Memory Layer
for your AI agents.
The managed memory layer for AI agents. Store user preferences, past conversations, and facts across infinite sessions—without managing vector DBs.
Why standard RAG fails for agents
× Context Limits
Injecting entire conversation histories gets expensive and confuses the model with irrelevant noise.
× The "Goldfish" Effect
Standard chatbots reset their memory every session. They can't learn user preferences over time.
× High Latency
Naive vector search is too slow (500ms+) for real-time voice agents that need human-like response times.
Self Learning layer. Gets smarter with every interaction
Don't just store logs. Build to adopt uniquely to your users.
1. Ingest Conversations
Stream chat logs, voice transcripts, or raw text. We identify the user and the context automatically.
2. It Learns & Evolves
The engine detects changes. It updates the profile ('Omnivore' → 'Vegetarian') and forgets outdated facts.
3. Contextual Recall
Next time they ask for food, the agent knows. No manual prompts needed. It just feels like magic.
Superior Recall Accuracy. ⚡️
We outperform ChatGPT on context retrieval tasks.
Based on Snap Research LoCoMo Benchmarks.
Save up to 90%
on inference costs.
Standard chatbots re-send the entire conversation history with every new message, bloating your context window.
LongMemory acts as a semantic filter, retrieving only the specific facts needed for the current query. Stop paying for noise.
- Reduce context Tokens by ~90%
- Lower Latency ⚡️
Token Usage per Request
Self Learning Memory Layer 🪴
Don't ask users to repeat themselves. Longmemory learns about you as you interact
Ordering your usual Oat Milk Latte.
Pickup in 10 mins.
Break Context Limits 🚀
Search Years old context in milliseconds ⚡️
Ask "What did we discuss last Tuesday?" or "How has my sleep changed since November?" and get accurate, time-aware answers.
Fastest Recall speeds ⚡️
When you're building voice agents, every millisecond counts. We optimized our retrieval pipeline to fit within the 200ms conversational turn window.
* Mem0 latency (1.44s p95) sourced directly fromarXiv:2504.19413v1(Table 2). LongMemory latency (123ms p99) measured on LoCoMo Benchmark by Snap Research.
Why we are different
Built for high-speed agents, not just chatbots.
mem0
- Read Latency~1.4s+
- Setup TimeModerate (Config heavy)
LongMemory.io
Self Evolving memory layer 🪴
- Read Latency~123ms11x Faster
- Infrastructure Fully Managed
- Optimized For Real-time / Voice
- Setup Time3-4 Lines of code