AI, ML & Generative AI Capabilities
Logic Fruit has graduated from doing traditional FPGA/DSP based systems to developing hardware accelerated AI/ML applications using FPGA’s and GPU’s. The solutions include both on-edge and cloud based deployments.
Overview
At Logic Fruit Technologies, we blend deep system-level engineering with advanced AI/ML and Generative AI expertise to deliver scalable, intelligent, and production-ready solutions. From accelerating neural networks on custom hardware to optimizing models for edge devices, our solutions are designed for speed, portability, and real-world performance.
Building on our strong foundation in complex FPGA-based systems, we are advancing into next-generation AI/ML, Computer Vision, and real-time edge analytics. We specialize in video/image processing, object detection, embedded vision (Jetson/FPGAs), and Generative AI pipelines (LLMs, RAG). Our cross-domain proficiency spans CPUs, GPUs, and FPGAs to deliver low-latency, high-throughput AI systems.
Our AI/ML Capabilites
Computer Vision & Embedded Vision
Natural Language Processing
Generative AI & LLMs
Edge AI & Hardware Acceleration
AI Model Optimization & Porting
Data Mining & Feature Engineering
Inference Acceleration & Containerized Deployment
Predictive Maintenance
Anomaly Detection
Time Series AI
Speech & Audio Processing
Synthetic Data Generation
Demos: Computer Vision with AI/ML for Real-Life Solutions
Explore our demos showcasing AI/ML-powered computer vision solving real-life challenges. From traffic detection to collision avoidance, experience how our intelligent systems are transforming everyday scenarios with real-time precision.
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What Logic Fruit has for you!
Hardware Acceleration
- Edge deployment on platforms like Xilinx Alveo U200, Kria, Ultrascale+, Ultrascale96, ZCU102, and Jetson Orin/Nano
- Custom RTL/HLS kernel acceleration using C/C++, OpenCL, and HLS for domain-specific AI operators
- DPU customization with model-aware pipelining, memory reuse, and hardware scheduling optimizations
- Hybrid acceleration with FPGA + GPU co-processing for ultra-low latency and high-throughput inference
- AI model porting & optimization to FPGAs using Vitis AI, TFLite, ONNX, and OpenVINO toolchains
- Power-efficient AI inference for embedded platforms (Jetson, Raspberry Pi)
- Security & IP licensing support via Accelize DRM and Xilinx App Store integration
AI/ML & Generative AI
- End-to-end pipeline: Ingestion -> Training -> Optimization -> Deployment
- NLP, Computer Vision, and LLM-based solutions using PyTorch, TensorFlow, and Hugging Face
- Vision intelligence: Object detection, video/image analytics, embedded deployment using YOLOv5, ViT, and ResNet on Jetson/FPGAs
- Generative AI pipelines using LangChain, LlamaIndex, FAISS
- Quantization and fine-tuning using LoRA, QLoRA, AWQ, BitsAndBytes
- Optimized edge inference using TensorRT, TFLite, OpenVINO, and vLLM
Tools and Infrastructure
Want To Talk With Our Experts!
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