Delvitech Secures Major Funding Round as AI-Native AOI Enters Its Next Phase
In an era where electronics manufacturing is under relentless pressure to be faster, more efficient, and faultless, Delvitech is emerging as a notable force in the Automated Optical Inspection (AOI) sector. The Swiss deep-tech company has recently closed a $40 million Series B funding round, a development that highlights both its accelerating growth and the industry’s shift toward data-driven, continuously learning inspection systems.
While Delvitech is gaining strong traction in electronics production, its technology is not limited to the electronics sector. The company’s AI-native inspection architecture has been designed from the outset to operate across multiple industries where complex assemblies, mixed materials, and high reliability demand advanced visual and dimensional verification.
The investment positions Delvitech to scale its platform globally at a moment when inspection technology is evolving from a static defect-detection step into a dynamic contributor to process intelligence across smart-factory environments, regardless of industry sector.
With the new capital, Delvitech plans significant international expansion, including a major push into India. The company intends to establish a manufacturing facility in Bengaluru by 2026, with a long-term goal of producing more than 200 AOI systems per month by 2030. This aggressive scaling strategy reflects rising global demand for inspection systems capable of supporting high-mix manufacturing, multi-material assemblies, multi-site coordination, and increasingly data-centric quality frameworks across sectors from automotive to industrial equipment to consumer goods.
Adaptive Intelligence as AOI Architecture
Central to Delvitech’s platform is a deep-learning model developed through an internal training and validation environment. Rather than relying on fixed rule sets or manually curated image libraries — long-standing constraints of traditional AOI — the system learns directly from production data. Each inspection cycle contributes to model refinement, improving classification confidence, reducing manual tuning, and aligning with the broader industry shift toward adaptive, continuously learning inspection architectures.
This design addresses a key pain point in AOI: the metrology burden of maintaining inspection programs as designs, geometries, and process parameters shift. Adaptive classification reduces dependency on operator expertise while maintaining tight detection thresholds — whether the product is a PCB, an automotive module, or a precision mechanical subassembly.
“We have developed an AI-native platform built on a future-proof neural network architecture. Our flexible and agnostic system can be applied across multiple markets and industries. Moreover, thanks to our proprietary predictive technology, we are paving the way to prevent errors rather than merely detecting them. Delvitech competes at the forefront of the high-tech industry, driven by a unique combination of cutting-edge innovation and vision,” explained Roberto Gatti, founder and CEO of Delvitech.
3D Measurement as a Core Modality — Up to Six Cameras and True 3D Inspection
At the heart of Delvitech’s platforms is its patented optical-head technology, combining up to six cameras, FPGA integration, and four digital projectors to deliver true 3D data. Powered by proprietary neural networks, the system adapts seamlessly to any surface, material, or height, capturing even the most challenging elements — reflective metals, shadowed zones, tall connectors, fine-pitch assemblies, glue deposits, and non-electronic features found in industrial modules.
Delvitech’s use of full 3D imaging — height, depth, volume, and surface geometry — reflects a broader metrology trend. As assembly complexity increases across industries, 2D pattern-based methods are proving insufficient.
3D data enhances the reliability of detecting mechanical deviations, coplanarity issues, and shape anomalies. For sectors where defect escapes carry high cost or safety risk, volumetric measurement is becoming a baseline requirement.
Integration into Data-Centric Manufacturing
The software infrastructure surrounding the inspection engine is built to operate within Industry 4.0 architectures. The platform supports centralized model governance, remote diagnostics, and SPC-style dashboards, enabling multi-line and multi-site oversight of inspection performance.
This shift marks AOI’s evolution from an isolated machine to a connected analytics node. In smart-factory environments — whether electronics, automotive, medical, or industrial equipment — inspection data is increasingly expected to feed upstream process control, machine-learning feedback loops, and predictive-quality strategies.
A Data-Driven Path Forward
With new capital, Delvitech is positioned to scale its technology and manufacturing footprint. For the metrology community, the development highlights a broader trajectory: AOI is evolving into a continuous-learning subsystem within digital production ecosystems.
As manufacturing of all kinds moves toward tighter tolerances, greater assembly complexity, and more dynamic product cycles, adaptive AI-native inspection may represent the next phase of quality-assurance infrastructure — not only for electronics, but across multiple industrial domains.
For more information: www.delvi.tech
