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Structured memory API for LLMs. Store, recall, and assemble prompt-ready context (facts, recent events, and a summary) under a token budget.
Flumes turns messy history into typed, queryable facts and budgeted context your model can use immediately. Explore the graph to see entities and relationships; track what was retrieved and why.
Flumes handles memory for LLMs: store, retrieve, and manage data with a single API. No manual pipelines or token juggling.
Gain insights into memory usage, set access controls, and manage data efficiently with built-in analytics and admin tools.
Flumes AI streamlines memory for your AI agents—one API, structured layers, and built-in analytics. Simple, scalable, and cost-efficient.
/memories, /recall, /summarize, /prune, /observability/events: a small surface that does the work.
Send a turn; get facts, recent events, summary, sources, token counts, and optional trace.
Greedy packing, dedupe, and supersession to fit a max token budget predictably.
See scores (semantic, BM25, graph, recency), dropped items, and cost signals for every request.
Hot, warm, and cold storage tiers ensure fast access and efficient long-term retention for all workloads.
One API connects your AI stack to unified memory—no complex setup or maintenance required.
Store, retrieve, and manage memory through one streamlined API. No ops, no setup, no headaches.
Hot, warm, and cold layers keep agents fast and memory use efficient. No manual tuning needed.
Summarization and compression adjust automatically to your usage.
Control access, track usage, and clean up memory with tools built for visibility and scale.
Encryption, audit logs, and fine-grained permissions built in at every layer of the stack.
Minimal setup. Simple APIs. Built to fit your workflow, not the other way around.
Designed for effortless integration and intelligent scaling.
