AI Detection

AI Detection focuses on identifying patterns, anomalies, and meaningful structures within large datasets, images, video, or text. We design detection systems that leverage machine learning, computer vision, and natural language processing to recognize trends, classify content, and detect outliers in real time. Our implementations combine the scalability of Linux with the enterprise integration capabilities of .NET.

Technical Focus

  • Computer Vision: Object detection, facial recognition, and motion tracking using OpenCV, YOLOv8, and TensorFlow on Linux-based GPU systems.
  • Natural Language Detection: Text classification, sentiment analysis, and content moderation via Transformers (BERT, RoBERTa) and spaCy, integrated through Python APIs and ML.NET.
  • Anomaly & Fraud Detection: Time-series and statistical models implemented with Scikit-learn and PyTorch, combined with .NET microservices for real-time inference.
  • Deployment & Integration: Model hosting through ONNX Runtime and ASP.NET Core APIs, containerized via Docker and orchestrated with Kubernetes on Linux servers.
  • Data Pipelines: Continuous input streams using Kafka, Airflow, and Azure Event Hubs for automated detection workflows.

Core Competence

We specialize in intelligent detection systems that combine AI-driven perception with enterprise-grade integration. Our Linux and .NET solutions deliver real-time analysis, continuous learning, and cross-platform scalability for security, compliance, and automation use cases.

AI Generative

AI Generative technologies create new content — from text and images to audio and code — by learning complex data patterns. Our generative AI solutions integrate open-source deep learning frameworks with .NET and Linux infrastructures to deliver scalable and customizable creative intelligence for enterprise applications.

Technical Focus

  • Large Language Models (LLMs): Deployment and fine-tuning of transformer-based models such as GPT, LLaMA, and Phi using PyTorch and Hugging Face Transformers on Linux GPU clusters.
  • Generative Media: Text-to-image and video synthesis using Stable Diffusion, ControlNet, and Diffusers libraries integrated with RESTful APIs hosted in ASP.NET Core.
  • Code & Workflow Generation: Automation of code and documentation generation through Copilot-like assistants and ML.NET pipelines.
  • Hybrid Architecture: Seamless communication between Python-based model services and .NET front-end or middleware layers via gRPC and FastAPI.
  • Deployment & Scaling: Containerized deployment with Docker, Kubernetes, and GPU-accelerated Linux environments; version control with MLflow and Weights & Biases.
  • Data Privacy & Compliance: Implementation of secure, on-premise model hosting and controlled generation pipelines aligned with enterprise security standards.

Core Competence

We build advanced generative AI systems that combine deep learning innovation with .NET integration and Linux scalability. From creative automation to enterprise-level content synthesis, our solutions empower organizations to innovate faster while maintaining control, accuracy, and security.