About us

A serious engineering firm, built from applied research and German industrial projects

AcousticAI Lab is an industrial AI engineering and research firm. We build sensing-based AI systems for factories and critical assets, together with our industrial partner NeuroControls GmbH, and we build them with the client's engineers rather than selling a generic product.

Who we are

Engineering rigour from Germany, availability in India's time zone

We build multi-modal sensor units (vision, audio from audible to ultrasonic, vibration, lidar, environmental and gas sensors), energy-efficient edge AI that runs on the machine, and sovereign AI setups where data never leaves the plant, including federated learning across sites.

Our methods are peer-reviewed and our experience comes from projects with German SMEs, automotive companies, battery manufacturers, technical universities and leading research institutes. In 2026 we opened the practice to Indian industry, with remote delivery, on-site visits to client plants and working hours that overlap with the Indian day.

  • Co-development, not generic solutions: we work inside your process with your engineers
  • One accountable team for sensing hardware and AI, with NeuroControls GmbH
  • Sovereign by default: on-premise, on-device, no cloud dependency
  • Honest evaluation with a go / no-go gate before large spend
Industrial test setup with sensors and cabling
Since 2019Independent research and consulting; NeuroControls partnership since 2026
Precision machining on a CNC lathe
How the firm started

From applied research to the factory floor

The firm grew out of applied research in industrial sound and vibration analysis and from joint projects with German industry: automotive OEMs and suppliers, battery cell and module manufacturers, machine-building SMEs, technical universities and research institutes.

Those projects taught us one thing: general-purpose solutions rarely meet a company's real goal. Systems have to be developed with the company, on its process, under its constraints. In 2026 we joined forces with NeuroControls GmbH in Munich to co-develop multi-modal sensor units and edge AI hardware, and we are now opening the practice to Indian industry.

  1. 2019Independent research and consulting begins, alongside applied research in industrial acoustics
  2. 2021–2023Peer-reviewed work on partial discharge detection, acoustic traffic benchmarks and laser-weld monitoring
  3. 2026Partnership with NeuroControls GmbH; practice opened to Indian manufacturing
Founder

Saichand Gourishetti

SGFounder photo to be added

Founder and Lead Engineer

Industrial acoustic, vibration and multi-modal sensor AI; edge machine learning.

Saichand leads AcousticAI Lab's engineering and research. He was formerly a Senior Scientific Researcher at Fraunhofer IDMT, working on industrial sound and vibration analysis, and is a PhD candidate at TU Ilmenau. His work spans acoustic monitoring of welding processes, partial discharge detection, open acoustic benchmark datasets and energy-efficient edge models. Consulting is performed independently of those affiliations.

Partners & credentials

Industrial sensing and hardware partner: NeuroControls GmbH

NeuroControls GmbH, Munich, co-develops and deploys the multi-modal sensor units and edge hardware with us. Together we deliver sensing hardware and AI as one accountable team, from pilot line to roll-out.

Project experience, shown as categories until written permission for names exists: German machine-building SMEs, automotive OEMs and suppliers, battery cell and module manufacturers, technical universities and leading research institutes. Professional liability insurance is maintained.

AcousticAI Lab in collaboration with NeuroControls GmbH
Publications

Peer-reviewed research behind the practice

Papers and datasets from the team's research. Full list with DOIs on Google Scholar and ORCID.

Acoustic monitoring of joint-gap formation in laser beam butt weldingCrystals, 2023 · Airborne acoustic emission, STFT features, neural network classifier under process variability
Partial discharge detection using deep neural networks with airborne acoustic emission2021 · Time-frequency representations, DNN detection and classification for continuous HV asset monitoring
IDMT-Traffic: an open benchmark dataset for acoustic traffic monitoring researchEUSIPCO 2021 · Co-author · Evaluation splits, baseline protocol, microphone-mismatch robustness
Acoustic quality control in food processing: corn extrusionDAGA 2022 · Acoustic characterisation of extrusion under process changes
Further peer-reviewed work on industrial sound and vibration analysis, representations and edge ML13+ publications in total · See Google Scholar and ORCID for the complete list with DOIs

Want to know whether our methods fit your problem?

Book a free discovery call. We will look at your process and your data and give you a straight answer, including no-go where the physics says so.