions1536 (OpenAI v3)
EncryptionAES-256 / TLS 1.3
ComplianceSOC 2 & ISO 27001
Authorizations: ActiveSegments synced
Contextual Discovery

Bridging engineering tool silos

Access engineering context instantly without waiting for developer responses.

Unified ingestion mesh

Connect Slack, Jira, Confluence, and GitHub. Sync workspace data with secure Slack applications and indexed Confluence pages.

Semantic connections

Trace repository commits back to Slack channels. Build corporate knowledge maps that link issues to design discussions.

semantic-graph-v2.0
Nodes: 4,120Synced: 100%

Workspace AI Copilot

Query decisions instantly. Run enterprise AI search mappings that keep teams aligned without manual documentation.

Ask Lem AI...
Trace Safari CSS wrapping bug
Show DB latency alert decisions

Restoration velocity

Identify root causes and resolve issues in seconds instead of hours. Minimize search latency across all repositories.

98%Velocity
Search latency< 80ms
Incident MTTR-95% Saved

Team context ledger

Ensure organizational memory survives developer transitions. Trace ADR logs and system specifications dynamically.

LM
Lottie MarshDev lead
Lottie Marsh merged PR #394 resolving Safari flex bugs.
SOP Matcher:Compliant

Connect your team memory today

Start retaining engineering rationale, onboarding developers faster, and optimizing context search velocity.

$npm install -g get-lem-ai && get-lem-ai setup