Solution

Industry AI Pack

Industry AI packages on top of the RESTART AI Enterprise Platform: ready-made scripts, data templates and agents for industry, oil and gas, energy, mining, metrology, MRO, HSE, production and quality.

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Product positioning

Industry AI Pack is needed where universal AI does not sufficiently understand the industry context: shift logs, MRO, HSE, metrology, production deviations, quality, operational regulations, industrial data and access restrictions.

RESTART’s product idea is not to sell “AI in general”, but to deliver industry packages on top of a single platform core. This shortens the path from pilot to useful scenario: there are standard agents, integration templates, industry dictionaries and a process map.

Benefits for the client

Faster to the pilot

No need to start from scratch: scenarios, roles, sources and templates are already described as an industry package.

Link AI to manufacturing

The module does not work separately from processes, but around ERP, EAM, MES, logs, regulations and industrial data.

Reduce operational risks

AI helps look for anomalies, repeatable problems, HSE requirements, repair history and quality documents.

Scale by site

After the first scenario, you can connect new divisions, plants, sources and roles on the same platform core.

Industry Pack Scenarios

Maintenance

MRO and operation

Search by repair history, regulations, applications, failures, instructions and diagnostic recommendations.

HSE

Occupational health and safety

Answers on regulations, incidents, checklists, training and safety requirements.

Shift logs

Replaceable magazines

Summarization of events, search for recurring deviations, preparation of shift handover and control of orders.

Quality

Production and quality

Analysis of inconsistencies, protocols, parameters, comments, corrective actions and causes of deviations.

Integrations

environmentExamples of sources
ERP / EAM1C, SAP, repair accounting, applications, materials, equipment, documents and financial data.
MES/productionProduction events, shift reports, batches, parameters, deviations, quality.
Process control systems and industrial dataHistorical data, references, measurements and process context for the agreed loop.
Documents and regulationsInstructions, HSE, metrology, equipment data sheets, protocols, standards and knowledge base.

How we implement it

Step 1

Discovery

We fix the business process, data sources, user roles, information security restrictions, benefit criteria and the first scenario.

Step 2

MVP

We launch the working module in a limited loop, connect data, roles, logs, interface and quality control.

Step 3

Pilot

We test the effect on real users, set up rules, finalize integrations and prepare for operation.

Step 4

Scale

We expand the module to new units, sources, roles and scenarios without breaking the platform core.

Industry control

Industrial and critical processes require careful boundaries of responsibility. AI helps to search, explain and prepare tips, but does not replace approved technological regulations, responsible specialists and industrial safety requirements.

Data under control

Sources, permissions, logs, and restrictions are fixed at the architecture level rather than added after launch.

Integrations

Modules connect to ERP, 1C, SAP, DWH, EDMS, Service Desk, GitLab, Jira, Confluence, portals and internal APIs.

Verifiability

Answers and actions should be explainable: sources, versions, logs, processing statuses and the responsible owner of the process.

Scaling

Each of the following scenarios uses the platform core: roles, models, RAGs, logs, connectors, and security rules.

Infrastructure for industry AI packages

Industry AI scenarios for industry, energy, metrology, telecom or public sector require different loads, sources and restrictions. AI Compute allows you to assemble a manageable environment for a specific industry and scale it by roles, sites and modules.

Frequently asked questions

Can I start with one workshop or site?

Yes. Typically, a pilot is limited to a single process, site, data type, and user group.

Do you need to connect the automated process control system right away?

Not necessarily. They often start with documents, logs, EAM/ERP and historical data, and the industrial environment is connected using a separate architecture.

Can we make an industry package to suit our specific needs?

Yes. The package is adapted to the industry, terminology, sources, regulations and customer roles.

Enterprise product packaging

Industry AI Pack is delivered as a RESTART AI Enterprise Platform module: with a clear area of ​​responsibility, business process owner, data model, integrations, roles, logs, pilot criteria and industrial launch plan. This is important for CIOs and CISOs: the module does not live separately from the corporate architecture, but is integrated into the IT landscape, security, operations and change management.

Business effect

Success criteria are formulated before the pilot: time, quality, reduction of manual workload, speed of response, completeness of data or controllability of the process.

Integrations

The module connects to customer systems: ERP, 1C, SAP, BI, DWH, EDMS, Service Desk, Git, portal, mail, documents and internal APIs.

Information security and compliance

The separation of roles, sources, loops, logs, and data is considered at the architectural level rather than added after launch.

Scaling

After the first successful scenario, the module can be expanded to new departments, documents, processes, users and regions.

How to show value per pilot

1

Select one process

Don’t try to automate everything at once: choose a process with an understandable pain, an owner and a measurable result.

2

Connect data

Collect a limited but real set of documents, applications, reports, code, regulations or historical requests.

3

Check with users

Conduct a pilot on working scenarios, collect feedback, adjust the quality of answers and control of controversial cases.

4

Design an production environment

Fix the architecture, roles, regulations, SLA, monitoring, support and development roadmap.

Let's discuss your environment

Describe the task, current systems, constraints, and expected results. We will offer a practical first step: diagnostics, pilot, audit, roadmap or project team.

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