Services

Industrial AI services, co-developed with your engineers

Eight ways to work with us, from a two-day feasibility study to a deployed multi-modal sensing and edge AI system. No packages, no generic product: an engagement ladder where every rung has a fixed scope and a clear output. Prices on enquiry.

Co-Development R&D Multi-Modal Sensing Sovereign AI Energy-Efficient Edge AI Deployment Expert Consultation Feasibility Study Industrial-Grade Dataset Creation Training How we work

PoC 2–8 weeks · R&D 3–12 months

Co-Development R&D & Proof of Concept

Applied R&D done together with your engineers, on your process, with a measurable target agreed up front.

What is included

Joint problem definition and success metrics; measurement plan; dataset engineering (label specification, QA, versioning); representation and model design; evaluation under realistic operating conditions with strong baselines; error analysis; production plan. Suitable for internal R&D budgets, publicly funded projects and university collaborations.

Who it is forLarge manufacturers and industrial SMEs with an R&D budget and a concrete problem: condition monitoring, process and weld monitoring, acoustic or visual quality control, electrical asset monitoring.

What you getA validated prototype with measured performance on your data, a reusable dataset you own, and a defensible decision on production investment.

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Pilot line first, then roll-out

Multi-Modal Sensing + Edge AI Systems

Co-developed sensor units and on-device AI with NeuroControls GmbH: vision, audio (audible to ultrasonic), vibration, lidar, environmental and gas sensing in one platform.

What is included

Sensor selection, placement and synchronisation across modalities; ruggedised sensor units and data acquisition from NeuroControls GmbH; sensor-fusion models; inference on the edge device; alerts and dashboards; integration with PLC, SCADA or MES; handover to your OT/IT team. Delivered as a pilot line first, then roll-out.

Who it is forPlants that want a deployed monitoring or inspection system, not a study: automotive and auto-component, battery manufacturing, power and heavy electrical, process industries, pharma, food and FMCG.

What you getOne accountable team for hardware and AI; shorter time from idea to a running pilot; hardware proven in German industrial projects.

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Architecture to compliance sign-off

Sovereign AI & Federated Learning

AI that stays on your premises: on-device and on-premise deployment, and federated learning across plants without moving raw data.

What is included

Architecture for on-premise or on-device training and inference with no cloud dependency; data governance and access design; federated learning across sites or partner companies (secure aggregation, model versioning, monitoring); open-weight models and open tooling where possible so you are not locked to a vendor; documentation for IT security and compliance reviews.

Who it is forMulti-plant manufacturers, conglomerates, public-sector and defence-adjacent industry, and any company whose process data must not leave the site.

What you getFull ownership of data, models and infrastructure; models that learn from all sites without centralising sensitive data; reduced vendor and cloud dependency.

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From one device to a fleet

Energy-Efficient Edge AI Deployment

Models sized for the hardware and the site's power budget: quantisation, pruning, efficient architectures, real-time on embedded devices.

What is included

Hardware selection (microcontroller, embedded GPU, NPU); model compression and quantisation; latency and memory profiling; test harness and hardware-in-the-loop validation; monitoring and drift strategy; MLOps for fleets of edge devices.

Who it is forCompanies deploying AI on many machines or in sites with constrained power, connectivity or IT infrastructure.

What you getLower unit cost per deployment, real-time response without cloud round-trips, lower energy use, scalable roll-out.

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Per day or monthly retainer

Expert Consultation & Advisory

Senior engineering time for teams that already have data scientists: architecture reviews, evaluation design, sensor choice, edge and sovereign deployment.

What is included

Typical work: reviewing a stuck project, designing evaluation and labelling protocols, choosing sensors and sampling rates, deciding what runs on the edge versus on-premise, preparing technical sections of funding proposals, mentoring engineers.

Who it is forHeads of data science, CTOs, R&D managers, digital transformation teams.

What you getFaster decisions, fewer dead ends, and a team that learns the methods instead of outsourcing them.

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2–10 days · fixed fee

Feasibility Study

The low-risk entry point: 2 to 10 days on your data or a short measurement campaign, fixed scope, fixed fee, honest go / no-go.

What is included

Signal inspection and time-frequency analysis; quick transparent baselines; a first learned model evaluated on held-out data; an assessment of sensor placement, edge hardware class, integration points and data governance. Delivered as a written report with evidence, a go / no-go recommendation and, if go, a scoped proof-of-concept proposal.

Who it is forAny plant with a concrete problem, a stalled pilot or a vendor solution that did not meet the goal.

What you getA data-backed answer in days: is the signature present in a signal you can afford to measure, and what would the next step cost?

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Campaign to documented dataset

Industrial-Grade Dataset Creation

Measurement campaigns, label specifications, quality assurance and versioning that turn recordings into an asset your team can train on for years.

What is included

Measurement planning across the process window; synchronised multi-modal acquisition; label specification written with your quality engineers; annotation QA and inter-annotator checks; metadata and versioning; documentation and handover. Optionally an internal benchmark with fixed splits and baselines.

Who it is forCompanies building in-house AI capability, R&D centres and universities that need a rigorous dataset before modelling.

What you getA reusable, documented dataset you own, independent of any vendor or model.

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Workshops and mentoring

Training & Capability Building

Hands-on training for in-house teams: industrial signal processing, dataset engineering, honest evaluation, edge deployment and sovereign architectures.

What is included

Workshops tailored to your engineers' level and your machines' data; paired work on a live project; evaluation and labelling protocols your team keeps; mentoring for data scientists moving into industrial sensing.

Who it is forR&D teams, digital transformation units and corporate innovation centres that want to run the methods themselves.

What you getA team that can specify, evaluate and maintain sensing-based AI without depending on outside vendors.

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How we work

The engagement ladder

You decide at every rung whether to climb the next one. An advisory retainer (per day or monthly) is available for companies with their own data team.

Step 1 · Free, 30–45 min

Discovery call

Bring the problem, the data you have and your constraints. We tell you whether sensing-based AI is the right tool, and which modality is likely to carry the signature.

Step 2 · 2–10 days · fixed fee

Feasibility study

On your existing data or a short measurement campaign. Signal analysis, quick baselines, a first model, an honest written go / no-go.

Step 3 · 2–8 weeks (PoC) · 3–12 months (R&D)

Co-development R&D or proof of concept

Milestone-based. Measurement plan, dataset engineering, model design, evaluation under realistic conditions, error analysis, production plan.

Step 4 · per project

Pilot line, then roll-out

Sensor units and edge AI on one line, integrated with PLC, SCADA or MES, handed over to your OT/IT team, then scaled across lines and sites.

What we always deliver

The dataset with its specification, the trained models, the evaluation report and the documentation. You own all of it.

What we never do

Invent performance numbers, move your raw data to a cloud you do not control, or lock you into our tooling.

How we work with India

Remote delivery with on-site visits for measurement and deployment. Calls 12:30–16:30 IST. NDAs standard. EUR invoicing from Germany.

Ready to find out if it works on your machines?

Start with a free 30 to 45 minute discovery call. Bring the problem, the data you have and your questions. We will tell you honestly whether sensing-based AI is the right tool and what the next step would cost in days, not months.

Book a discovery call Send an enquiry