Our customers perceive us as a natural extension of their R&D teams: expert computer vision consultants entrusted with tackling their most complex and strategic challenges across vision, AI, and robotics.
What sets us apart
Real expertise in computer vision consulting means turning research into added value and building solutions that perform reliably not only in the lab but in real-world and production environments. Indeed, as a specialized computer vision company, Deep Vision Consulting transforms advanced technology into robust, high-performing products. Our team combines deep technical knowledge with hands-on industry expertise to deliver end-to-end computer vision consulting services from early feasibility studies to deployment-ready systems. When you work with us, you gain a trusted technical partner committed to making computer vision and artificial intelligence deliver tangible business impact.
OUR SERVICES
We provide end-to-end computer vision consulting for AI-driven projects.
- Problem & Context Analysis: We work alongside you to assess your case from every perspective: you bring domain expertise, we bring technological insight.
- State-of-the-Art Review: Scientific and technological assessments to identify the latest advancements relevant to your case.
- Project Definition: Making sure that clear and objective technical requirements and functional specifications are set as a solid project foundation.
- Project Planning: Structuring activities for the team, whether ours or yours, based on SMART criteria (Specific, Measurable, Achievable, Relevant, Time-bound).
- Industrial Research & Feasibility Studies: Exploring solutions and assessing technological viability.
- Existing Solutions Assessment: Evaluating tools, frameworks, and software available either from your current codebase, open-source repositories or third parties.
- Design, Prototyping & Validation: Developing, refining, and testing software, algorithms, methods, procedures, tools and instruments.
- Data Management: Defining, identifying, preparing, collecting, and tagging datasets.
- Industrial-Grade Software Development: Building robust, secure, maintainable, efficient and scalable software.
- Deployment on target platforms: Optimizing the solution for cloud, on-premise workstations, mobile devices or embedded systems.
- Technology Transfer: Ensuring seamless adoption and integration within your organization.
- Problem & Context Analysis: We work alongside you to assess your case from every perspective: you bring your domain expertise, we bring our technological insight.
- State-of-the-Art Review: Scientific and technological assessments to identify the latest advancements relevant to your case.
- Project Definition: Making sure that clear and objective technical requirements and functional specifications are set as a solid project foundation.
- Project Planning: Structuring activities for the team, whether ours or yours, based on SMART criteria (Specific, Measurable, Achievable, Relevant, Time-bound).
- Industrial Research & Feasibility Studies: Exploring solutions and assessing technological viability.
- Existing Solutions Assessment: Evaluating tools, frameworks, and software available from third parties.
- Design, Prototyping & Validation: Developing, refining, and testing software, algorithms, methods, procedures, tools and instruments.
- Data Management: Defining, identifying, preparing, collecting, and tagging datasets.
- Industrial-Grade Software Development: Building robust, secure and scalable software.
- Deployment on target platforms: Optimizing the solution for cloud, on-premise workstations, mobile devices or embedded platforms.
- Technology Transfer: Ensuring seamless adoption and integration within your organization.
OUR EXPERTISE
Computer vision comes in many forms, and most projects involve more than one. As experienced computer vision consultants, we intentionally cover them all.
Image formation and early processing
Many problems can be made easier just by choosing the most appropriate imaging acquisition setup: sensors, optics, illumination, and relative poses. Once an image is captured, traditional image processing methods can be combined with custom logics either to effectively solve straightforward problems or to create a solid ground for further processing.
A robust computer vision system starts long before AI models are trained. As a computer vision consulting company, we design and optimize the entire imaging acquisition pipeline from sensor technology and optical configuration to illumination engineering and traditional image processing. By mastering the physics of image formation and combining it with solid classical computer vision methods, we build reliable, efficient, and industry-ready solutions that reduce complexity and increase the final performance.
SENSORS
Selecting the right sensing technology is the first critical step toward a robust and measurable vision system. We support sensor selection, benchmarking, synchronization, and integration in embedded systems or industrial environments.
