Lighthouse vs Tarlo

Lighthouse combines decentralized file storage with a long-term memory service for AI agents. Lighthouse Memory saves project context, preferences, and decisions for retrieval in later sessions, with remember, recall, and forget operations. Its batched engine supports local hybrid retrieval using embeddings alongside keyword or tag matching. Memories are documented as verifiable, content-addressed blobs, and the hosted backend exposes tools through the Model Context Protocol for Claude Code, Claude Desktop, and other compatible agents. For files, Lighthouse uses IPFS and lists Filecoin and Walrus as storage networks; its web app supports storing, retrieving, and sharing files. Developers can use an SDK and CLI, while documented memory storage options include Lighthouse Walrus, Lighthouse IPFS/Filecoin, AWS S3, R2, MinIO, and a local folder. Plans include a free tier with 5 GB and 10,000 AI memories, Lite at $12 a month for 500 GB and 25,000 memories, and Premium at $49 a month for 2.5 TB and 100,000 memories. Encryption and other features are add-ons. Lighthouse cautions that forgetting a memory may not erase its stored blob, and content identifiers do not establish whether content is true.

Tarlo has no write-up on Specifiction yet; its figures are above.