Session memory with fact extraction
Store user messages in an agent session, extract useful turns into short facts, and search them later instead of replaying the full transcript.
Actx0 is managed memory infrastructure for AI agents and apps. It helps teams store session context and workspace knowledge, then retrieve relevant facts in milliseconds before the next reply.
Actx0 is managed memory infrastructure for AI agents and apps. It stores session memories and workspace knowledge, then retrieves matching context in milliseconds before the next model response. The product is meant to sit around your model, not replace it.
The platform is built around a simple workflow: write user messages to an agent session, let Actx0 extract useful facts in the background, and search those memories when you need context. The source pages position it for production use, with managed cloud hosting, access keys, workspace isolation, audit logs, and monthly billing.
Store user messages in an agent session, extract useful turns into short facts, and search them later instead of replaying the full transcript.
Search workspace knowledge alongside session memories when the question relates to documents such as FAQs or policies.
Use the documented flow of add, learn, and retrieve to capture messages, extract facts in the background, and ground the next reply on the returned hits.
Run against managed cloud infrastructure with monthly self-serve billing, so teams do not need to provision or scale their own servers.
Work with Python, Node.js, Go, and REST clients using access keys and workspace IDs; the examples show no vector store to operate.
Control access and visibility with workspaces, roles, access keys, audit logs, usage tracking, and optional inactivity cleanup for sessions.
Keep ticket context in a session so a support agent can recover the last useful fact before replying, instead of rebuilding context from the whole thread.
Store stakeholder notes, objections, and commitments on a deal session, then retrieve them before the next call or follow-up message.
Remember appointment preferences and prior conversation context for scheduling or intake bots, while keeping clinical systems separate.
Use workspace knowledge for FAQs and policies, then ground replies in retrieved document chunks instead of relying on prompt stuffing.
Maintain memories for tutorials, coding conventions, or personal recommendations so the agent can adapt based on what was learned in the same session.
Actx0 stores user messages in an agent session, extracts useful facts in the background, and lets your app search those memories before generating the next reply. The source pages describe a simple flow: add messages, extract facts, then retrieve matching memories and knowledge.
The source shows Python, Node.js, Go, and REST clients. Example code uses an access key and workspace ID, then creates an agent, session, messages, and a memory search request.
Yes. The pricing page lists Hobby at $0/mo, Starter at $19/mo, Growth at $69/mo, Pro at $219/mo, and Enterprise with custom plans. All plans are billed monthly on Actx0's managed cloud.
Actx0 is positioned as memory infrastructure rather than a helpdesk, CRM, EHR, or channel-connector product. The case pages also note that integrations like helpdesk connectors or Salesforce and HubSpot connectors are not built in.
The product pages support session memory and workspace knowledge. They also note that sessions can be mapped across channels in your own app if you choose to use the same session ID, but Actx0 does not ship channel connectors.
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