Your Trusted Computer Vision Partner
At Visual Grab, you work directly with Dr. Raj Gupta (PhD, Computer Vision, IIT Madras) and a team of computer vision experts who specialise in deep learning and the latest AI technologies. We build robust vision systems using advanced techniques such as object detection, image segmentation, pose estimation, activity analysis, and tracking. Our solutions are engineered to perform reliably in real-world conditions—handling noise, lighting changes, motion, and hardware constraints—while delivering clear business outcomes like safety, efficiency, automation, and quality improvement. With honest guidance, end-to-end execution, and custom models tailored to your cameras and environment, we provide practical, scalable, and high-impact computer vision solutions for modern industries.
About Us
Our work is driven by a highly skilled team of computer vision and deep-learning specialists, led by Dr. Raj Gupta, a PhD in Computer Vision from IIT Madras with over 20 years of experience in AI, image processing, and video analytics. Together, we design and deploy practical, real-world vision systems that transform camera data into intelligence, automation, and measurable outcomes.
With strong research foundations and hands-on deployment expertise, our team builds solutions that handle real-world variability—noise, lighting shifts, motion, occlusions, and hardware constraints—while staying aligned with industry needs across surveillance, manufacturing, retail, healthcare, and smart-city applications.
🎓 Led by a PhD in Computer Vision (IIT Madras)
🧠 Team of AI/ML & Vision Engineering Experts
Computer Vision Services and many more
Our Approach
Our methodology reflects a research-oriented yet industry-practical framework designed to ensure that every computer vision system we deliver is scientifically robust, operationally reliable, and aligned with measurable business objectives.
Understand the Problem
We begin with a rigorous problem-definition phase, analysing your operational constraints, camera ecosystem, environmental variables, and expected performance metrics. This establishes a clear problem–solution formulation grounded in technical feasibility.
Feasibility & Proof of Concept (PoC)
Using representative data from your cameras, we conduct a controlled feasibility study to evaluate signal quality, scene complexity, and achievable model accuracy. This step ensures that the proposed approach is empirically validated before moving to full-scale development.
Data & Model Design
We architect a tailored data pipeline—defining annotation strategy, sampling distribution, model architecture selection, and augmentation protocols. Every design choice is optimised for your domain conditions including lighting, perspective, motion profiles, and hardware limitations.
Build & Integrate
We develop and optimise the deep-learning model, compress it for edge or hybrid deployment if required, and integrate the system with your existing infrastructure—dashboards, platforms, APIs, or workflow engines—ensuring seamless interoperability.
Deploy, Monitor & Improve
Post-deployment, we implement continuous monitoring, error analysis, and statistical performance tracking. This enables iterative refinement, domain adaptation, and long-term model stability as real-world conditions evolve.
🎓 PhD-Led Expertise
Direct access to a computer vision researcher, not just a generic vendor
⚙️ From Research to Deployment
Solutions tested against noise, lighting, occlusion, and real-world constraints
📊 Business-First Mindset
We translate technical metrics into ROI, safety, compliance, and productivity
🧩 Flexible Engagements
Advisory, PoC, or complete end-to-end delivery
Engagement Models
We offer flexible collaboration models designed to match your technical maturity, deployment readiness, and business timelines. Each model allows you to leverage deep expertise in computer vision, while engaging at the pace and scale that best fits your requirements.
Technical Advisory & Strategy Consulting
Ideal for organisations exploring computer vision for the first time or validating an internal roadmap.
We provide expert guidance on feasibility, architecture selection, model strategy, hardware recommendations, and risk evaluation—ensuring you invest in the right direction from day one.
Feasibility Study & Proof of Concept (PoC)
A focused 4–12 week engagement where we analyse your real camera data, build a baseline model, and empirically validate whether computer vision can meet your accuracy and operational goals.
This de-risks larger investments and establishes a data-backed foundation for full development.
Custom Model Development
End-to-end development of deep-learning models including detection, segmentation, pose estimation, tracking, and activity recognition—fully tailored to your domain, hardware, and environmental conditions.
This includes dataset design, annotation guidelines, model training, optimisation, and evaluation.
Full Solution Delivery (End-to-End)
A complete deployment cycle where we handle the entire pipeline:
data management → model design → system development → integration → QA → edge/cloud deployment → monitoring.
This is ideal for organisations ready to operationalise computer vision at scale.
Joint R&D or Team Augmentation
For companies building internal vision capability, we work as your extended R&D team—supporting algorithm design, code reviews, optimisation, benchmarking, and knowledge transfer.
This ensures your team accelerates development while maintaining high scientific rigor.