Industrial AI Products & Accelerators

Put proven industrial AI to work on the repetitive review, monitoring and searching that slows your teams down.

These products and accelerators are already built. NeoBram configures them around your equipment, data, documents and rules, so the first deployment can move faster than a custom build, and your people keep every decision that matters.

Fewer hours on manual review and searching
Earlier warning of events and risks
People approve every consequential decision
Runs privately, on-prem, at the edge or offline

Discuss a first deployment See NeoVision

Industrial plant floor with equipment monitored through an AI asset-intelligence view

Proven foundation first, then configured around your data, equipment, documents and rules.

Direct answer

NeoBram's industrial AI products and accelerators help plants and engineering teams cut the hours spent on manual review, monitoring and searching, and find events and risks earlier. NeoVision turns existing CCTV into safety, quality and process alerts; NeoAssetHorizon finds component lifecycle and supply risks in BOMs and installed bases; Tender and Procurement Intelligence extract requirements and compare documents; Industrial Knowledge Systems answer from your own procedures; Reliability Intelligence prioritises equipment attention. Each is configured for the customer's environment, not sold as one-size-fits-all SaaS, and people keep every consequential decision.

Products and accelerators

What your teams can do differently.

Each product is described the way a buyer thinks about it: the problem, the manual work today, what it costs, what changes, what you receive, what stays under human control, how it deploys, and only then the AI behind it.

Industrial vision

NeoVision

See safety, quality and process events as they happen, without someone watching screens all day.

The problem

Safety and quality events on a plant floor are found late or not at all, because nobody can review every camera or every pack in real time.

Manual work today

Repetitive CCTV review, spot checks at the line, headcounts by hand, incident investigation from partial footage.

What it costs

Missed events, slow response, repetitive supervisor time and weak evidence when something goes wrong.

How the work changes

Before: Someone reviews footage after the fact, or an event is never noticed.

After: Cameras stream locally → configured safety, quality and vehicle events are flagged → timestamped evidence is routed to the right person → they decide.

What you get

Real-time alerts for configured safety and process events
People, goods and vehicle counts and events
Timestamped evidence clips and notifications
Packaging, label and defect flags for review

Human control: People decide on every flagged event; the system alerts and records, it does not enforce.
Deployment: Runs locally on your site at the edge or on-premises using existing CCTV where coverage allows.
AI inside: Computer vision models configured for your cameras, zones, products and event definitions.

NeoVision overview Industrial vision guide Food and beverage hub

Asset and product lifecycle intelligence

NeoAssetHorizon

Stop searching through hundreds of lifecycle notices and BOM lines to find what needs engineering attention.

The problem

Long-lifecycle equipment and products depend on components whose end-of-life, end-of-support, vulnerability and supply-risk signals are scattered across vendor portals, PDFs and emails.

Manual work today

Engineers search multiple portals and datasheets, compare BOM lines by hand and chase suppliers by email.

What it costs

Engineering hours lost to searching, late discovery of obsolescence, unplanned redesign and emergency procurement.

How the work changes

Before: An engineer searches portals and PDFs component by component.

After: Upload the BOM or installed base → lifecycle, support, vulnerability and supply risks are flagged → evidence is shown → the engineer reviews and decides.

What you get

Prioritised review list by component and asset
End-of-life, end-of-support and obsolescence flags
Replacement-part and spare-part candidates
Source evidence with confidence and last-checked dates

Human control: Engineers approve every replacement or design decision; the system proposes and evidences.
Deployment: Private cloud or on-premises, connected to your BOM, installed-base and approved supplier sources.
AI inside: Document understanding, language models and structured data matching behind the workflow.

NeoAssetHorizon overview Spare-parts and obsolescence engagement brief Oil and gas hub

Bid and requirement workflows

Tender Intelligence

Spend less time reading tender documents and more time deciding which bids to win.

The problem

Tender packages arrive as hundreds of pages plus addenda; requirements are split across documents and easy to miss.

Manual work today

Bid teams read every document, build requirement registers in spreadsheets and compare against past responses by memory.

What it costs

Bid-team hours, missed requirements, late qualification decisions and rushed responses.

How the work changes

Before: The team reads the whole package and builds the register by hand.

After: Upload the tender → requirements, deadlines and compliance items are extracted → evidence and past responses are retrieved → the bid team reviews and decides.

What you get

Requirement and compliance register with source references
Qualification and bid or no-bid summary
Document comparison across addenda
Draft response sections for review

Human control: Bid managers and engineers approve every requirement interpretation and every response.
Deployment: Private cloud or on-premises, configured to your templates, response library and document systems.
AI inside: Document understanding, language models and retrieval over your approved library.

AI-assisted tender management brief Requirements evidence review brief EPC and industrial engineering hub

Procurement automation

Procurement Intelligence

Spend less time reading quotations and checking the same technical requirements.

The problem

Every RFQ cycle means comparing supplier quotations and technical documents against specifications, line by line.

Manual work today

Procurement and engineering teams check quotations, datasheets and compliance statements manually and chase missing items by email.

What it costs

Procurement and engineering hours, slow award decisions, missed exceptions and specification mismatches found late.

How the work changes

Before: Each quotation is read and compared against the specification by hand.

After: Load the RFQ and quotations → requirements are extracted and supplier responses compared → exceptions are flagged → procurement and engineering review.

