The Long-Term Memory Layer for AI Systems
Event-sourced, distributed memory that gives your AI agents perfect recall. 84% accuracy vs 32% for alternatives.
from cortexdb import Cortex
client = Cortex(api_key="your-key")
client.remember(content="Q3 revenue: $2.4M",
tenant_id="acme")
result = client.recall(query="Q3 revenue?",
tenant_id="acme")
Built for production AI workloads
Everything your AI agents need for reliable, accurate long-term memory. No compromises.
Event-Sourced Memory
Raw content preserved exactly as received. Never rewritten or hallucinated by an LLM. Full audit trail of every change.
Knowledge Graph
Auto-extracted entity relationships and causal chains. Understands connections between people, projects, decisions, and events.
Hybrid Retrieval
Multi-signal search combining keyword, semantic, and graph-based retrieval for superior recall and precision.
Crash Durable
Battle-tested storage engine with zero data loss under any failure scenario. Your memories survive anything, guaranteed.
Multi-Tenant
Full isolation per tenant with namespace support. Predictable performance at any scale with automatic resource management.
16 Data Connectors
Slack, GitHub, Jira, Notion, Salesforce, and 11 more built-in. Ingest your team's knowledge automatically.
Lossless architecture vs. lossy alternatives
Other memory systems rewrite your data through an LLM before storing it. CortexDB preserves the original.
CortexDB
Lossless, event-sourced
Raw content stored as immutable events
LLM enrichment is async, off write path
Write-path cost: ~$20/day for 10K events
Full audit trail with time-travel queries
Others
Lossy, LLM-rewritten
Content rewritten by LLM before storage
LLM on critical write path (latency + cost)
Write-path cost: ~$10K/day for 10K events
No audit trail, original data lost
CortexDB vs. the competition
A detailed comparison across the metrics that matter.
| Feature | CortexDB | Competition |
|---|---|---|
| Accuracy | 84% | 32% |
| Data preservation | Lossless (raw) | Lossy (LLM-rewritten) |
| Ingest speed | 2.5x faster | Baseline |
| Write-path cost | ~$20/day | ~$10K/day |
| Knowledge graph | Auto-built | Separate add-on |
| Crash durability | Crash-safe storage | Depends on vector DB |
| Data connectors | 16 built-in | 0 |
| Integrations | 35+ frameworks | Manual only |
| Cluster mode | Built-in consensus | N/A |
| Event sourcing | Full audit trail | None |
First-class SDKs for every stack
Get started in minutes with our Python, TypeScript, or REST API.
from cortexdb import Cortex
client = Cortex("https://api.cortexdb.dev", api_key="your-key")
# Store a memory
client.remember(
content="Q3 revenue exceeded $2.4M, up 34% YoY",
tenant_id="acme-corp",
)
# Retrieve with hybrid search
result = client.recall(
query="What was Q3 revenue?",
tenant_id="acme-corp",
)
print(result.context)
# => "Q3 revenue exceeded $2.4M, up 34% YoY"Connects to everything you use
Drop-in support for 19 agent frameworks, 16 data connectors, 6 orchestration tools, and more.
Ready to give your AI agents perfect memory?
Get started in under 5 minutes. Free forever for self-hosted deployments.