Cameras, Modules, Sensors
- Industrial cameras (e.g. Opto Engineering, Basler, Alkeria, FLIR, Allied Vision, VA Imaging, Lucid, etc)
- Camera modules (Videology, Arducam, Innodisk, Leopard, E-con Systems, TechNexion, Raspi cams, etc)
- Sensors (e.g. OnSemi, OmniVision, Sony, STMicroelectronics, Heimann, Excelitas, Metavision, etc)
- Smart cameras (based on SoCs with GPUs or NPUs, like Nvidia Jetson, NXP i.MX8/9, Renesas RZ/V2*, Texas Instruments Jacinto, Hailo 15, AMD UltraScale+)
2.5 & 3D Imaging Technologies
- Stereo cameras (e.g. FLIR / Point Grey, ZED, custom stereo rigs)
- Structured light systems (e.g. Kinect v1, PrimeSense, Asus Xtion)
- Time-of-Flight (ToF) cameras (e.g. Kinect v2, Basler ToF, IFM, BlueTechnix)
- Laser profilometers (e.g. Leuze, Wenglor)
- LiDAR sensors (e.g. SICK, Velodyne, Ouster)
- Radar systems
Beyond Visible Spectrum
- Infrared imaging (NIR, SWIR)
- Thermal imaging (LWIR)
- UV imaging
- Multispectral and hyperspectral imaging
- X-ray imaging
- Neuromorphic imaging / Event cameras
OPTICS & ILLUMINATION
The quality of the imaging system beyond the sensors often determines algorithmic success. We design acquisition setups that maximize signal-to-noise ratio and robustness in real-world conditions.
We provide consulting on:
- Lens selection (focal length, distortion, MTF, telecentric optics)
- Depth of field optimization
- Structured lighting
- Deflectometry over specular surfaces
- Polarized illumination
- Backlight, dark-field, bright-field setups
- High-speed strobed illumination
- Illumination control for reflective or transparent materials
IMAGE PROCESSING AND ANALYSIS
Before deep learning and AI in general, strong foundations in traditional computer vision are often the key to robustness and efficiency. We combine traditional computer vision with custom logics and domain-specific constraints to build reliable, interpretable, and computationally better solutions, often simplifying the AI models that follow.
Our expertise includes:
- OpenCV-based pipelines
- Intrinsic, extrinsic and multi-camera calibrations
- Geometric and 2D/3D transformations
- Image rectification and undistortion
- Denoising and filtering
- Thresholding and segmentation
- Morphological operations
- Edge detection and feature extraction
- Keypoints and local features
- Optical flow and motion estimation
- Classical object detection and measurement
- Sub-pixel localization and metrology
- Rule-based inspection systems
Deep learning and AI
Very few projects can rely solely on traditional image processing. Most require the integration of AI and deep learning models, such as deep convolutional neural networks, vision transformers, and vision-language models, to extract higher-level, more semantic information. However, just using off-the-shelf solutions unleashes just a minimal portion of the opportunities. With our experienced technical team you will exploit AI to the full, rethinking the entire AI pipeline from the ground up: from architecture design and the underlying mathematical foundations to training strategies customized to incorporate problem-specific constraints and nuances.
As part of our deep learning consulting services, we design, train, and deploy custom AI models tailored to specific requirements. We do not rely solely on off-the-shelf architectures: when needed, we redesign network structures, loss functions, and optimization strategies to reflect the specific geometry, physics, or operational constraints of the problem.
We manage the entire AI pipeline from dataset strategy and annotation workflows to model validation and performance benchmarking.
