World's FirstHuman-Like Memory
We've Engineered A Foundational Memory Layer Powering Next-Gen AI World Models
No credit card required · Free tier available
Works with every agent framework
Hypermemory is a hybrid memory retrieval system for AI agents. It combines semantic search, BM25 keyword matching, temporal scoring, and multi-hop reasoning to give long-running agents persistent, adaptive memory. Unlike context windows that reset, Hypermemory persists facts across sessions and achieves state-of-the-art results on the LoCoMo conversational memory benchmark — scoring 92% on Temporal Reasoning, 94% on Single Hop, and 88% on Multi Hop.
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Live Dashboard
Full Visibility Into Every Memory
Search, trace, ingest, and query your memory store. Explore retrieval analytics. Earn XP as you explore.
6
Memories
0.90
Avg Score
5
Active
12ms
Avg Latency
0.90
Avg Score
5
Active
4
Modes Used
Retrieval Radar
Product launch is April 15th — confirmed by CEO in standup
Mode Usage
Most active mode: Semantic
Source Breakdown
24h Activity
liveMemory ingestions over last 24h
Score Distribution
Architecture
5 Retrieval Modes, Running in Parallel
Every query fans through all strategies simultaneously. Adaptive score fusion returns the best result from whichever path wins.
Finds conceptually similar memories even when exact words differ
Precise recall for exact terms, names, and specific phrases
Weights recent memories higher; detects date-specific queries
Structured recall of who, what, where from extracted facts
Chains related memories across topics for complex queries
Memory Retrieval
Hybrid Retrieval Architecture
Hypermemory gives long-running agents persistent, adaptive memory that continuously evolves their intelligence. It drives cost-efficient self-learning, saving developers time, tokens, and money while enabling advanced reasoning across domains like temporal, inferential, and open-world tasks.
Semantic Search
Vector SimilarityKeyword Search
BM25 RankingTemporal Reasoning
Date-AwareMulti-Hop Reasoning
Connected TraversalAdversarial
Hallucination-ProofInferential
Commonsense + World KnowledgeData Ingestion
API · MCP · SDK
Fact Extraction
Lazy Async
Multi-Modal Index
5 Modes
Query Intelligence
Expand · Filter
Hybrid Retrieval
Score Fusion
Memory Response
Ranked + Proven
Developer API
Built for Developers
Simple REST API and MCP integration. Add memory to your AI in minutes.
REST API
Store and retrieve memories with a simple HTTP call
curl -X POST https://api.hypermemory.run/v1/memories \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"agent_id": "support-agent",
"content": "Arjun from FinexAI: latency spiked to 8s after v2.3.1 SDK update — hotfix needed by 5pm",
"metadata": { "source": "slack", "customer": "FinexAI", "priority": "high" }
}'MCP Integration
Add Hypermemory as a Model Context Protocol server
{
"mcpServers": {
"hypermemory": {
"command": "npx",
"args": ["-y", "hypermemory-mcp"],
"env": {
"HYPERMEMORY_API_KEY": "your-api-key",
"HYPERMEMORY_AGENT_ID": "support-agent"
}
}
}
}Integration
One-Line Ingestion.
Infinite Recall.
Add persistent memory to your LLM apps with a single function call.
from hypermemory import Hypermemory
hm = Hypermemory(api_key="your-api-key")
# Store a memory — fact extraction happens automatically
hm.add(
agent_id="support-agent",
content="Arjun from FinexAI reported that inference latency spiked to 8 seconds "
"after the v2.3.1 SDK update. Needs a hotfix by 5pm or escalates to CTO.",
)
# Recall with natural language — multi-modal retrieval kicks in
results = hm.search(
agent_id="support-agent",
query="Which customers are affected by the SDK latency regression?",
)
# Returns: relevant memories ranked by semantic similarity,
# temporal recency, and entity-fact matchesOpen Source
Open Source at Heart
Built in the open. Join thousands of developers building the future of AI memory.
MIT Licensed
Use it freely in personal projects, startups, or enterprise products. No strings attached — ever.
Fully Auditable
Every line of the memory layer is public. Understand exactly how your data is stored, retrieved, and scored.
Self-Hostable
Deploy on your own infra — on-prem, private cloud, or air-gapped. Zero dependency on our servers.
Shape the Roadmap
Open issues, submit PRs, and vote on features. The community drives what gets built next.
