Accelerating Connectivity

AI & HPC for Telecom and Media

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Telecom operators and broadcast platforms are under pressure to deliver high-quality experiences on a scale. TechnoLynx enables this with GPU-accelerated signal simulations, codec optimisation, and AI-driven analytics for real-time insights.

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City view
Telecommunication tower with antennas for network connectivity

Industry Landscape

Challenges include:

  • Signal propagation complexity in dense urban or remote terrains.
  • Codec performance bottlenecks for streaming and XR applications.
  • Data overload from network logs and telemetry.

    • Generic R&D claims won’t suffice—our proof lies in projects that have transformed performance for global leaders.

    Why Choose Us?

    Our Promise

    Enterprises expect measurable outcomes. Our modules deliver human‑perceived quality metrics and low‑latency pipelines, accelerating pilots into offer‑ised services operators can market.

    Classical Vision

    CloudRF Signal Propagation Acceleration

    Broadcast

    Cut multi-day simulations to hours with GPU optimisation.

    Explainability

    Custom Codec Engineering

    Broadcast

    Expertise in V-Nova LCEVC and Teraki for bandwidth-efficient streaming.

    Cross-Disciplinary

    AI Analytics for Telco Data

    Broadcast

    Real-time pattern detection and anomaly alerts for proactive incident management.

    Areas of Expertise

    Signal Propagation
    Codec Engineering
    Generative AI
    High-Performance Computing

    Featured Case Studies

    Explore our latest thought leadership on innovation, technology, and industry best practices.

    Case Study: CloudRF  Signal Propagation and Tower Optimisation

    Case Study: CloudRF  Signal Propagation and Tower Optimisation

    May 15, 2025

    See how TechnoLynx helped CloudRF speed up signal propagation and tower placement simulations with GPU acceleration, custom algorithms, and cross-platform support. Faster, smarter radio frequency planning made simple.

    Read more
    Case-Study: V-Nova - GPU Porting from OpenCL to Metal

    Case-Study: V-Nova - GPU Porting from OpenCL to Metal

    Dec 15, 2023

    Case study on moving a GPU application from OpenCL to Metal for our client V-Nova. Boosts performance, adds support for real-time apps, VR, and machine learning on Apple M1/M2 chips.

    Read more
    View case studies See all
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    Technology Stack

    Python
    C++
    PyTorch
    TensorFlow
    CUDA
    OpenCL
    FFmpeg
    NVIDIA GPUs
    AWS EC2
    2019
    Founded in
    95%+
    Client Satisfaction Rate
    20+
    Successful Projects Delivered

    Client Testimonials

    TechnoLynx delivered the project on time and provided quality outputs that met the client's expectations. The team was proactive in providing ideas and suggestions, and they were careful at properly planning the tasks. The client also praised the team's expertise in GPU programming and AI.

    Guido Meardi - CEO

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    Check V-Nova

    TechnoLynx's skill in low-level software development was impressive. TechnoLynx was able to create four prototypes with common components and an interface for easy maintenance. The client was extremely happy with the solution's speed. Moreover, their communication was seamless and straightforward.

    Alex Farrant - Director

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    Check CloudRF

    TechnoLynx's unique aspect is that they're able to transform complex theories into practicable and applicable results. TechnoLynx provides research reports and architecture planning documents. The team is able to transform complex theories into practicable and applicable results. TechnoLynx's project management is strong and delivers work on time without hardware issues, being responsive through virtual meetings.

    Forrest Smith - CEO & Co-Founder

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    Check Kineon

    I’m delighted with our collaboration with their team. Thanks to TechnoLynx's work, the client has been able to co-author two patents. They lead responsive project management to solve problems quickly. The team also praises their skilled and knowledgeable team.

    Gil Hagi - CEO

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    Check Tasty

    We had high-efficiency meetings. TechnoLynx’s work resulted in a successful breakthrough, and their input improved the client’s app. Their flexible and organised project management cultivated a healthy collaboration experience. Ultimately, their professionalism and commitment were impressive.

    Anonymous - CEO

    Telco & Media Optimization FAQ

    How does TechnoLynx optimize Telco and Media workflows?

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    We accelerate high-bandwidth, low-latency operations using GPU-driven engineering. Our expertise covers:

    • RF & Signal Propagation: Large-scale simulations for tower and network planning.
    • Media Streaming: Codec performance optimization for 4K/8K, streaming, and XR.
    • Proactive Operations: AI analytics for real-time incident detection and network maintenance.

    Can you improve Quality of Experience (QoE) without payload inspection?

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    Yes. We prioritize privacy-preserving QoE optimization. By analyzing stream metadata, network telemetry, and heuristic perceptual signals, we derive quality metrics without ever inspecting sensitive content payloads. This keeps workloads compliant and computationally efficient.

    What is TechnoLynx’s experience with modern video codecs?

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    We specialize in the implementation and tuning of high-efficiency codecs, including LCEVC. Our team builds custom pipeline optimizations for low-latency delivery and immersive XR use cases, ensuring bandwidth efficiency without compromising visual fidelity.

    Where are TechnoLynx solutions typically deployed?

