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Industries
About Us
Our Work
Industry Landscape
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
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.
Why Choose Us?
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.
Private by Design
Surveillance
On‑prem/edge processing with live de‑identification and signed events preserves evidentiary value while minimising personal data.
Explainable Alerts
Models tuned for low false positives and operator feedback loops provide transparent reasons and faster triage.
Edge Ready
Portable modules deploy across cameras, NVRs, and MEC nodes with consistent governance.
Partner Proposition
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.
Better intelligence
Explainable analytics
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.
We are leaders in generative and agentic AI, with optimised inference for faster deployments. We combine LLMs and natural language processing (NLP) to parse reports and logs written in human language, then orchestrate autonomous agents that triage, summarise and route alerts — with advanced simulation capabilities for design and rehearsal.
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.
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
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
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
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
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
We prioritize seamless interoperability through industry standards. TechnoLynx solutions are compatible with ONVIF Profiles T and M, ensuring smooth integration with:
We maintain model integrity through Explainable AI (XAI) and "Human-in-the-Loop" feedback. Our robustness strategy involves:
Yes. Our architecture is designed for Edge, On-Premise, and Hybrid deployments.
Edge processing is a core component of our strategy to reduce latency and lower bandwidth costs. By processing video at the source, we enable near-instantaneous alerts and ensure sensitive data remains within your local network, significantly improving privacy.
Through modular, instrumented pipelines — not by tuning a single monolithic model. False alarms compound from several stages (detection, tracking, classification, scene context, alert policy), so we engineer each stage to be independently observable and explainable. Operators can trace why an alert fired, which is what builds trust and lets the system be improved over time — see why AI video surveillance generates false alarms.
28/04/2026
Surveillance false alarms are an architecture problem, not a sensitivity setting.
30/04/2026
Operators stop trusting CV alerts when the pipeline is opaque. Observable, modular CCTV pipelines decompose decisions into auditable stages.
Naive GPU porting of sequential RF simulation delivers modest gains. Algorithmic redesign to expose parallelism turns multi-day runtimes into hours.
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.
10/12/2024
Hierarchical SKU classification using DINO embeddings and few-shot learning — above 95% accuracy at ~1k classes, above 83% at ~2k.
20/11/2024
Browser-deployed face quality classifier rebuilt around a single multiclassifier, WebGL pixel capture, and explicit device-capability gating.
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.
15/07/2024
In-cart perception for autonomous retail checkout: detection, tracking, adaptive FPS sampling, and a session-scoped cart-state model.
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.
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.
15/10/2023
Camera-based barcode pipeline for in-cart capture: YOLO localisation, ensemble decoding, multi-frame polling — 86.7% vs Dynamsoft 80%.
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.
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.
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.
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.
