Player profile
NarraNexus
An open-source AI agent team workspace by NetMind.AI whose agents remember, collaborate, and use tools from day one.
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Where it fits
NarraNexus is an open-source AI agent team workspace by NetMind.AI. It is not another framework for wiring agents together, but a team of agents that already remember, collaborate, and use tools from day one.
It belongs in Open Orchestrators because it provides a complete multi-agent operating environment: agents with persistent memory across sessions, multi-agent collaboration, composable capabilities (Memory, Awareness, Chat, RAG, Jobs, Skills, Social Network, Matrix), MCP tool integrations, and cloud/macOS/local deployment options.
Builder web analytics
Measure projects built with NarraNexus
NarraNexus gives teams a ready-to-run agent workspace where agents collaborate with persistent memory. Agent Analytics measures whether the agent-driven changes move real users afterward.
Instrument the project surface that NarraNexus agents affect. Agent Analytics reads the reported web or product events; it does not replace NarraNexus internal logs or traces.
First loop to measure
- a NarraNexus agent team collaborates on a website, docs, onboarding flow, product surface, or experiment
- the changed surface reports visits, sources, CTA clicks, signup, activation, retention, or task-completion events to Agent Analytics
- a NarraNexus agent fetches Agent Analytics results after the change ships
- the agent team updates its next task from measured user behavior
Copyable prompt
Use Agent Analytics for this project. If event reporting is missing, add the tracker and report events for this project surface, including NarraNexus-managed page, docs path, traffic source, CTA click, signup, activation event, retention signal, or shipped experiment. Verify events are arriving. Then fetch the last 7 days and compare them with the prior 7 days. Tell me which NarraNexus-managed page, docs path, traffic source, CTA click, signup, activation event, retention signal, or shipped experiment moved users toward value, where users dropped off, which sources mattered, and what my agent workflow should improve next.