IMAGE TASKS
We develop custom computer vision models for:
- Image classification, object detection, and segmentation
- Instance and semantic segmentation
- 2D and 3D pose estimation
- Keypoint detection and landmark localization
- OCR, OCV, and document analysis
- Anomaly and defect detection
- Depth estimation and monocular 3D reconstruction
- Vision-language integration (multimodal models)
VIDEO TASKS
For dynamic environments, we provide AI consulting solutions for:
- Action and activity recognition
- Optical flow estimation
- Single and multi-object tracking
- Temporal event detection
- Video anomaly detection
- Multi-camera fusion and spatio-temporal modeling
DATA & TRAINING PIPELINES
Strong AI systems are built on strong data foundations:
- Dataset cleaning and curation
- Supervision of annotation teams
- Design of custom tagging tools
- Data augmentation and domain adaptation
- Synthetic data generation
- Training strategy optimization (transfer learning, fine-tuning, distillation)
- Model evaluation, ablation studies, and robustness analysis
3D vision and geometry
Producing 3D data introduces additional complexity compared to traditional 2D imaging because it is inherently different. It requires specialized algorithms rather than conventional imaging techniques or standard deep neural networks. However, leveraging 3D data, either alone or combined with 2D data, can significantly enhance system performance and enable achievements that would be challenging to reach with optical imaging alone.
3D perception requires more than changing the sensor alone, it demands a solid understanding of multi-view geometry, projective models, and spatial reasoning. As part of our computer vision consulting services, we design and implement 3D computer vision solutions that combine advanced sensing technologies with geometry-aware algorithms and learning-based methods.
We support projects ranging from industrial inspection and robotics to autonomous systems and high-precision metrology, leveraging both classical geometric vision and modern deep learning approaches for 3D data.
3D RECONSTRUCTION & GEOMETRIC VISION
Our expertise covers:
- Multi-view 3D reconstruction and Structure from Motion (SfM)
- Monocular and stereo photogrammetry
- Dense and sparse point cloud generation
- Surface reconstruction and meshing
- Shape-from-shading and photometric stereo
- Deflectometry for reconstruction of specular surfaces
LOCALIZATION, MAPPING & CALIBRATION
- Visual-inertial odometry and SLAM (Simultaneous Localization and Mapping)
- Marker-based and markerless calibration
- Single and multi-camera calibration
- Hand-eye calibration for robotic systems
- Geometric alignment and registration (ICP and variants)
3D ANALYSIS & LEARNING
We combine geometry-based methods with deep learning for:
- 3D object detection and segmentation
- Point cloud processing (PointNet-like architectures and graph-based models)
- 6D pose estimation
- 3D inspection and dimensional measurement
- Fusion of 2D and 3D data for enhanced robustness
Simulation
Simulation acts as a powerful accelerator in modern computer vision consulting, allowing us to model sensors, scenes, and system dynamics in physics-aware environments. By designing these virtual spaces, we enable faster prototyping, controlled experimentation, and scalable synthetic data generation, significantly reducing development time and real-world risk before any solution is deployed.
Beyond simple acceleration, simulation serves as a digital bridge between concept and reality. We build custom, physics-aware environments tailored to the exact geometry and operational context of your project, allowing for rigorous testing of algorithms and hardware interaction that would be impractical to perform manually. This deep-dive approach ensures that our solutions arrive in the real world already battle-tested against environmental variables and rare edge cases.
SYNTHETIC DATA GENERATION
When real data is scarce, expensive, or difficult to annotate, we develop synthetic data pipelines for industrial and robotics applications to:
- Generate photorealistic RGB, depth, IR, NIR, SWIR, Thermal, UV and multi-spectral / multi-domain images in general
- Simulate LiDAR, stereo, and ToF sensors
- Automatically produce pixel-level annotations
- Model rare events and edge cases
- Perform domain randomization for robust AI training
PHYSICS-BASED SENSOR SIMULATION
To obtain accurate benchmarking of algorithms under controlled and repeatable conditions, we simulate:
- Camera projection models and lens distortion
- Illumination effects and material reflectance
- Noise models and sensor artifacts
- Multi-view and multi-sensor setups
- 3D scene geometry and object interactions
DIGITAL TWINS & SYSTEM VALIDATION
We develop virtual replicas of real environments to:
- Test perception algorithms before deployment
- Validate 3D vision and robotics pipelines
- Stress-test AI models under controlled variability
- Optimize sensor placement and acquisition setups
Deployment
Developing an idea and building a prototype is often just half the journey. Our team specializes in turning algorithm pipelines and solution prototypes into industry-grade software libraries (python or C++) optimized for the choosen target hardware: either an embedded system, a mobile phone, a datacenter server with massive GPUs or a remote cloud infrastructure.
