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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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

    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

    Frequently Asked Questions

    What do you help telco and media teams optimise?

    +

    RF/signal‑propagation simulations, codec performance for streaming/XR, and AI analytics for incident detection and proactive operations.

    Can you improve QoE without inspecting content payloads?

    +

    Yes. We use stream metadata, telemetry, and heuristics to derive perceptual quality signals—keeping workloads efficient and privacy‑preserving.

    What’s your codec experience?

    +

    We’ve ported and tuned modern codecs, including LCEVC—for low‑latency, bandwidth‑efficient delivery and XR use cases; we also build custom pipeline optimisations around them.

    Where do your solutions run—edge, on‑prem, or cloud?

    +

    All three. We target NVIDIA/Intel GPU stacks and containerised AWS EC2 GPU environments, depending on your latency, cost, and data‑sovereignty requirements.

    What proof points can you share?

    +

    CloudRF Signal Propagation & Tower Optimisation—a GPU‑accelerated engine that made large‑scale propagation studies practical for day‑to‑day planning. Public case study available.

    How do you integrate with existing toolchains?

    +

    Via standard video/RF processing components (e.g., FFmpeg, custom libraries) and APIs, we extend your current simulation or media pipelines rather than replacing them.

    How do you approach security and IP ownership?

    +

    Engagements are NDA‑first with strict IP clauses; code and models delivered under contract terms you control. We prioritise on‑prem/edge options when sovereignty is required.

    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: 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: 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

    Learn how TechnoLynx helps reduce inference costs for trained neural networks and real-time applications including natural language processing, video games, and large language models.

    Case Study: Multi-Target Multi-Camera Tracking

    Case Study: Multi-Target Multi-Camera Tracking

    10/02/2023

    Learn how TechnoLynx built a cost-efficient, AI-powered multi-target tracking system using existing CCTV infrastructure. Real-time object tracking across non-overlapping cameras using global and local IDs.

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

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

    11/01/2023

    See how TechnoLynx used AI-powered action recognition to improve video analysis and automate complex tasks. Learn how smart solutions can boost efficiency and accuracy in real-world applications.

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

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

    15/12/2022

    TechnoLynx improved V-Nova’s video decoder with GPU-based pixel processing, Metal shaders, and efficient image handling for high-quality colour images across Apple devices.

    Consulting: AI for Personal Training Case Study - Kineon

    Consulting: AI for Personal Training Case Study - Kineon

    2/11/2022

    TechnoLynx partnered with Kineon to design an AI-powered personal training concept, combining biosensors, machine learning, and personalised workouts to support fitness goals and personal training certification paths.

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

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

    22/05/2022

    See how we successfully compeleted this project using Anomaly Detection!

    Case Study: Accelerating Cryptocurrency Mining (Under NDA)

    Case Study: Accelerating Cryptocurrency Mining (Under NDA)

    29/12/2020

    Our client had a vision to analyse and engage with the most disruptive ideas in the crypto-currency domain. Read more to see our solution for this mission!

    Case Study - AI-Generated Dental Simulation

    Case Study - AI-Generated Dental Simulation

    10/11/2020

    Our client, Tasty Tech, was an organically growing start-up with a first-generation product in the dental space, and their product-market fit was validated. Read more.

    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)

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