Memori Labs Launches Memori Cloud – The Fully Hosted SQL-Native Memory Layer for Production AI Agents

Memori Cloud enables teams to deploy persistent, LLM-agnostic memory in minutes – with zero database setup, full observability, and up to 98% reduction in inference costs.

Memori Labs announced the launch of Memori Cloud, a fully hosted version of its SQL-native memory infrastructure built for production AI agents. Memori Cloud enables developers and enterprises to add persistent, evolving memory to AI systems without provisioning or managing database infrastructure.

Memori Labs is the creator of the leading SQL-native memory layer for AI applications. Its open-source repository is one of the top-ranked memory systems on GitHub, with rapidly expanding developer adoption and growing enterprise deployment across customer support agents, commerce automation, internal copilots, and other multi-session AI workflows.

Unlike vector-only memory solutions or proprietary memory stacks that require new infrastructure decisions, Memori is built SQL-native from the ground up – enabling structured, durable, and auditable memory that fits naturally into enterprise production environments.

“AI agents without memory are inherently stateless and inefficient,” said Adam B. Struck, CEO and Co-Founder of Memori Labs. “Memori Cloud transforms interactions into durable, structured knowledge and retrieves the right context in real time – dramatically reducing inference spend while eliminating the operational burden of managing memory infrastructure.”

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Built for Production, Not Prototypes

Most AI systems today rely on stateless LLM calls and repeated context injection, leading to token bloat, higher latency, and inconsistent user experiences. Memori is designed specifically for production environments where reliability, durability, and observability matter.

Built SQL-native from the ground up, Memori stores memory in structured, queryable form with transactional integrity – making it suitable for real-world enterprise workloads rather than experimental demos. The platform is LLM-agnostic by design, allowing teams to integrate with providers such as OpenAI, Anthropic, Gemini, Grok, and Amazon Bedrock without vendor lock-in. With flexible deployment options including fully hosted, BYODB, and on-prem or VPC configurations, Memori enables organizations to maintain their security posture, compliance requirements, and infrastructure preferences while deploying persistent AI systems at scale.

Built for Teams That Want Memori Without the Ops Overhead

Memori’s BYODB (“Bring Your Own Database”) offering provides maximum control for teams running on their own infrastructure. Memori Cloud extends those same capabilities into a fully managed option for teams that want to move quickly without handling database provisioning, schema management, or ongoing operational maintenance.

With Memori Cloud, teams can get started using a single API key and the same Memori SDK they already use across deployment models, while avoiding the need to provision storage infrastructure and still maintaining production-grade reliability, performance, and observability as they scale.

What Memori Cloud Delivers at Launch

Memori Cloud provides a managed memory pipeline for AI applications, including:

• Synchronous capture of LLM conversations on the request path
• Asynchronous advanced augmentation to extract facts, preferences, skills, and relationships
• Semantic recall that ranks and injects relevant memories into future prompts
• Knowledge graph construction from extracted semantic triples

This architecture ensures memory is fast where it needs to be – and intelligent where it matters most.

“Developers want memory that feels native to their application: fast on the request path, richer in the background, and observable when something goes wrong,” said Michael Montero, CTO of Memori Labs. “Memori Cloud pairs synchronous capture with asynchronous augmentation, then makes the entire memory lifecycle visible through a dashboard so teams can inspect, validate, and optimize as they scale.”

A Dashboard for Testing, Observability, and Memory Inspection

In addition to the core managed memory engine, Memori Cloud launches with product tooling through the Cloud Dashboard, including:

• Memories: inspect memory rows, subjects, retrieval counts, and graph relationships
• Analytics: monitor created/recalled volume, sessions, users, and quota usage
• Playground: chat and watch extracted memories and graph updates in real time

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