Transforming a prototype into a production-ready system requires more than porting code to new hardware. As part of our computer vision consulting services, we design scalable, maintainable, and optimized AI deployment solutions that bridge research and real-world operation.
We convert traditional computer vision and deep learning prototypes into robust software platforms, engineered for performance, reliability, and long-term maintainability.
OPTIMIZATION & PERFORMANCE ENGINEERING
Deep learning and vision algorithms can be computationally demanding. We optimize them to minimize latency, memory footprint, computing resources usage and energy consumption:
- Model pruning, quantization, and distillation
- TensorRT and ONNX runtime optimization
- CUDA acceleration and GPU kernel optimization
- CPU vectorization (Eigen, SIMD)
- Mixed precision and low-bit inference
- Algorithmic optimization and complexity reduction
TARGET PLATFORMS & HARDWARE
We deploy AI systems across heterogeneous environments:
- X86 or ARM-based CPUs
- NVIDIA GPUs (desktop, embedded, data center)
- Embedded SoCs with NPUs
- NXP i.MX8, i.MX93, i.MX95
- AMD Zynq Ultrascale+
- Hailo15
- Renesaz RZ-V2L, RZ-V2N, RZ-V2H
- Texas Instruments Jacinto TD4V*, AM6*A
- Nvidia Jetson platforms
- Dedicated AI accelerators (Hailo8, DeepX M1)
PRODUCTION DEPLOYMENT & PLATFORMS
Deployment is also about software engineering discipline. We provide:
- Modular C++ and Python libraries
- API design and SDK development
- Containerization (Docker-based workflows)
- CI/CD pipelines and version control integration
- Unit testing and validation frameworks
- Cloud, on-premise, mobile, edge and web deployment
- Scalable inference services (GPU cloud or hybrid architectures)
Robotics
Vision systems give robots the ability to perceive the world, but acting on that data is the true challenge, especially in industrial and collaborative robotics (cobots). We bridge this gap by mastering complex motion control and path planning, from managing collisions (self, objects, or other robots) to optimizing multi-robot workflows, ensuring safety and precision in demanding environments.
Vision enables robots to perceive the environment and robotics enables them to act. As part of our robotics consulting services, we design perception-driven control systems where computer vision, geometry, and motion planning operate as a unified pipeline.
We develop AI-driven robotics solutions in which robotic arms and autonomous platforms dynamically adapt their motion based on real-time perception data, enabling complex tasks such as bin picking, precision assembly, inspection, and agricultural harvesting.
MOTION & PATH PLANNING
We have extensive experience navigating robots in complex and constrained environments, optimizing motion to minimize cycle time while ensuring safety and robustness. Our expertise includes:
- Path planning and trajectory generation
- Motion planning and kinodynamic planning
- Collision avoidance and obstacle-aware planning
- Real-time replanning based on vision feedback
- Optimization of task completion time
- Multi-robot coordination strategies
ROBOT KINEMATICS & CONTROL
Our solutions integrate deep learning in robotics with classical control theory, ensuring both adaptability and reliability. We design and optimize robotic arm behavior through:
- Forward and inverse kinematics
- Singularity analysis and avoidance
- Workspace analysis and reachability studies
- Velocity profile optimization (e.g. S-curve trajectories)
- Force-aware and constraint-aware motion
- Vision-guided manipulation
ROBOTIC PLATFORMS
We have worked with multiple industrial robotic systems and controllers, including:
- Kawasaki robotic arms
- Mitsubishi industrial robots
- Siemens-controlled automation systems
OUR APPROACH
Over the years we have developed an approach that helps us to firmly navigate through the complexity and uncertainty of industrial research and innovation projects.
