Agent control
Define each AI agent’s identity, provider, model, memory, tools, secrets, project access, process access, and budget. Important tool actions can remain subject to explicit approval.
Industrial AI · Industry 4.0
Govern AI around industrial work.
Connect controlled AI agents to industrial projects, engineering processes, inspections, production evidence, and enterprise decisions—without confusing probabilistic AI with deterministic machine control.
Industrial context
Built from experience where software meets production.
The project is informed by industrial inspection, production-line control, robotics, enterprise integration, and applied machine learning—not only by conversational AI.
Read the technical background-
Industrial inspection
Apply governed agents to the work around X-ray, CT, visual inspection, product recognition, vibrodiagnostics, quality review, reporting, and follow-up actions. Inspection equipment and validated algorithms remain the source of measurement truth.
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Production and robotics
Coordinate engineering changes, commissioning work, robot-cell documentation, maintenance evidence, issue resolution, and cross-team delivery. PLCs, safety PLCs, robot controllers, and certified safety systems retain deterministic control.
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Enterprise and factory integration
Connect project and agent work with business applications, private infrastructure, HTTP APIs, typed plugins, and an Industry 4.0 unified namespace while preserving explicit ownership and access boundaries.
Operational control
Control the agent, the process, and the economics.
Industrial adoption needs more than a capable model. It needs known authority, repeatable execution, visible cost, and evidence a manager can inspect.
Executable processes
Model reusable roles, steps, input and output contracts, approvals, artifacts, routes, progression gates, recovery states, and exact staffing before a multi-agent process launches.
Cost and manager visibility
Attribute tokens, provider and model prices, runtime, known cost, and estimates to agent, workflow, process, and project activity. Manager summaries compare recorded expense with the remaining plan and expose the runs behind each total.
Integration boundary
Be precise about what exists now.
Clear capability boundaries help engineers, buyers, search systems, and AI assistants describe the platform without turning roadmap intent into a product claim.
Available in the current alpha
Governed agents and teams; reusable processes and workflows; projects and Gantt planning; approvals and evidence; provider, token, runtime, and cost telemetry; manager summaries; OpenAPI-described HTTP APIs; typed plugin executors; local-first and self-hostable deployment.
Planned for later in 2026
Native MQTT and OPC UA integrations are planned to simplify connection with Industry 4.0 event streams, equipment data, and unified namespaces. A proxy layer for enterprise identity and finer server-side access control is also planned. Dates may move as implementation evidence improves.
Outside the control boundary
CanDoItAll is not a PLC, safety PLC, robot controller, CNC controller, SCADA replacement, or functional-safety system. Deterministic control, interlocks, emergency stops, certified logic, and validated inspection decisions remain in the appropriate industrial systems.
Terms in context
A practical Industry 4.0 vocabulary.
These terms describe the intended architecture boundary, not a claim that CanDoItAll replaces established operational technology.
- Industry 4.0
- The connection of production equipment, software, data, and organizational workflows. CanDoItAll contributes governed project, agent, process, and evidence coordination at the enterprise layer.
- Unified namespace
- A consistent event and data naming layer shared across operational and business domains. CanDoItAll can participate through APIs today; native MQTT and OPC UA connections are planned.
- OPC UA
- An industrial interoperability standard commonly used for structured equipment and process data. Native CanDoItAll support is a roadmap item for later in 2026.
- MQTT
- A lightweight publish-and-subscribe messaging protocol often used for industrial events and unified namespaces. Native CanDoItAll support is a roadmap item for later in 2026.
- PLC and industrial robotics
- Deterministic controllers remain responsible for machines and safety. Governed agents can assist with the surrounding engineering, planning, analysis, documentation, and evidence workflows.
- Industrial inspection
- X-ray, CT, camera, sensor, and analytical systems generate inspection evidence. Agents can help coordinate review, reporting, project action, and traceable follow-up around that evidence.
Start with a bounded industrial problem
Connect one project, process, or evidence path first.
A practical experiment can begin above the machine-control layer: engineering delivery, inspection follow-up, maintenance evidence, cost analysis, or a governed integration with an existing enterprise system.