Lossless Memory is long-term memory for a personal AI that refuses to summarize: it keeps every line, puts a timestamp on everything, and builds every index on that time axis, which the project calls the Temporal Backbone. You can query by time first and words second, results come back chronological and unsummarized, and a small index tells the model which topic the conversation is in so context survives compaction.
Be the first to rate Lossless Memory. Your feedback helps other users decide.
Store raw conversation logs in full instead of lossy summaries
Ask for yesterday evening about the budget and get chronological results
Keep identity and topic across context-window compaction and new sessions
Similar tools in the same category — compare side-by-side
Bise is an open-source terminal app for multi-agent coding. You talk to one agent, the team lead, an...
Orthogonal connects your agent to web search, scraping and enrichment APIs through one account, offe...
Pirate Face is a censorship-resistant, checksum-verified mirror for open AI models. It turns models,...
Guides and comparisons about code tools
Code graphs, persistent decision memory, semantic layers and artifact plumbing: recent tools giving coding agents the context they keep losing.
Nine Show HN launches beneath the model: filesystems, snapshots, gateways and deploy tools that decide what an agent sees and what survives.
Nine launches that check agent work: per-call access policy, MCP server vetting, runtime verification, readable diffs and a hard stop at 95%.
Nine Show HN launches sitting under the agent: a model gateway, vectorless retrieval, on-device inference, an MCP browser layer and connectors for real systems.
Eight Show HN projects for trusting long agent runs: work context capture, distilled memory, folder fences, dollar budgets, plan review and tool governance.
