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Bulkgrid vs Vectorize

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Bulkgrid compared with Vectorize
DetailBulkgrid logo BulkgridVectorize logo Vectorize
What it doesThe Knowledge Layer for AI Agents Agent memory that learns from experience
StageNot given Startup
FoundedNot given 2024
Based inSE US
Pricing modelNot given Freemium
PricingNot given Self-hosted: Free, MIT licensed. Hindsight Cloud: Pay-as-you-go with free credits to start. Retain (store memories) $10.00 per million tokens, Recall (retrieve memories) $0.75 per million tokens, Reflect (synthesize patterns) $0.05 per call, Iris Extract (structured extraction) $7.50 per million tok
Key features
  • Search for web pages, images, and news
  • Crawl pages into Markdown, HTML, links, and screenshots
  • Map discovery using website sitemaps
  • Extract structured JSON from pages
  • Index with scheduled refreshes and retrieval
  • TypeScript and Python SDKs
  • Model Context Protocol (MCP) integration
  • REST API for all capabilities
  • CLI for terminal and script access
  • Private GitHub repository indexing
  • Per-user persistent memory with preferences, history and decisions kept separate
  • Cross-session persistence allows context to survive weeks between interactions
  • Fast parallel retrieval in under 100ms through four strategies running simultaneously
  • Works with any LLM without losing learned context when swapping models
  • Learns from mistakes and corrects behavior on repeated problems
  • Automatic pattern detection synthesizes individual facts into consolidated knowledge
  • Conflict detection preserves both old and new states with timestamps when facts change
  • Integrates with 20+ coding agents including Claude Code, Cursor, and Copilot
What makes it different
  • Maintains indexed knowledge with automatic scheduled refreshes
  • Provides source references for verifiable answers
  • Supports both public and private knowledge sources
  • Handles infrastructure for data pipelines
  • 94.6% retrieval accuracy on LongMemEval-S, beating next-best system at 74.0%
  • MIT licensed open source with no usage limits, telemetry or restrictions
  • Reflection layer automatically builds judgment and mental models over time without manual tagging
  • Entity resolution handles hundreds of entities with 99.5% query reduction
Free planNot given Not given
Open sourceNot given Not given
PlatformsNot given Not given
Public APINot given Not given
Community votes00
DR (Domain Rating by Ahrefs)4 no change since last check68 +1 (up) since last check
Trust Flow (Majestic)818
Citation Flow (Majestic)2647
Referring domains (Majestic)301378

4 details filled in for both companies.

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