Personal agents that learn the user
Remember preferences, goals, commitments, and corrections so the agent becomes more useful without a growing system prompt.
agent task · “Plan today around my active goals and working preferences.”
for individual agent builders
Build an agent that knows the user and remembers the work.
A personal assistant, coding copilot, or research agent should not need its entire history pasted into every prompt. memoricAI gives it durable memory that stays current across sessions, tools, and tasks.
incoming agent task
“Continue the Helix research and propose the next experiment.”
run_041/tool_output
The personal recall prototype tested best.
research/market_map.pdf
Most alternatives focus on team search.
user/preferences
Prefer small tests with one measurable variable.
assembled context
3 memories · 126 tokens
Continue the personal recall prototype. Test whether answers linked to sources improve task completion; change only the retrieval mode and measure correction rate.
where agent memory pays off
Agents that continue, not restart.
Use persistent memory wherever an agent needs to build on previous work instead of reconstructing context from scratch.
Coding agents with project history
Carry architecture decisions, rejected approaches, and recent changes from one coding session into the next.
agent task · “Implement this change without reopening a rejected design.”
Research agents that compound evidence
Relate new papers and web findings to earlier hypotheses while keeping the source behind every remembered claim.
agent task · “Update the thesis with this paper and flag contradictions.”
Workflow agents that resume
Let long running automations remember prior outputs, tool results, and unresolved work across independent runs.
agent task · “Continue the workflow from the last verified result.”
the agent memory loop
Every run makes the next run better.
Start with one agent and one repeated workflow. memoricAI handles the memory lifecycle around every run.
- 01observe
Send the events worth remembering
Ingest user messages, documents, tool outputs, and verified results through the API or supported connectors.
- 02distill
Turn a noisy run into durable memory
memoricAI extracts atomic facts, preferences, and decisions while keeping each memory linked to its source.
- 03retrieve
Resolve the context for the next task
Hybrid search finds relevant memories and follows version chains so superseded facts do not enter the run.
- 04inject
Give the agent a compact context packet
Use the API, MCP server, or OpenAI compatible memory router to place context that is ready to use before the model call.
the foundation
Your agent memory stays yours.
Agent memory becomes part of the application. You should be able to inspect it, move it, and decide where it runs.
- linked to sources
- Every retrieved memory retains provenance so the agent can cite evidence and you can debug why it acted.
- runs anywhere
- Run the same MIT licensed engine on your own Postgres, or use the managed cloud and move later.
- made to forget
- Version chains, deletion, and expiration keep stale context from becoming permanent agent behavior.
Build an agent that recognizes the next run.
Start with the workflow whose context you are tired of rebuilding. Give that agent a past it can use.