What you get

Quotation comparison against specification
Technical compliance and exception list
Material and part matches
Purchase-document extraction for your systems

Human control: Procurement and engineering teams make every award and compliance decision.
Deployment: Private cloud or on-premises, connected to your ERP or procurement system interfaces where approved.
AI inside: Document understanding, language models and structured comparison behind the workflow.

AI-assisted quotations brief Document and workflow automation guide

Plant and engineering knowledge

Industrial Knowledge Systems

Make your company's technical knowledge available in seconds, without sending sensitive information outside your environment.

The problem

Procedures, manuals, drawings and past incidents exist, but the people who need them cannot find the right version quickly, and experienced staff are retiring.

Manual work today

Searching folders and paper binders, asking the one person who knows, reading whole manuals to find one step.

What it costs

Lost operator and engineer time, inconsistent answers, slower troubleshooting and knowledge that leaves with people.

How the work changes

Before: An operator searches binders or waits for the expert.

After: Ask in plain language → the approved procedure or record is retrieved → the answer is shown with its source → the person acts or escalates.

What you get

Answers with the controlled source and version shown
SOP and work-instruction assistants
Troubleshooting and maintenance knowledge
Escalation when evidence is missing

Human control: People follow the source, not the summary; the system declines when evidence is insufficient.
Deployment: Fully offline, on-premises or private cloud, inside your permissions.
AI inside: Controlled retrieval, language models and, where useful, a company-specific model adapted to your terminology.

Knowledge systems guide Factory-floor knowledge assistant Industry-floor assistant brief

Asset health and maintenance prioritisation

Reliability and Predictive Intelligence

Know which equipment needs attention before the next costly interruption.

The problem

Maintenance teams cannot watch every asset; failures still surprise the plant and planned work competes with firefighting.

Manual work today

Reviewing historian trends by hand, periodic inspections regardless of condition, alarm lists nobody has time to analyse.

What it costs

Unplanned downtime exposure, reactive maintenance, unnecessary inspections and spare parts ordered too late.

How the work changes

Before: Trends are reviewed occasionally and failures are found when they happen.

After: Operating data, maintenance history and equipment behaviour are combined → assets needing attention are prioritised → maintenance reviews and plans the intervention.

What you get

Prioritised asset attention list
Asset-health scores and condition alerts
Anomaly and trend explanations
Work-order recommendations for your CMMS

Human control: Maintenance planners decide what is inspected and when; alerts prioritise, they do not act.
Deployment: On-premises, edge or private cloud, connected to historians, sensors and CMMS or EAM systems.
AI inside: Machine learning and predictive models configured for your assets, failure modes and operating regimes.

Predictive maintenance for manufacturing Predictive AI guide Predictive maintenance ROI estimate

Delivery time

Already built, configured for your plant.

Data

Equipment

Process

Documents

Systems

Network boundary

Workflows

Acceptance criteria

Operating rules

Each product is configured around these nine things for every customer. NeoBram does not install one product and expect it to behave identically in every factory.

Already built

What NeoBram brings

Working products and accelerators, not a blank page
Reference architectures, pipelines and integration patterns
Evaluation methods, acceptance templates and monitoring
Deployment options for cloud, private cloud, on-prem, edge and offline
Documentation, runbooks and capability transfer

Configured with you

What stays yours

Domain rules, exceptions and acceptance criteria from your experts
Data, equipment, document and system interfaces you approve
Permissions, human-approval gates and operating boundaries
Ownership terms for configurations, workflows, adapters and artefacts, within third-party licences

Direct answers

Questions buyers ask about products and accelerators.

Are these off-the-shelf SaaS products?+

No. Each is a proven engineering foundation that NeoBram configures and integrates around your data, equipment, processes, documents, systems, network boundary, workflows, acceptance criteria and operating rules. Deployment is customer-specific and can be on-premises, at the edge, fully offline or in a private cloud.

Will one product work identically in every factory?+

No, and it should not. Cameras, lines, asset hierarchies, document corpora and approval rules differ between sites. NeoBram brings the proven foundation, then configures and validates it against your environment and acceptance criteria.

How quickly can a product be deployed?+

Delivery time depends on the use case, available data, integrations and validation requirements. Where NeoBram already has a reusable product or accelerator, the first deployment can often move significantly faster than a custom build. Because NeoVision is built on a reusable industrial vision platform, deployments can often move significantly faster than a fully custom computer-vision project. Final timing depends on camera readiness, use cases, integrations, hardware and site conditions. For the other products the work is mostly configuration, data or document connection, acceptance checks and rollout, and the schedule is agreed per site.

What does the customer own after deployment?+

Customer-specific assets such as configurations, prompts, workflows, integration code, indexes, runbooks, fine-tuned adapters and customer-trained artefacts can be transferred where contractual and third-party licensing terms allow. Reusable NeoBram foundations and third-party base models remain subject to their applicable licences.

Who provides the domain expertise?+

You do. Your engineers, quality, maintenance, procurement and operations experts define process truth, rules, exceptions and acceptance criteria. NeoBram provides the AI engineering, integration, evaluation and production assurance around them.

Can a partner deliver these to its own customers?+

Yes. Industrial OEMs, automation companies, system integrators, EPC and engineering firms and industrial software companies keep the customer relationship and industrial scope while NeoBram provides the AI engineering behind the solution.

Bring one workflow

Start with the manual work that costs your team the most time.

We will look at what your people do today, what it costs in hours and exposure, and which product or accelerator changes it first.

Discuss a first deployment