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About Us
Our Work
Generative & Agentic AI
Why Choose Us?
We're not just your tech team — we're your thought partner. Every collaboration begins with deep understanding, followed by sharp execution.
Leaders in Gen AI
Generative AI
We’ve been mastering generative AI since 2019, with a deep understanding of latent spaces, embeddings, and LLMs.
Model Optimisation for Inference
Our expertise in optimising large model inference ensures faster, more efficient deployments.
Explainable and Verifiable
We prioritise transparency with techniques like RAGs, making your AI solutions explainable and verifiable.
Multi-GPU Optimisation
We fine-tune large models using TensorRT to maximise multi-GPU performance and efficiency.
Ethical and Trustworthy
We ensure compliance with regulations while mitigating bias to create fair and ethical AI systems.
Reduced Onboarding Costs
Our use of self-supervised techniques minimises onboarding costs and streamlines adoption.
Intelligent Automation
We design agentic AI workflows, automating tasks and empowering dynamic, adaptive systems.
Scalable Custom Solutions
Our company is proud to offer solutions that are designed for optimal scalability, ranging from data management to computational performance.
Advanced Simulation
Our capabilities in simulation and prototyping accelerate testing and bring your ideas to life faster.
Built Together
We are a team that brings unique expertise in generative and agentic AI, making every step of the process enjoyable and collaborative. We don't just build powerful AI systems — we share our knowledge and refine solutions with you. Communication is at the core of our approach, and we are constantly seeking to optimise our processes to deliver results!
expertise in Generative AI with a creative mindset
open knowledge-sharing every step of the way
continuous communication, real outcomes
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
The choice depends on your specific balance of novelty, cost, and data privacy. TechnoLynx helps you navigate this decision:
No, limited data is rarely a blocker. TechnoLynx employs advanced techniques to overcome data scarcity and build robust models, including:
We build scalability into the architecture from day one using a hybrid approach:
TechnoLynx specializes in multimodal Generative AI, handling diverse data types including:
No — LLMs are one family inside a much broader generative landscape. Diffusion models, GANs, VAEs, and audio/video/3D generators all solve different deployment-constrained problems, and the right architecture depends on data, latency, and compute budget rather than on which family is currently fashionable. Picking the wrong family is a common cause of feasibility failure — see generative AI beyond LLMs and how to evaluate GenAI feasibility before you build.
20/04/2026
Most GenAI use cases fail at feasibility, not implementation. Assess data, accuracy tolerance, and integration complexity before building.
27/04/2026
A working GenAI prototype is not production-ready. It still needs evaluation pipelines, guardrails, cost controls, latency optimisation, and monitoring.
22/04/2026
LLMs dominate GenAI, but diffusion models, GANs, VAEs, and neural codecs handle image, audio, video, and 3D generation with different architectures.
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.
2/05/2026
Selecting an agent framework for partial on-device inference: four axes that decide whether a desktop-class framework survives the edge-target boundary.
26/04/2026
Agent frameworks differ on observability, tool integration, error recovery, and readiness. LangGraph, AutoGen, and CrewAI target different needs.
25/04/2026
Multi-agent AI decomposes tasks across specialised agents. Conflicting plans, hallucinated handoffs, and unbounded loops are the production risks.
24/04/2026
Generative AI produces output on request. Agentic AI takes autonomous multi-step actions toward a goal. The core difference is execution autonomy.
23/04/2026
GANs produce sharp output in one pass but train unstably. Diffusion models train stably but cost more at inference. Choose based on deployment constraints.
21/04/2026
GenAI project failures cluster around scope inflation, evaluation gaps, and integration underestimation. The patterns are predictable and preventable.
19/09/2025
Make AI systems validation‑ready across GxP. GMP, GCP and GLP. Build secure, audit‑ready workflows for data integrity, manufacturing and clinical trials.
17/09/2025
Edge imaging transforms cell & gene therapy manufacturing with real‑time monitoring, risk‑based control and Annex 1 compliance for safer, faster production.
11/09/2025
Improve quality and safety in sterile injectable manufacturing with AI‑driven visual inspection, real‑time control and cost‑effective compliance.
5/09/2025
AI helps pharma teams predict clinical trial risks, side effects, and deviations in real time, improving decisions and protecting human subjects.
1/09/2025
Generative AI transforms pharma by streamlining compliance, drug discovery, and documentation with AI models, GANs, and synthetic training data for safer innovation.
27/08/2025
AI helps pharma teams improve compliance, reduce risk, and manage quality in clinical trials and manufacturing with real-time insights.
31/03/2025
Discover how Markov chains power Generative AI models, from text generation to computer vision and AR/VR/XR. Explore real-world applications!
2/01/2025
LLMOps optimisation: profiling throughput and latency bottlenecks in LLM serving systems and the infrastructure decisions that determine sustainable performance under load.
10/06/2024
Diffusion networks explained: the forward noising process, the learned reverse pass, and how these models are trained and used for image generation.
6/10/2023
With the hype of generative AI, all of us had the urge to build a generative AI application or even needed to integrate it into a web application.
26/04/2023
Traditionally, drug discovery is a slow and expensive process that involves trial and error experimentation.
