Blinkin
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Frontline AI apps for connected workers

Operational AI for the people who keep industry running.

Blinkin turns approved manuals, SOPs, checklists, field evidence and expert know-how into guided AI apps for inspection, documentation, technical support and industrial service teams.

Connected workers in flow Multimodal evidence captured Expert control built in

Track record

Industrial AI that delivers where the work happens.

Practical industrial AI connects approved knowledge with frontline evidence, guides the connected worker through the task, then writes back structured outputs the business can reuse.

Technician using a Blinkin AI assistant during an industrial site assessment
Use case layer

Digital site assessment and installed-base capture

A technician walkaround becomes asset hierarchy, nameplate extraction, checklist evidence and review prompts. The point is not more form filling. It is better field data from the same visit.

Asset hierarchy Nameplate extraction Human review
Heating system pipework and service equipment
Use case layer

Assistant hub for equipment service operations

Logs, inventory capture, work reports, voice notes and technical knowledge become one operational assistant layer for service teams that need speed and consistency in the field.

Equipment logs Inventory Work reports
Technician documenting an industrial control panel with a mobile device
Use case layer

Visual field-service workflows for technical teams

Photos, videos and technician inputs become structured asset knowledge, evidence-linked service documentation and checklist verification that can fit into existing service ecosystems.

Service reports Checklist verification Structured asset data

How Blinkin works

From scattered knowledge to guided frontline execution.

Industrial teams need fewer blank forms, fewer weak handovers and clearer service records. Each app connects approved content, captures reality, guides action, controls risk and writes back a reviewed result.

Evidence layer

Capture

Use chat, scan, voice, photo, video, documents and visible machine data as the live evidence layer.

App reads Chat, scan, voice, photo, video, documents and visible machine data.
Team gets A complete multimodal evidence layer with missing views visible before handover.
Evidence intake Capture gaps visible
Photos Voice notes Forms Logs

App patterns

Frontline micro-apps for the work at hand.

Different teams need different shapes: site intake, asset records, service reports, knowledge support and live troubleshooting. Each app can be shared by URL, QR or integration while the evidence layer stays consistent.

Site intake

Site Survey App

Used before a quote, retrofit or takeover. It maps rooms, equipment, missing views and follow-up questions from one site visit.

Asset record

Installed-Base Register

Used when existing equipment needs a clean record. It captures serials, nameplate fields, components, location and service status.

After the visit

Service Report Writer

Used once the work is done. It turns notes, photos, measurements and decisions into a report, handover and open action list.

When stuck

Technical Knowledge Assistant

Used to answer procedure, code or part questions against manuals, SOPs and expert notes, with a specialist summary when needed.

During diagnosis

Troubleshooting Companion

Used live in a fault case. It asks the next diagnostic question, narrows likely causes and records the path taken for the case file.

Industrial plant pipework and process equipment

Built for professionals

AI that respects the expert's job.

Industrial users do not need another abstract chat window. They need a connected-worker app that understands the object in front of them, the procedure they are following and the output the organization needs after the job is done.

Evidence stays attached to the answer.
AI-first, hybrid and expert-first modes fit the risk.
Outputs fit the workflow, not the other way around.
The professional remains the decision maker.

Pilot shape

Your first AI app starts with one workflow that matters.

The pilot should stay narrow: one service, inspection, installed-base or documentation workflow with high visual complexity and measurable friction. In 30 to 90 days, Blinkin can turn it into a branded connected-worker app and measure before-and-after value.