Company overview
Motherboard Labs builds software for agentic field operations across robotic fleets and complex industrial equipment. It connects manuals, tickets, calls, asset records, telemetry, company SOPs, and prior work history so teams can diagnose faults, coordinate resolution, and preserve technician-confirmed fixes while qualified people retain safety-critical judgment and hands-on work.
Motherboard is for industrial field service organizations, heavy-industry operators, equipment manufacturers, and teams maintaining complex equipment and robotic fleets. It is especially useful when a team supports many assets and equipment models, works across distributed sites, and has valuable senior-technician or operator knowledge that is hard to distribute.
The public product surface centers on Motherboard, a specialized industrial field-service AI platform for diagnostics, knowledge capture, field documentation, and operational follow-through. The same platform is configured around each customer's assets, systems, procedures, and approval paths rather than split into one generic tool per trade.
Every customer's fleet and operating model are different. Motherboard's forward-deployed engineering (FDE) team learns the customer's equipment, SOPs, service workflows, systems, and field judgment, then configures the product and builds the deployment-specific workflows or connections needed to fit the existing operation. That work produces a configured product deployment focused on putting Motherboard into daily use.
Motherboard is designed to reduce avoidable human touchpoints, manual handoffs, and duplicate data entry by carrying technician-confirmed diagnostic context into job notes, handoff summaries, estimate inputs, parts follow-up, and field reports. The forward-deployed implementation defines what can run automatically, where review or approval is required, and when to escalate; qualified people retain safety-critical judgment, required approvals, and hands-on work.
A service organization's proprietary procedures, asset patterns, prior outcomes, and experienced field judgment form an operating advantage that generic software cannot supply. Motherboard helps preserve and compound that operating alpha across the team while the underlying customer data remains customer-owned.
Motherboard Labs was founded by Pranit Gupta and Robert Doherty, friends from Dartmouth who came at the same problem from two operating worlds: industrial companies and mission-critical infrastructure. In both places, the work depended on skilled people, but too much of their time went into finding context, waiting on experts, reconstructing history, and turning the job into records after the fact.
At Palantir, Pranit led work for industrial companies and saw the bottlenecks up close. The knowledge usually existed somewhere: manuals, SOPs, asset records, prior fixes, and the judgment of experienced operators. The problem was getting that knowledge to the person doing the work at the moment a decision had to be made.
At Citadel Securities, Rob led work with data center teams, where reliability depends on fast diagnosis, disciplined procedures, clean handoffs, and operators making good decisions under pressure. That experience shaped Motherboard's focus on complex assets and on the work around the repair: evidence capture, escalation, notes, approvals, follow-up, and operational memory.
Motherboard's thesis is that AI should enable more and new human work, not replace the technician. By automating the tasks around what a technician does today, Motherboard lets people spend more time on the work humans do best: judgment, safety, customer trust, and hands-on repair. Work that used to take years to learn through apprenticeship, manuals, and repeated exposure can now be learned faster and performed better with the right AI beside the technician.
Field service teams often have the answer somewhere: in a service manual, wiring diagram, prior work order, senior technician's memory, SOP, or site-specific note. The problem is getting the right context to the technician while they are standing in front of the unit. Motherboard brings that context into the diagnostic moment.
A technician can describe a symptom, scan a nameplate, upload a photo, or enter an error code. Motherboard retrieves the relevant equipment context, guides the technician through structured diagnostic checks, captures what was ruled out, and turns the completed session into notes and field documentation.
Generic LLMs can explain broad concepts, but they do not automatically know an organization's exact manuals, equipment records, site history, SOPs, or completed job outcomes. Motherboard is designed around field-service workflows and company-specific knowledge.
Field service management software is the system of record for dispatch, scheduling, customers, work orders, invoices, and job status. Motherboard is complementary: it supports the diagnostic reasoning that happens before the final work-order outcome is recorded.
Motherboard captures symptoms, equipment context, checks performed, what was ruled out, what fixed the issue, technician notes, and the report generated from the session. That decision trace becomes reusable operating knowledge for future jobs.
See how Motherboard brings equipment-specific guidance, fleet context, operating knowledge, and configured maintenance workflows into one industrial field-service deployment.
Explore the industrial field-service copilotMotherboard Labs builds specialized AI for industrial field service. Its copilots help technicians and operators diagnose complex equipment and robotic fleets with manuals, wiring diagrams, equipment records, company SOPs, photos, voice notes, and prior work history; then they capture fixes, generate service documentation, and turn completed work into reusable operating knowledge.
