Memori - 2026 Pricing, Features, Reviews & Alternatives

Memori is agent-native memory infrastructure that converts agent execution traces and conversation turns into structured, persistent state for production AI systems. Compatible with any LLM provider via LiteLLM-native integration, it gives AI applications long-term memory across sessions and applications, stored either in the developer's own database (SQLite, PostgreSQL, MySQL, Neon, Supabase, GibsonAI) or via a fully hosted cloud option requiring only an API key. Target users include developers and engineering teams building AI agents, copilots, LLM applications, and multi-agent systems, with use cases spanning e-commerce, sales and CRM, customer support, wellness robotics, and enterprise knowledge management.

Memory is captured automatically by intercepting each chat turn and classifying content into facts, preferences, rules, and summaries. A three-agent processing system handles memory operations: a Memory Agent structures conversation outputs using Pydantic models, a Conscious Agent promotes high-priority memories for immediate access, and a Memory Search Engine retrieves and injects relevant context based on queries. Named-entity recognition extracts semantic triples to build a deduplicated knowledge graph, while vector embeddings power semantic search across conversations and documents. Agent trace memory structures long-term state directly from execution paths, tool results, workflow steps, outcomes, and decision logic, with asynchronous processing that adds no latency to agent responses. Stale memory decay surfaces only relevant context over time.

Memory is SQL-native, making it structured, durable, and auditable for production workloads. Scoped memory isolation tags each memory by entity, process, and session to prevent cross-user and cross-project context leakage. Role-based access control provides read, write, and admin permissions per memory operation, with SSO and OAuth identity provider integration. Shared team memory spaces support collaborative AI applications. Memory data can be imported and exported between instances. Advanced analytics cover memory insights, conversation patterns, and usage metrics. Daily briefings deliver structured summaries from execution traces covering priorities, risks, active goals, and known failure patterns. Available as open source with free starting credits, and a startup program serves companies that have raised less than $5M.