Our commitments
Performance
LoCoMo Benchmark Results
Hypermemory excels across all LoCoMo evaluation domains.
| Domain | Hypermemory | Baseline |
|---|---|---|
| Temporal Reasoning | 92% | 61% |
| Open Domain | 89% | 58% |
| Inferential | 87% | 54% |
| Single Hop | 94% | 67% |
| Multi Hop | 88% | 52% |
Use Cases
AI Memory That Adapts to Your Domain
Hallucination-proof RAG for compliance-critical AI
Patient data retrieval, diagnostics, drug interaction checks
Reduce Readmissions by 40%
Telehealth agents that remember every patient interaction, medication change, and care preference. No more lost context between visits — your AI assistant recalls what matters for better outcomes.
- Cut repeat diagnostic workups by 60%
- Catch medication conflicts before they happen
- Track patient journeys across providers seamlessly
Live example
Use Cases
Built for Every Industry
Hypermemory adapts to your industry — the same retrieval engine, tuned to what matters most in your context.
Agents that remember every patient
Telehealth agents that recall medications, symptoms, allergies, and care preferences across every visit — reducing readmissions and improving outcomes.
40%
fewer readmissions
Tutors that adapt to every learner
AI tutors that track each student's learning pace, knowledge gaps, and preferred explanation style — personalizing every session from day one.
3×
faster concept retention
Shopping assistants with taste memory
Agents that remember what a customer bought, returned, loved, and hated — surfacing the right product before they even search for it.
2.8×
higher conversion
Support that never makes you repeat yourself
Agents with full conversation history across channels. Every ticket, refund, and complaint remembered — so customers never have to explain twice.
65%
reduction in handle time
AI reps that remember every deal detail
Sales agents that track objections, competitor mentions, stakeholder names, and deal history — delivering hyper-personalised follow-ups that close.
31%
higher close rate
Assistants that track regulatory changes
Agents that monitor case law, contract clauses, and compliance requirements over time — with temporal supersession so the current rule always wins.
90%
faster clause retrieval
NPCs with persistent world memory
Game characters that remember player choices, past interactions, and evolving storylines — creating narratives that feel genuinely alive.
4×
player session length
Internal agents that know your org
Knowledge agents that remember org charts, project history, team preferences, and institutional knowledge — making every employee 10× more effective.
55%
reduction in search time
Enterprise
Secure Memory Layer That Cuts LLM Spend and Passes Audits
SOC 2 Type II ready. Deploy anywhere. Full audit trails.
Zero-Trust Security & Compliance
SOC 2 Type II ready. End-to-end encryption, RBAC, and audit logs for every memory operation.
Deploy Anywhere, No Tradeoffs
On-prem, private cloud, or managed SaaS. Same API, same performance, your infrastructure.
Traceable by Default
Full provenance for every memory. Know where data came from, when it was updated, and who accessed it.
Deployment Options
From the Blog
Insights on AI Memory
Why Your AI Agent Forgets Everything — And How to Fix It
Long-running agents break down not because of bad reasoning, but because they can't remember. We explore the root causes of context degradation and the architecture that solves it.
Hybrid Retrieval: Why One Search Strategy Is Never Enough
Semantic search alone misses keywords. BM25 alone misses meaning. Temporal search alone misses context. Here's how fusing all five retrieval modes with RRF produces SOTA results.
One-Line Memory for Any LLM Framework
Whether you're on LangChain, LlamaIndex, CrewAI, or raw OpenAI — adding persistent memory to your agent should take minutes, not weeks. Here's how we built that.
SOTA on LoCoMo: Breaking Down the Benchmark Results
Hypermemory achieves state-of-the-art across all 5 LoCoMo domains. We walk through what each domain tests, where other systems fail, and why our temporal fact engine makes the difference.
Temporal Supersession: Tracking Facts That Change Over Time
"My meeting with Sarah is on Thursday" becomes stale the moment the meeting passes. Here's how Hypermemory's fact graph tracks current state vs. historical state without explicit updates.
Self-Hosting Hypermemory: A Complete Guide
Run Hypermemory entirely on your own infrastructure — on-prem, private cloud, or air-gapped. This guide covers deployment, Qdrant configuration, and production hardening.
Join The Hypermemory Community
Connect with developers building the future of AI memory.