NeoTek Solutions builds AI for manufacturing and automotive suppliers, from predictive maintenance and computer-vision quality inspection to SOP knowledge assistants and demand forecasting. We work with plants, parts suppliers and smaller shops across Middle Tennessee and the US, sizing each project to your operation and the systems you already run. Maintenance planners, inspectors and safety leaders make every decision, and we build within your quality system.

We build in one of the country’s major automotive and manufacturing regions. Assembly plants in Smyrna and Spring Hill anchor a broad network of parts suppliers, metal shops and logistics providers.


The Pressures Manufacturers Face

The plants and suppliers we work with run under tight delivery schedules and strict quality demands, where unplanned downtime ripples through a customer’s line. Skilled technicians are hard to hire, and experienced workers retire with knowledge that was never written down.

Paperwork adds friction too, as purchase orders, shipping notices, certificates and change requests arrive in many formats and demand shifts with customer schedules. Most of the data needed to fix this already sits in your machines, historians, ERP and quality systems, so we start by connecting it.


How Can AI Help Manufacturers?

Predictive Maintenance

Problem Equipment fails without warning, or parts get replaced on a calendar whether needed or not.

What AI does We build machine learning models that watch sensor, vibration and maintenance data for the patterns that come before failures.

Human in the loop We route alerts to your maintenance planners, who inspect the equipment and decide when to schedule work.

Computer-Vision Quality Inspection

Problem Manual visual inspection is tiring, inconsistent and hard to staff on every shift.

What AI does We build computer vision, meaning AI that analyzes camera images, to flag possible defects on parts or assemblies in real time.

Human in the loop We route flagged parts to your quality inspectors, and we feed their decisions back to retrain the model.

Supplier and Purchase-Order Document Processing

Problem Buyers and clerks re-key purchase orders, shipping notices and certificates into ERP.

What AI does We build document AI that extracts part numbers, quantities, dates and terms, then checks them against open orders.

Human in the loop We route mismatches and low-confidence fields to your staff before any record posts.

Maintenance and SOP Knowledge Assistants

Problem Technicians lose time searching manuals, work instructions and past work orders.

What AI does We build retrieval-augmented generation (RAG), which grounds answers in your approved documents, to answer questions in plain language and cite the source page.

Human in the loop We ground it in your approved procedures, so technicians follow them and your engineers own the content and fix gaps. Learn more about RAG maintenance and SOP assistants.

Demand and Inventory Forecasting

Problem Customer releases change often, leaving too much stock of some parts and shortages of others.

What AI does We build forecasting models that combine order history, customer schedules and lead times to project demand and suggest reorder points.

Human in the loop We leave purchasing with your planners, who adjust forecasts using what they know.

Safety Incident Analysis

Problem Near-miss and incident reports pile up as free text, and patterns go unnoticed.

What AI does We build on a large language model (LLM), an AI model that reads and writes text, to group reports by cause, location and equipment.

Human in the loop We put the patterns in front of your safety leaders, who investigate root causes and decide on corrective actions.


Data, Security and Operational Considerations

We build manufacturing AI to respect both your IT security and the realities of the plant floor:

  • OT and IT separationWe design data flows that respect network segmentation between operational technology and business systems.
  • Data readinessSensor, historian and quality data often needs cleaning and labeling before models are useful. We plan for that work up front.
  • Edge or cloudVision and maintenance models can run at the edge, on-premises or in Azure, AWS or Google Cloud.
  • Customer requirementsSuppliers often must meet customer quality and data handling rules. We work within your quality system and those requirements.
  • Intellectual propertyDrawings, process data and pricing stay in your controlled environment. Your data is never used to train public models.

We do not provide legal or regulatory advice. Safety decisions always stay with qualified people. See AI governance, security and compliance for how we set up controls and oversight.


How Can NeoTek Solutions Help Your Plant?

Your planners, inspectors and engineers know which failures and which paperwork cost the most. We build the tools that address them and connect those tools to the systems already on your floor.

  • Work we deliverPredictive maintenance models, computer-vision inspection, supplier and purchase-order document processing, SOP and maintenance assistants, demand forecasting and safety incident analysis.
  • Built on your systemsWe integrate with your ERP, MES, historians and quality systems through the interfaces, databases and exports they support, respecting your OT and IT segmentation.
  • Built for your customer requirementsWe work inside your quality system and your customers’ data handling rules, and your drawings, process data and pricing stay in your controlled environment.
  • How we workShort cycles with AI-assisted delivery and human review, with success criteria agreed early, so you see one station or one line working before we widen the scope.
  • Skills on the teamAI and machine learning engineers, data engineers, cloud and security specialists and QA in one team, able to run models at the edge or in your cloud tenant.
  • What makes us differentStrategy, build and staffing come from one team, so we hand the finished line to your engineers or keep ours working alongside them.

Safety decisions always stay with qualified people on your side. Book a free AI consultation to talk through one machine, line or document flow.


How Do Manufacturers Start With AI?

  1. Assessment

    We walk your processes, review data sources and talk to operators, planners and engineers. Then we rank use cases.

  2. Focused proof of concept

    We test one use case, such as vision inspection on a single station, with real parts and data.

  3. Production

    We harden the solution, connect it to your systems, add monitoring and train your team. Then we expand to more lines.


Related Services


Frequently Asked Questions

Will you need new sensors for predictive maintenance?

Often not. We first use what your PLCs, historians and maintenance systems already collect, and the assessment tells you whether that data is enough or where a few added sensors would help.

Will the vision system you build replace our quality inspectors?

No. We build vision to flag likely defects so your inspectors focus their attention, and we feed their confirmations back into the model so it improves on your parts.

Can you work with our ERP and MES systems?

Usually, yes. We integrate through the interfaces, databases or exports your systems support, and we confirm the options with your team before committing to a design.

Do you only work with large plants?

No. We scope focused projects for smaller suppliers, such as purchase-order processing or an SOP assistant, and we size the work to your operation and budget.

Where does our production data go?

We keep your data in environments you control, whether on-premises, at the edge or in your cloud tenant. You own what we build, and we never let your data train public models.


Put AI to Work on Your Plant Floor

Find out which use cases fit your plant, your data and your customers’ requirements. Take the free AI readiness assessment or book a free AI consultation.