Long-running engagements where context matters
Customer success, account management, research projects — work where today's question depends on what was learned six weeks ago.
Agent
OpenClaw with a brain that compounds.
OpenClaw + GBrain pairs the open-source workhorse agent with a persistent local brain — facts, decisions, files, and people the agent has encountered are remembered across sessions instead of re-explained every time. On MindsHub it deploys in one click: agent, brain, model router, and 43 pre-loaded skills, no setup.
GBrain is a local memory layer for agents — a structured store of pages, facts, and entities that the agent reads from before answering and writes to as it works. Layered onto OpenClaw, it turns a stateless agent into one that gets sharper week over week: it remembers the customer you asked about last Tuesday, the schema decision you made last sprint, the playbook you reviewed last month.
On MindsHub, OpenClaw + GBrain ships as a 1-click deploy. Each user gets their own isolated instance with GBrain pre-installed (pinned to a verified upstream release), a 43-skill skillpack already scaffolded, PGLite as the local brain backend (no external database to wire up), and the MindsHub Model Router pre-configured. The full stack provisions in ~2–3 minutes and is ready to use without touching a terminal.
Customer success, account management, research projects — work where today's question depends on what was learned six weeks ago.
Your people, projects, decisions, and preferences — encoded once, reused forever. The agent stops re-asking questions you already answered.
Standups, design reviews, postmortems — every conversation feeds the brain, so the agent can answer 'what did we decide about X?' months later.
Sources, claims, contradictions tracked over time. The agent can surface 'we saw the opposite finding in the March report' without you remembering it existed.
An agent that remembers your investors, your customers, your team's history — without you re-priming it every Monday morning.
OpenClaw + GBrain is open-source either way. The difference is the operational backbone around it.
| What you handle… | Self-hosted | On MindsHub |
|---|---|---|
| Secrets management | You manage keys, rotation, scoping | Built-in credentials vault |
| Model access | One provider relationship per LLM | Model Router with `latest:*` aliases |
| Persistent execution | Queues, workers, retries you build | Managed runtime, jobs survive restarts |
| Memory across runs | Your storage, your schema, your reset logic | Shared memory store, built in |
| Tool integrations | Per-tool plumbing, per-tool auth | Pre-built catalog, shared auth |
| Observability | You wire your own traces | Scratchpad + audit log on every run |
| Scaling | VMs, queues, autoscaling rules | Managed — no servers to mind |
Agent, brain, model router, 43 skills — provisioned in ~2-3 minutes. The path from 'I want to try this' to a working agent is a single click, not a 2-hour setup.
Your brain lives on your instance. Other users' agents can't read or write to it. The data layer is private by construction, not by policy.
The agent talks to a hosted LLM gateway out of the box — no OpenAI / Anthropic key required to start. Bring your own keys later if you want direct provider control.
GBrain ships with 43 skills (brain-ops protocols, ingestion patterns, query workflows) already installed and brain-first compliant. The agent uses them from session one.
Long-running tasks survive restarts. Yesterday's facts inform today's answers. The brain compounds across every session — that's the point.
No PGLite to set up, no embedding model to choose, no autopilot daemon to wire up. MindsHub manages the layer; you describe the work.
One click. MindsHub provisions an isolated instance with OpenClaw + GBrain, the skillpack, the model router, and a per-instance brain.
Point the agent at the things it should remember — documents, conversations, people, decisions. GBrain extracts and stores; every future session reads from the same memory.
Hand off tasks the way you'd use OpenClaw, with one difference: the agent queries the brain first. Answers come back grounded in what you've taught it, not just general knowledge.
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