
Eightify
Transform long YouTube videos into actionable insights in seconds with AI-powered summaries.

The AI-native workspace for modern team intelligence and automated workflows.

Bloc is a high-performance AI workspace designed to centralize fragmented organizational knowledge and convert it into actionable intelligence. Built on a Retrieval-Augmented Generation (RAG) architecture, Bloc allows enterprises to index disparate data sources—including Notion, Google Drive, Slack, and local PDFs—into a unified semantic vector store. By 2026, Bloc has positioned itself as the 'connective tissue' for AI-driven organizations, moving beyond static documentation into dynamic agentic workflows. Its technical core leverages advanced metadata filtering and hybrid search algorithms to ensure that the AI agents built on top of the platform provide halluciation-free, contextually accurate responses. The platform’s unique value proposition lies in its ability to not only store information but to proactively deploy 'Bloc Agents' that can automate repetitive tasks, such as drafting technical specifications or responding to RFPs based on historical data. Architecturally, it supports enterprise-grade requirements with robust permissioning layers and the flexibility to swap underlying LLMs, ensuring that data sovereignty and performance are optimized for specific business verticals.
Bloc is a high-performance AI workspace designed to centralize fragmented organizational knowledge and convert it into actionable intelligence.
Explore all tools that specialize in extract key insights. This domain focus ensures Bloc delivers optimized results for this specific requirement.
Explore all tools that specialize in ai agent deployment. This domain focus ensures Bloc delivers optimized results for this specific requirement.
Uses hierarchical vector embeddings to search across disparate apps like Slack and Notion simultaneously.
Allows users to define multi-step logic where an AI agent can read data, reason, and perform an action.
Real-time monitoring of connected source changes with delta-updates to the vector index.
Combines BM25 keyword matching with dense vector embeddings for optimal retrieval.
Every AI response includes deep-links to the exact block or page of the source document.
Ability to rebrand the AI interface for client-facing knowledge portals.
Metadata-level permissions ensuring users only see search results they have access to in the original source.
Create a workspace account and define your organizational domain.
Connect primary data silos via OAuth (Notion, Slack, Google Workspace).
Initialize the indexing engine to crawl and vectorize connected repositories.
Configure 'Knowledge Blocs' to categorize information by department or project.
Define Access Control Lists (ACLs) to ensure data privacy between teams.
Select the preferred LLM model (GPT-4o, Claude 3.5, or Llama 3) for the inference layer.
Deploy a test AI agent to verify RAG accuracy using the 'Playground' environment.
Embed the Bloc widget into internal tools or portals via Javascript snippet.
Set up automated 'Sync Tasks' to keep the vector database updated in real-time.
Invite team members and distribute API keys for custom integration development.
All Set
Ready to go
Verified feedback from other users.
"Users praise the ease of setup and the quality of the RAG implementation, though some note that large PDF indexing can take several minutes."
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