Tool overview
Memori is listed under AI Infrastructure & MLOps AI tools.
What is Memori?
Memori is an LLM-, datastore-, and framework-agnostic memory layer for agents, copilots, and AI applications. It captures conversations and execution traces, extracts structured knowledge, supports intelligent recall, and runs as open source, managed cloud, VPC, or on-premises.
Best for
Engineering teams adding governed long-term memory to production agents
Who is it for?
Decision note
Rebuilt from the original export under the complete V411 factual-source gate. Each tool was researched independently and every high-risk family was checked again in a second pass. Preview only. Apply remains blocked until failures = 0, warnings = 0, unmapped = 0, missing = 0, logo QA is accepted or image import is disabled, explicit clears are reviewed, and a representative WordPress edit screen is checked.
Key features
Conversation and agent-trace memory capture
Structured facts, preferences, rules, and relationships
Python, TypeScript, MCP, and framework integrations
Cloud, BYODB, VPC, and on-premises deployment
Use cases
Give agents cross-session memory
Personalize copilots with user context
Share controlled memory across teams
Add memory to coding and support agents
Pros
- Free open-source and cloud tiers
- LLM- and framework-agnostic design
- Multiple enterprise deployment models
Limitations
Persistent memory requires clear consent, scope, retention, deletion, access-control, and sensitive-data policies
Benchmark results do not replace evaluation on the application's own users, traces, tools, and failure modes
Pricing details
Billing options
Pricing note
Open Source and Cloud Free cost $0. Team starts at $60,000/year, Business at $150,000/year, and Enterprise is custom. The eligibility-limited startup program is not recorded as a general free trial.
Supported languages
- English
Integrations
PostgreSQL
MySQL
MongoDB
CockroachDB
MCP
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