Lark
The All-in-One Collaboration Super-App Eliminating the 'Toggle Tax' with Native AI Integration.
Unified AI Knowledge Layer for Teams: Search, Chat, and Automate across your entire SaaS stack.
Neve is a sophisticated AI-driven knowledge management platform designed to act as a centralized 'intelligence layer' for modern enterprises. Built on a Retrieval-Augmented Generation (RAG) architecture, Neve connects natively to disparate data silos—including Slack, Google Drive, Notion, GitHub, and Jira—to provide a single, conversational interface for institutional knowledge. Unlike traditional keyword-based search, Neve utilizes high-dimensional vector embeddings and semantic indexing to understand context, intent, and cross-application relationships. This allows technical teams to query complex documentation, legal teams to synthesize contracts, and sales teams to retrieve historical deal data instantly. Positioned for the 2026 market, Neve emphasizes privacy-first AI with 'Zero-Trust Indexing,' ensuring that sensitive corporate data is processed with granular permissioning that mirrors existing OAuth structures. Its roadmap focuses on 'Actionable Intelligence,' where the AI not only retrieves information but also triggers workflows via webhooks, bridging the gap between a search engine and an autonomous agent.
Data is encrypted at rest and in transit; vector embeddings are calculated without Neve personnel ever seeing the raw text.
The All-in-One Collaboration Super-App Eliminating the 'Toggle Tax' with Native AI Integration.
The semantic knowledge fabric for high-velocity enterprise intelligence.
Cognitive Enterprise Search and RAG-Powered Knowledge Discovery for the Intelligent Workspace.
Transform complex database schemas into actionable natural language insights with autonomous SQL synthesis.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Combines BM25 keyword matching with Dense Vector Retrieval (HNSW) for maximum accuracy on technical jargon.
The AI can combine data from three different apps (e.g., a Slack message, a Jira ticket, and a Figma link) to answer a single query.
Automatically categorizes and tags files upon ingestion based on content analysis.
Dynamically updates the context window as new data arrives in connected apps.
Every AI response includes direct deep-links to the source document and specific paragraph.
Allows admins to configure specific system prompts for different user groups (e.g., Support vs. Engineering).
New hires spend weeks asking redundant questions about company policy and tech stacks.
Registry Updated:2/7/2026
Support agents can't find specific edge-case solutions buried in historical tickets.
Sifting through thousands of contracts for specific clauses.