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Boosting efficiency, streamlining operations, automating routines to address challenges that were once too time-consuming, costly, or even impossible.
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01
Image Recognition
Identify and classify objects in images with precision. Ideal for a wide range of applications, from retail inventory management to document processing in banking services.
02
Video Analysis
Real-time video analysis solutions can detect and track objects, recognise activities, and monitor environments. Used to enhance security and surveillance.
03
Facial Recognition
Facial recognition technology ensures high accuracy in identity verification, enhancing security measures and personalising user experiences.
04
Optical Text-Character
Recognition (OCR)
Convert printed or handwritten text into machine-readable data with our OCR solutions, improving data entry processes and document management.
JS
YOLO
Restful API Backend
Rapid STP
PyTorch
REST API
OpenCV
TimescaleDB
PostgreSQL
TensorFlow
Qt
C++ / C
Efficiently handle vast volumes of documents with precision and speed using Optical Character Recognition (OCR) technology. Our systems integrate advanced OCR algorithms to extract data from invoices, contracts, and forms, streamlining workflows and reducing manual errors.
Detect anomalies and suspicious patterns in transactions using machine learning algorithms and anomaly detection techniques. Our systems employ real-time monitoring and predictive analytics to identify and mitigate fraudulent transactions swiftly.
Utilise advanced biometric authentication technologies like FaceNet for facial recognition and speaker recognition models for secure and accurate customer identity verification.
Employ machine learning models such as Gradient Boosting Machines (GBMs) and Neural Networks to assess credit risk profiles, automate decision-making, and optimise lending strategies.
Integrate deeep.app's diverse user scenarios database to enhance AI model training and validation, ensuring robust and scalable solutions for business applications.
Vision systems monitor hygiene in food processing plants by detecting contaminants and foreign objects on production lines. They also ensure compliance with cleanliness standards by checking for residues on surfaces and equipment, thereby preventing potential health hazards.
Deploy high-resolution cameras and AI algorithms to inspect food products for defects. Vision systems detect blemishes and size discrepancies, guaranteeing consistency and quality and reducing human error.
Analyse visual data from storage facilities to monitor inventory levels and the condition of stored food items. Reduce waste by identifying products nearing expiration, ensuring fresher goods reach the market.
Employ advanced computer vision to verify that packaging is correctly sealed and labels are properly applied and legible. Detect misaligned or missing labels, flagging defective products for removal. This prevents packaging errors and guarantees that accurate information reaches consumers, enhancing brand reliability.
In smart kitchens, computer vision aids robotic systems in preparing food by recognising ingredients, measuring portions, and monitoring cooking processes.
Automate inventory tracking and management via image recognition. It identifies and counts stock items on shelves or in storage, improving inventory accuracy and optimizing supply chain operations.
Streamline visual inspection processes to detect defects like scratches or dents on products with ML-powered anomaly detection algorithms. This technology will ensure consistent quality control without the need for extensive manual oversight.
Integrate OCR technology to extract text from images of labels or documents and automate tasks like batch tracking and compliance verification. It will improve data accuracy and speed up administrative processes.
Enhance workplace safety by monitoring employee activities and detecting unsafe behaviours, such as operating machinery without proper protective gear. This will help enforce safety protocols and reduce accidents.
Use computer vision to guide robots accurately in assembly tasks by recognising parts and their orientation. This will ensure precise component placement and assembly, reducing errors and boosting production efficiency.
Monitor equipment health in real-time using IoT sensors and image analysis. It will detect early signs of wear, such as abnormal vibrations or heat patterns, allowing proactive maintenance to prevent costly breakdowns.
years of experience
employees
projects
international awards
on Clutch
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Dr. Kaplun is ready to roll.
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With a Ph.D. in Computer Science from St Petersburg Electrotechnical University (LETI), Dr. Kaplun brings over 15 years of experience in machine learning, deep learning, and real-time processing. Author of 100+ papers and holder of 5 patents, he specialises in object detection, scene understanding, and medical imaging. He is also a member of Institute of Electrical and Electronics Engineers (IEEE) and a candidate of Technical Sciences.
Fields of Expertise
Computer Vision
Machine Learning
Embedded Systems
Digital Signal Processing
We upgrade IP cameras with AI to monitor and analyse business operations. This ensures quality control, boosts staff efficiency, increases speed, reduces inaccuracies, and improves overall performance.