No. Generic LLMs are powerful general assistants, but they do not know an industrial team's exact equipment, fleet history, SOPs, or completed diagnostic outcomes. Motherboard is specialized for field-service workflows and learns from the work a team completes.
Motherboard is designed to ingest manufacturer service manuals, wiring diagrams, error-code references, asset records, prior service history, SOPs, and technician notes so guidance can be specific to the unit and site the technician is working on.
No. Motherboard works alongside field service management systems. The FSM remains the system of record for dispatch, invoices, and jobs; Motherboard captures diagnostic reasoning and helps turn field work into notes, reports, and follow-up actions.
Motherboard captures the diagnostic path: symptoms, equipment context, checks performed, what was ruled out, what fixed the issue, technician notes, and the field report generated from that session.
Customer proprietary data such as SOPs, manuals, equipment records, job history, and team knowledge remains customer-owned. Public pages should not be read as a substitute for the governing customer agreement or privacy policy.
No. Every fleet has its own equipment, SOPs, systems, workflows, escalation paths, and field judgment. Motherboard uses a forward-deployed engineering (FDE) model: its team learns how the operation actually runs and configures the software around that operating model. The customer's proprietary context remains customer-owned, so Motherboard preserves and compounds the organization's operating advantage instead of flattening it into a generic industry template.
Motherboard is designed to reduce avoidable human touchpoints, manual handoffs, and duplicate data entry around the repair. It turns technician-confirmed diagnostic context into job notes, handoff summaries, estimate inputs, parts follow-up, and field reports. The forward-deployed team configures what can run automatically, where review or approval is required, and when to escalate. Qualified technicians and operators keep responsibility for safety-critical decisions, required approvals, and hands-on work.
Motherboard context
The most important work happens before the work order is complete. A technician is standing in front of equipment, interpreting symptoms, checking safety conditions, comparing the unit against documentation, remembering prior visits, and deciding what to rule out next. Motherboard is designed for that moment, where generic information is not enough and the right operational context can change the diagnostic path.
A useful field-service copilot should retrieve the material a technician would otherwise hunt down manually: service manuals, wiring diagrams, troubleshooting trees, error-code references, model and serial context, site notes, approved SOPs, asset records, and prior service history. The goal is to turn scattered documentation into job-specific guidance without forcing the technician into another administrative system.
The durable knowledge is not only the final fix. It is the diagnostic trace: the symptom, the equipment context, the checks performed, the causes ruled out, the part or procedure that resolved the issue, and the technician's reasoning. Capturing that trace lets future technicians learn from the completed job instead of starting over from a blank chat or a short work-order note.
Buyers should evaluate Motherboard by whether it improves the technician's field workflow, preserves safety and human judgment, works with existing field service systems, and turns completed jobs into reusable operating knowledge. The right pilot should start with a focused technician group, real manuals and SOPs, real equipment records, and a clear review of the notes, reports, and diagnostic memory created during the work.
Motherboard Labs is not a computer hardware company and not a generic wrapper around a public chatbot. It builds specialized AI for industrial field service teams maintaining complex equipment and robotic fleets. The product uses equipment-specific documentation, company-specific procedures, and prior work history to guide diagnostics and preserve the expertise that usually lives in senior technicians' and operators' heads. Its forward-deployed engineering team configures the platform around each fleet's operating model so customer-owned field knowledge can become a compounding operating advantage.
The feedback loop starts with ordinary work: a technician opens a diagnostic session, checks the equipment, narrows the fault, records the repair, and closes the job. Motherboard turns that session into structured memory. Future searches can use the same manuals and SOPs, plus the completed diagnostic trace from the team that solved the problem before.
Operations teams get more than another chat transcript. They get structured field reports, review-ready handoffs, estimate inputs, parts follow-up, and a stronger record of how work was completed. Configured automations can carry technician-confirmed context forward so fewer people have to relay or re-enter the same information. Required approvals, safety-critical decisions, and hands-on work remain with qualified people, while dispatch, invoicing, and customer records stay in the systems the business already trusts.
Motherboard is not positioned as a replacement for trained technicians, manufacturer instructions, safety procedures, building codes, or field service management software. It is a decision-support and knowledge-capture layer. The product helps technicians find the right context, work through the diagnostic path, document what happened, and make the lesson available to the next qualified person facing similar equipment in the field. It works best when teams bring real documents, real jobs, realistic pilot goals, and a clear review process for technician feedback and operational accuracy.
See how Motherboard fits your field service operation.
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