01. KICKOFF
It all starts with introductory meetings with the goal to understand as much as possible needs, context, challenges and constraints. After internal assessments by senior team members, we plan another moment to share what could be defined as a draft of a collaboration, with coarse technical goals and efforts required to get there. This initial approach to the problem can be iterated and refined. Depending on the complexity and uncertainty of the project, the outcome of this phase can be more tentative – to be discussed as we go – or more definitive – with clear milestones and releases.
02. ANALYSIS
In the third step, we actually design and develop the prototypes. Here uncertainty has lowered, but typically not vanished. We usually approach the most uncertain topics early, so to have higher chances to deal with them from a different perspective if needed. Whenever applicable, we take great care in preparing the playing field by selecting train / test data, metrics and baselines so we can measure improvements and quantify where we stand with respect to our target. During this part of the project, we continuously touch base with the technical counterpart of the client.
03. PROTOTYPING
In the third step, we actually develop the prototype. Here uncertainty has lowered, but typically not vanished. So we usually try to approach the most uncertain topics early, so to have higher chances to deal with them from a different perspective if needed. Whenever applicable, we take great care in preparing the playing field by selecting train / test data, metrics and baselines so we can measure improvements and quantify where we stand with respect to our target. During this part of the project, we continuously touch base with the technical counterpart of the client.
04. ENGINEERING
Eventually, we take the prototype algorithm and convert it into a production grade software library that integrates with the client’s existing tech stack. This includes, but is not limited to, C++ code, neural network quantization / deployment to custom boards, code profiling and optimization, deployment to the target platforms, logging and pervasive testing.
05. EVOLUTION
Our work does not end at deployment. We continue to keep our clients’ challenges in view beyond the immediate engagement, drawing fresh perspectives from industry events, research conferences, and conversations with technology partners. When we identify a meaningful opportunity, we proactively return with new ideas and concrete proposals. Whether to improve performance, extend capabilities, or take advantage of emerging technologies. This continuity helps our clients protect their investment, adapt to change, and remain at the forefront of what is possible.
01. KICKOFF
It all starts with introductory meetings with the goal to understand as much as possible needs, context, challenges and constraints. After internal assessments by senior team members, we plan another moment to share what could be defined as a draft of a collaboration, with coarse technical goals and efforts required to get there. This initial approach to the problem can be iterated and refined. Depending on the complexity and uncertainty of the project, the outcome of this phase can be more tentative – to be discussed as we go – or more definitive – with clear milestones and releases.
02. ANALYSIS
The second step is to deepen the analysis – and in many cases this is also the most important step. Here we make sure every aspect of the problem has been considered, we help the client fill in the gaps for specification / requirements or to sort different goals according to complexity and priority. It is also the time to review the literature, do quick tests to assess the exploitability of already developed technologies. At the end of this step, a reduced number of promising action plans have been defined.
03. PROTOTYPING
In the third step, we actually develop the prototype. Here uncertainty has lowered, but typically not vanished. So we usually try to approach the most uncertain topics early, so to have higher chances to deal with them from a different perspective if needed. Whenever applicable, we take great care in preparing the playing field by selecting train / test data, metrics and baselines so we can measure improvements and quantify where we stand with respect to our target. During this part of the project, we continuously touch base with the technical counterpart of the client.
04. ENGINEERING
Eventually, we take the prototype algorithm and convert it into a production grade software library that integrates with the existing tech stack. This includes, but is not limited to, C++ code, neural network quantization / deployment to custom boards, code profiling and optimization, deployment to the cloud.
05. EVOLUTION
As technology advances, we help our clients stay ahead. With a solid deployed solution in place, we continuously refine and enhance it, ensuring it remains at the cutting edge of what’s possible.