Building the operating layer for enterprise AI.
Structured knowledge plus role-scoped agents, deployed inside your perimeter. Open source at the core, owned by your enterprise.
Most enterprise AI projects stall in the same place. The model is fluent; the company is illegible. There is no shared context for the model to act on, so the output is generic and the project never makes it past pilot.
Hubzoid builds the company side of that equation. Structured knowledge of how an organization actually decides, plus a workforce of role-scoped agents that act on it. The hub is deployed inside the customer's perimeter, so the model has full context and the data never leaves.
Three phases. One operating layer.
The same model behind hubs now running in retail, manufacturing, and IT operations.
We map how the company decides.
World models, policy thresholds, escalation routing, named owners. The structured knowledge most AI projects skip straight past, captured as versioned markdown.
Role-scoped agents, wired in.
On-demand tools, conversational Q&A, scheduled background workers. Connected to your existing systems read-only, running on the open-source runtime inside your cloud.
The hub becomes yours.
Versioned in your repository, operated by your team against a runbook. Engineer access is time-bound and revoked. Nothing about it stays locked to us.
Five positions, taken seriously.
- 01
Domain knowledge is the bottleneck. The model is not.
- 02
Inside the customer's perimeter, or it does not count as enterprise.
- 03
Deterministic where policy matters. Agentic where judgment matters.
- 04
Open source at the core. Auditable, never a black box.
- 05
Owned by your enterprise. No vendor lock-in.
The runtime is not a black box.
The substrate behind every engagement is an open-source package: hubzoid, MIT-licensed, installable with pip install hubzoid. It runs inside your perimeter, against your data, so your team can read exactly what executes. The same package powers our engagements. What you audit is what ships.
View the repository$ pip install hubzoid $ hubzoid init demo-hub $ hubzoid run demo-hub → hub live at localhost:3080
Selective by design.
Conversations begin with a single 30-minute fit call. If the hub is right for your operating layer, we say so. If it is not, we say that too.