Works on your existing cameras
Standard IP / CCTV feeds, RTSP or NVR. No rip-and-replace, no new capex cycle to trigger a first deployment.
Custom industrial AI, 50+ engineers
Operational AI systems for heavy industry.
We build AI systems for the real conditions of mines, ports, terminals and plants: computer vision, predictive maintenance, forecasting. From evaluation to production in weeks.
Studio23: Production monitoring
LiveQuality control: Line 3
1 247
parts/h
3
defects
99.8 %
pass
99.8 %
Porosity ×2Scratch ×1
Predictive maintenance
Pump P-04D+18
Compressor C-02OK
Conveyor K-07OK
Pump P-04: work order created in SAP PM
Document intelligence
autoCert. EN 10204 3.13.1 s
autoPPAP: Part 447B4.8 s
reviewInvoice FRS-2024-88122.3 s
200+
active systems
99.1 %
vision accuracy
Trusted by
Computer vision on your existing CCTV
Turn your existing cameras into real-time safety and operations data.
No new hardware. We build on the cameras already installed across your site and turn each feed into live signals your HSE and operations teams can act on.
On-prem or edge, your data stays on site
Inference runs next to the cameras or in your own infrastructure, air-gapped if needed. Footage never has to leave the site.
Live in weeks, built around your site
We start from your camera layout and operating reality, not a generic template. First value on a defined perimeter in weeks, not capex cycles.
Safety
Prevent incidents before they happen
Continuous monitoring of the situations that drive HSE risk on open industrial sites.
- Vehicle-pedestrian proximity and collision risk near heavy equipment
- PPE compliance (helmet, high-vis, harness) at defined checkpoints
- Exclusion and no-go zone breaches, in real time
Operations
Measure what actually moves your throughput
The same feeds turned into operational metrics your teams can steer on.
- Truck movements, queueing and cycle-time measurement
- Stockpile and inventory volume estimation from camera views
- Bottleneck and dwell-time detection across the flow
Capabilities shown reflect deployed computer-vision work. Site-specific KPIs are scoped and validated with your teams before any figure is committed.
Areas of expertise
Focused domains, one constraint: real production.
Every system is built for the real site environment: real-time constraints, industrial system integration, continuous production monitoring.
Industrial vision
Defect detection, dimensional control, assembly inspection, plus safety and operations analytics on existing CCTV. Sub-200 ms inference, PLC integration.
CNNEdge AIOPC-UA
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Predictive maintenance
Anomaly detection and RUL on sensor time series. Historian and CMMS integration for automatic work-order triggering.
Time seriesLSTMCMMS
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Document intelligence
Structured extraction from technical documents, certificates, compliance files. OCR + LLM pipeline into the ERP.
OCRLLMERP
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Forecasting & supply chain
Demand forecasting and inventory optimization across thousands of SKUs. Output into ERP/WMS.
TFTLightGBMSAP
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Automation & MLOps
AI agents, workflow orchestration, ML CI/CD. Cloud and edge deployment, production monitoring.
MLOpsAgentsK8s
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Our team
50+
AI, data and MLOps engineers
Vision, time series, NLP, MLOps, edge and cloud deployment. Specialists, not generalists.
Industrial AI deployed in production
200+
AI systems live in production
21+
countries of deployment
8–14 months
average observed payback
Fixed PoC
signed KPIs, no commitment beyond
Case studies
Measured deployments, not demos.
Case studies from production projects: field constraints, deployed architectures, observed KPIs.
Mines · Ports · TerminalsIndustrial vision
Safety and operations analytics on existing CCTV
Heavy-industry sites already run hundreds of cameras, but the footage is only watched after an incident. Near-misses, PPE breaches and exclusion-zone intrusions go unseen, and operational metrics are still logged by hand.
Results
A single vision layer over existing CCTV: live proximity and zone alerts for safety, automated cycle-time and stockpile tracking for operations, deployed without replacing a single camera.
Read the study
Assembly: JapanIndustrial vision
AI vision pallet verification at end of line
Manual layer-by-layer counting with no second check and no image evidence. Sessions interrupted between shifts, errors discovered only after shipment.
Results
Shipping errors virtually eliminated, 100% traceability by pallet, operator and timestamp.
Read the study
SemiconductorsIndustrial vision
Fully on-prem visual inspection of wafers
Manual visual QC as the bottleneck. Repeated GPU batch attempts failing (OOM). Zero operator traceability.
Results
Inspection throughput ×2.3, batch cycle ~3.2 min (vs 7+ min), and no more GPU OOM errors.
Read the study
FMCG: national distributionForecasting & supply chain
AI stock-redistribution agent connected to the ERP
Expired product on one side, stockouts on the other. Manual planning took 2 to 5 days to reach a decision: by then the expiry window was already closed.
Results
−31% expiry write-offs, +7.3% sales in underserved territories, decisions in under an hour.
Read the study
The problem
AI creates value in production, not in demos.
Companies don't need one more tool. They need reliable systems, integrated into daily workflows, able to execute the right actions at the right time.
A demanding industrial environment
Vibration, short cycles, noisy sensor data, real-time constraints, ATEX zones, open sites. AI models work in the lab. Production systems are a different problem.
Heterogeneous systems to integrate
SCADA, MES, ERP, historian, CMMS, VMS/CCTV: every site has its own stack. Our systems plug into existing infrastructure (OPC-UA, REST, Profinet, RTSP) without rebuilding it.
From POC to production
A convincing prototype does not automatically make it to production. We handle MLOps, drift monitoring, retraining and availability SLAs from day one.
The Studio23 solution
An AI studio built around integration, not endless experimentation.
We start from your operations, not a technology looking for a home. Every system is designed to do a precise job, with clear rules, reliable connections and a simple experience for your teams.
Field audit
Assessment of equipment, available data, cameras, systems in place and deployment constraints. Identification of the priority use case.
Architecture & prototype
Stack selection, data acquisition or preparation, first testable model on a defined perimeter with real data.
Production integration
Connection to equipment and systems (OPC-UA, REST, Profinet, RTSP), operator interface, load testing and validation in real conditions.
MLOps & monitoring
Model CI/CD pipeline, drift monitoring, scheduled retraining, availability SLAs and knowledge transfer.
Method
A scoped, progressive, measurable rollout.
The goal isn't to automate everything at once. We start with a clear perimeter, validate the use, then scale what works.
01
Evaluation
Mapping of data, equipment, cameras and systems. Identification of the priority use case and estimate of achievable ROI.
02
Architecture
Definition of the technical stack, integration scope and deployment plan. Prototype on real data.
03
Build & integration
System development, connection to equipment and systems, validation testing in production conditions.
04
Deployment & MLOps
Go-live, performance monitoring, scheduled retraining and handover to your teams.
Why Studio23
A serious approach for companies that want concrete results.
Studio23 combines operational strategy, product design and technical integration to build systems that are useful, controllable and adopted by teams.
50+ engineers across AI, data, MLOps and industrial vision
Built for the field: vibration, short cycles, open sites, real-time constraints
Full-stack: data → model → deployment → continuous monitoring
Edge and cloud: deployed to your latency and data-sovereignty constraints
Industrial integration: OPC-UA, Profinet, MES, SCADA, ERP, CMMS, CCTV/VMS
From evaluation to production in weeks, not quarters
Contact
An industrial AI project to scope?
Tell us about the process, equipment, camera network or document flow to address. We will reply with a first feasibility analysis and an order of magnitude within 48 business hours.
Book a technical call