Privacy‑First
Surveillance AI

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Industry Landscape

Modern Survaillence

The modern surveillance landscape floods us with data but leaves us starved of clarity. TechnoLynx offers AI-powered video analytics. These tools use artificial intelligence (AI) to reduce distractions, automate compliance, and provide useful insights in real time. Our systems designed for this purpose help you move from reactive monitoring to proactive security and operational excellence.

The problem

Raisig costs, slow responses

In today's security environment, organisations deal with a lot of video data. Legacy computational systems generate countless false alarms, leading to operator fatigue and missed incidents.

New regulations like GDPR and the EU AI Act set strict rules for handling personal information. This makes it hard for the industry to comply. Inefficient workflows for storing, retrieving, and redacting data raise costs and slow down important incident responses. This puts both assets and people at risk.

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Why Choose Us?

Our Promise

Multi‑vendor edge rollouts demand consistent governance and trustworthy automation. Our tuned, explainable models and live de‑identification enable safe scale and compliant evidence trails.

Classical Vision

Private by Desig

Survaillence

On‑prem/edge processing with live de‑identification and signed events preserves evidentiary value while minimising personal data.

Explainability

Explainable Alerts

Survaillence

Models tuned for low false positives and operator feedback loops provide transparent reasons and faster triage.

Cross-Disciplinary

Edge Ready

Survaillence

Portable modules deploy across cameras, NVRs, and MEC nodes with consistent governance.

Areas of Expertise

Privacy-preserving video analytics (on-prem/edge)
Real-time PPE/behaviour detection
Automated redaction & signed evidence trails
Explainable alerting for SOCs
Multi-vendor edge governance
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Partner Proposition

Clarity, efficiency and compliance

We help security teams cut false alarms and compliance risk with privacy-first, explainable analytics that run at the edge. Deploy fast, integrate with your VMS/NVR, and scale safely across sites with consistent governance.

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Better intelligence

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Explainable analytics

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Our technological capabilities
are centred around three core pillars:

Computer Vision Services

Transform your processes with advanced visual recognition and analysis. Our services include skills in classical computer vision. We design systems with human supervision for legal compliance. We optimise video pipelines using tools like FFmpeg. We create custom models that can adapt. We also provide explainable AI for ethical transparency.

Generative AI

We are leaders in generative AI, offering optimised inference for faster deployments. This involves using large language models (LLMs) and natural language processing (NLP). These tools help us understand reports and logs written in human language. We design our systems to perform specific tasks with intelligent automation for adaptive workflows and advanced simulation capabilities.

GPU Acceleration

We deliver immersive XR solutions with cross-platform development (Unity 6), GPU performance optimisation, and expertise in NVIDIA Omniverse and CloudXR. We also use reinforcement learning for intelligent XR environments.

Technology Stack

PyTorch
TorchScript
TensorFlow
LiteRT
TensorRT
Face Recognition
ONNX
OpenCV
YOLO
Python
NumPy
SciPy
Numba
C
C++
CUDA
Unity
Unreal Engine
OpenXR
ARKit
ARCore
Vuforia
DeepAR
A Frame
WebXR
OpenCL
Vulkan
DirectX 12
Metal
WebGL
WebGPU
SteamVR SDK
Oculus SDK
Wave SDK
CloudXR
NVIDIA Omniverse
NVIDIA PhysX
PyTorch Lighting
TF-GAN
LangChain
LangGraph
LangSmith
LlamaIndex
W&B Weave
Hugging Face Transformers
LibFewShot
PandaAI
RagFlow
GraphRAG
JAX
Solo-learn
VFormer
Vertex AI Agent Builder
Vertex AI Search
AWS Bedrock
NVIDIA AI Foundry
NVIDIA NeMO
R

Client Testimonials

Frequently Asked Questions

How does your solution integrate with our existing VMS and cameras?

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Our solutions work well together and follow ONVIF profiles T and M. We are experts in improving video quality. This ensures smooth integration with many mixed-heritage camera systems and current Video Management Systems.

How do you ensure your AI models are unbiased and robust?

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We employ rigorous testing and validation processes, and our commitment to explainable AI (XAI) allows for continuous operator feedback. This helps to refine and improve model performance over time while actively mitigating bias.

Can your system perform analytics at the edge to reduce latency and data transfer?

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Yes. Our architecture supports deployment at the edge, on-premise, or in the cloud.

Edge processing is an important part of our plan. It helps reduce delays and lower cloud costs. It also allows for quick responses and improves data privacy.

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.

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 - Fraud Detector Audit (Under NDA)

17/09/2020

Discover how a robust fraud detection system combines traditional methods with advanced machine learning to detect various forms of fraud!

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

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

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