What is an AI Copilot

An AI copilot is a digital expert that works alongside your Technicians. It reasons over your own manuals, procedures, and field-proven fixes — not the general internet — and understands the specific configuration of the machine in front of the Technician.

Where a search bar returns a document, a copilot returns the next step: the right procedure, filtered to that unit, with the part number and the safety requirement attached. The result is measured in first-time fix rates and downtime, not in answers returned.

How It Works

The request

This is where the interaction begins — context engineering, or preparing the LLM with the right information before it starts to reason.

When a Technician asks a question, runs a task, or triggers an action, the system builds a structured prompt behind the scenes. That context frame includes:

Intent: the raw question or command.
Asset context: specific machine details, serial numbers, and current configurations.
Memory: relevant conversation history.
System directives: any underlying rules, constraints, or instructions.

The LLM

The core intelligence and orchestration layer of the copilot. The LLM receives the structured request alongside the asset data and conversation history, and acts as a routing engine to decide:

Which specialized agents to call.
What specific data is required to fulfill the request.
How to formulate the final answer.

Agents

The LLM does not do everything itself — it delegates specific tasks to specialized agents, which fall into two categories.

Built-in agents are securely connected to your internal knowledge base and use only verified data, which prevents hallucinations:

Agent	What it does
Manuals and Videos	Searches documentation, PDFs, and training content.
Solutions	Retrieves known fixes, historical resolutions, and best practices.
Tasks	Executes and guides Technicians through step-by-step procedures.
Parts	Looks up part numbers, component specifications, and replacement details in a parts spreadsheet.

Dynamic agents connect to live systems — OEM, factory, and lab systems — to pull real-time data:

Agent	What it does
Scripted	Executes custom, user-defined automations.
MCP (Model Context Protocol)	Manages external tools, third-party APIs, and system integrations.

The answer

Once the LLM has finished reasoning and the delegated agents have returned their results, the system synthesizes them into a clear, cohesive response. The final output delivers exactly what the Technician needs, which may include:

Step-by-step instructions
Root-cause diagnoses
Structured data summaries
Actionable next steps