AI research built for industry.

AI & machine learning R&D

We research AI and machine learning for industrial problems and build what the research supports. Our own AI is in development.

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Our approach

The people who research it also build it.

Because research and engineering work side by side, every recommendation we make is one we are equipped to deliver.

We test ideas on industrial problems and build only what the results support.

Our own AI is in development, so research and client projects can start from the same base.

Our internal apps run on machine learning too, so we use what we build.

What we do

Four areas of work.

  1. Applied research

    Testing AI and machine learning approaches on industrial problems.

  2. Solutions for industry

    Building models and running them inside our clients’ operations.

  3. Neural AI Project

    Our own AI, for our research and our clients’ projects.

  4. Internal apps

    Apps we develop in-house that run on machine learning.

How we work

From open question to deployed system.

  1. Frame

    We turn the problem into something measurable and check what data you already have.

  2. Research

    We try several approaches in controlled experiments and show you every result, including the ones that failed.

  3. Build

    We build the best-performing approach into a tested, documented system.

  4. Deploy & evolve

    We install it in your environment and keep tuning it as your data changes.

Research

What we are building.

Neural AI Project
Our own AI, built in-house and still in development. Research and client projects will start from the same base.
Internal apps
Tools we build for our own work and run on machine learning. We use them ourselves before anything reaches a client.
AI/ML neural solutions
Neural models trained on your data and tested in your operation, from the first experiment to production.
Experiment lab
Where we test ideas before they reach a client. Every run is logged, so any result can be repeated and checked.
Industrial data tooling
Tools to clean, label and organize messy operational data before a model sees it.
Open results
We report what worked and what didn’t, so you can decide from the facts.

Our focus

Where mistakes are expensive.

We work on industrial problems, where mistakes are expensive, data is messy and a model has to prove itself to the people running the operation. These are the areas where we work and test our approaches.

Sensor data
Drift, anomalies and early signs of failure in sensor, machine and controller readings, before they cause downtime.
Images and video
Inspection images from the line, to find defects, count items and check quality on every shift.
Documents and logs
Maintenance logs, reports and scanned forms, turned into structured data your team can search.
Proof on your data
We test on your own data first, against a simple baseline and on data the model has never seen. You get a report that says where it works and where it fails.

Impact

What Neuralquest can do for your company.

  1. We study the problem where it happens, in your operation.

  2. We build the solution and install it in your company.

  3. We bring the AI we are developing ourselves.