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    We provide flexible deployment models tailored to your data sovereignty and latency needs:

    • Edge: For ultra-low latency real-time processing.
    • On-Prem: For maximum security and localized control.
    • Cloud: Containerized GPU environments (e.g., AWS EC2 GPU) for massive scalability.

    What real-world results has TechnoLynx achieved in Telco?

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    One of our primary proof points is the CloudRF Signal Propagation & Tower Optimisation engine. We built a GPU-accelerated simulation engine that transformed large-scale propagation studies from time-intensive tasks into practical, day-to-day planning tools.

    How do you integrate with existing media toolchains?

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    We extend, rather than replace, your current stack. TechnoLynx solutions integrate via standard media components like FFmpeg, custom C++/Python libraries, and robust APIs, ensuring a seamless fit into your existing RF simulation or video processing pipelines.

    Case Studies

    Case Study: CloudRF  Signal Propagation and Tower Optimisation

    Case Study: CloudRF  Signal Propagation and Tower Optimisation

    15/05/2025

    See how TechnoLynx helped CloudRF speed up signal propagation and tower placement simulations with GPU acceleration, custom algorithms, and cross-platform support. Faster, smarter radio frequency planning made simple.
    Case Study: Large-Scale SKU Product Recognition

    Case Study: Large-Scale SKU Product Recognition

    10/12/2024

    Hierarchical SKU classification using DINO embeddings and few-shot learning — above 95% accuracy at ~1k classes, above 83% at ~2k.
    Case Study: WebSDK Client-Side ML Inference Optimisation

    Case Study: WebSDK Client-Side ML Inference Optimisation

    20/11/2024

    Browser-deployed face quality classifier rebuilt around a single multiclassifier, WebGL pixel capture, and explicit device-capability gating.
    Case Study: Share-of-Shelf Analytics

    Case Study: Share-of-Shelf Analytics

    20/09/2024

    Per-shelf share-of-shelf measurement in area and count modes, with unknown-product handling treated as a first-class operational output.
    Case Study: Smart Cart Object Detection and Tracking

    Case Study: Smart Cart Object Detection and Tracking

    15/07/2024

    In-cart perception for autonomous retail checkout: detection, tracking, adaptive FPS sampling, and a session-scoped cart-state model.
    Case-Study: Text-to-Speech Inference Optimisation on Edge (Under NDA)

    Case-Study: Text-to-Speech Inference Optimisation on Edge (Under NDA)

    12/03/2024

    See how our team applied a case study approach to build a real-time Kazakh text-to-speech solution using ONNX, deep learning, and different optimisation methods.
    Case-Study: V-Nova - GPU Porting from OpenCL to Metal

    Case-Study: V-Nova - GPU Porting from OpenCL to Metal

    15/12/2023

    Case study on moving a GPU application from OpenCL to Metal for our client V-Nova. Boosts performance, adds support for real-time apps, VR, and machine learning on Apple M1/M2 chips.
    Case Study: Barcode Detection for Autonomous Retail

    Case Study: Barcode Detection for Autonomous Retail

    15/10/2023

    Camera-based barcode pipeline for in-cart capture: YOLO localisation, ensemble decoding, multi-frame polling — 86.7% vs Dynamsoft 80%.
    Case-Study: Generative AI for Stock Market Prediction

    Case-Study: Generative AI for Stock Market Prediction

    6/06/2023

    Case study on using Generative AI for stock market prediction. Combines sentiment analysis, natural language processing, and large language models to identify trading opportunities in real time.
    Case-Study: Performance Modelling of AI Inference on GPUs

    Case-Study: Performance Modelling of AI Inference on GPUs

    15/05/2023

    How TechnoLynx modelled AI inference performance across GPU architectures — delivering two tools (topology-level performance predictor and OpenCL GPU characteriser) plus engineering education that changed how the client's team thinks about GPU cost.
    Case Study: Multi-Target Multi-Camera Tracking

    Case Study: Multi-Target Multi-Camera Tracking

    10/02/2023

    How TechnoLynx built a cost-efficient multi-target multi-camera tracking system for a smart retail deployment — real-time tracking across non-overlapping CCTV cameras using probabilistic trajectory prediction and consistent global identity.
    Case-Study: Action Recognition for Security (Under NDA)

    Case-Study: Action Recognition for Security (Under NDA)

    11/01/2023

    How TechnoLynx built a hybrid action recognition system for a smart retail environment — detecting suspicious behaviour in real time using transfer learning and a rules-based approach on cost-effective CCTV.

    Case-Study: V-Nova - Metal-Based Pixel Processing for Video Decoder

    Consulting: AI for Personal Training Case Study - Kineon

    Case-Study: A Generative Approach to Anomaly Detection (Under NDA)

    Case Study: Accelerating Cryptocurrency Mining (Under NDA)

    Case Study - AI-Generated Dental Simulation

    Case Study - Fraud Detector Audit (Under NDA)

    Case Study - Embedded Video Coding on GPU (Under NDA)

    Case Study - Accelerating Physics -Simulation Using GPUs (Under NDA)

    Related Posts

    Production Anomaly Detection in Video Data Pipelines: A Generative Approach

    Production Anomaly Detection in Video Data Pipelines: A Generative Approach

    1/05/2026

    Generative models trained on normal frames detect rare video anomalies without labelled anomaly data — reconstruction error is the score.