01 · HYBRID RETRIEVAL
Connect what matters.
People, projects, preferences, and decisions, linked together. Retrieve with graph, vector, and keyword signals in one pipeline.
◇ A LONGER MEMORY. A BETTER AGENT.
Good AI
remembers.
Give your agents the context to pick up where they left off. Open-source memory that connects the dots, across conversations.
pip install prmePowered by PRME. Local-first. Apache 2.0.
WORKSPACE / ASTERowner: alex
Source preserved
Original event
✓Stored with owner, timestamp, and source.
Aster uses PythonAster uses PostgreSQLAlex prefers concise explanations
Sample data
FROM CONVERSATION TO CONTEXTPick a step to explore
Fits the way
you already build.
Python SDKHTTP APIMCP READYDuckDBPostgreSQL
BEYOND THE CONTEXT WINDOW
Your next conversation
shouldn’t start from zero.
Preferences. Decisions. The reason behind a choice. The useful things get lost when a session ends, so users repeat themselves and agents guess.
Prism gives them a place to live. Built on PRME, it turns stored events and relationships into relevant context your agent can carry into what comes next.
Meet the memory engineTwo sessions with the same agent. On Monday the user says they run on PostgreSQL and want short answers. On Thursday they ask for a migration. Without memory, the agent asks which database they use. With Prism, the agent recalls both facts from Monday and answers with a short PostgreSQL migration.
THE RIGHT CONTEXT, WITH ITS ROOTS INTACT
More than remembering words.
PRME keeps the original events, links what they mean, and retrieves the few memories that matter for the next turn.
02 · SOURCE-BACKED MEMORY
Keep the story behind it.
Follow a memory back to its source. Preserve original events, represent explicit corrections, and keep conflicting claims visible.
03 · LOCAL-FIRST BY DESIGN
Take your memory with you.
Start with a local memory pack. Run on your own infrastructure, rebuild derived indexes, and keep control of your data.
SMALL INTEGRATION. LONG MEMORY.
Your agent.
Now with a past.
Store what matters. Retrieve what’s relevant. Pass the context to the model you already use.
Start with the Python SDK, expose memory over HTTP, or connect through MCP. No new agent framework required.
Read the quickstartPython 3.11+Sync & asyncModel agnostic
from prme import MemoryClient with MemoryClient("./memories") as memory: memory.store( "Alex prefers concise explanations.", user_id="alex", ) context = memory.retrieve( "How should I explain this?", user_id="alex", ) for result in context.results: print(result.node.content)YOUR MEMORY. YOUR WAY.
Build here. Run anywhere.
Start open source today. Help shape what comes next in the cloud.
Open source.
Wide open possibilities.
The complete PRME engine. Embed it in your product and run it where your data lives.
- Apache 2.0 licensed
- Local DuckDB or PostgreSQL
- Python, HTTP, and MCP interfaces
- Portable memory with source provenance
Focus on your agent.
Leave room for us.
A hosted home for Prism memory is on the way. Join the waitlist to hear when early access opens.
The same open-source foundation.
A managed experience in the making.
A managed experience in the making.
What’s the difference between Prism and PRME?
Prism is the product and hosted-service direction. PRME, the Portable Relational Memory Engine, is the open-source Python engine underneath it. You can use PRME in your own application today; hosted Prism is accepting early-access interest.
How is this different from a vector database?
PRME combines an event log, a relational graph, vector search, and lexical search. It stores relationships, evidence, and validity windows alongside content, then packs relevant memories into a bounded context for your model. Vector similarity is one retrieval signal.
Can I run it on my own infrastructure?
Yes. PRME is Apache 2.0 licensed and runs locally with DuckDB, USearch, and Tantivy. A PostgreSQL backend is also available. You choose where to store memory and which model providers to use.
Does it work with my existing agent?
PRME offers synchronous and asynchronous Python interfaces, an HTTP API, and an MCP server. Integrations are available for LangChain and LlamaIndex. Your application retrieves memory and passes the resulting context to its model.
What happens when information changes?
PRME supports explicit corrections, supersedence, validity windows, and contradiction links. Original events are retained, and a newer statement is not automatically treated as true. Store-time supersedence is opt-in; exact historical replay is not currently supported.
Is hosted Prism available today?
Hosted Prism is in early access planning. Join the waitlist for availability updates. Pricing and hosted service details have not been announced. You can start building with the open-source engine now.