Visual Computing for
Life Sciences

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10×–300×
Faster Simulation Speedups

GPU-accelerated computing for R&D modeling

30–40%
Lower Cost Reduction

Predictive maintenance cuts downtime expenses

Up to 90%
Shorter Development Time

Digital twins accelerate scale-up and process design

100%
Coverage, Quality Inspection

AI vision ensures 100% inspection zero label errors

Accelerating Innovation with Regulatory Complience

TechnoLynx helps pharma and biotech companies boost R&D, optimise manufacturing, and ensure quality using advanced AI and high-performance computing. We solve industry challenges-like contamination prevention and faster drug discovery-while meeting strict regulations. Our solutions deliver faster market entry, higher yields, fewer failures, and stronger compliance.

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What We Deliver

TechnoLynx combines technical innovation (AI, machine learning, computer vision, GPU computing) with business impact (cost and time savings, risk reduction, productivity).

AI-Powered Aseptic Operations

Real-time AI vision monitors sterile production, catching errors before contamination occurs. Prevents costly batch failures and ensures compliance.

R&D Acceleration

HPC and AI accelerate simulations by 10-300×, enabling faster drug discovery, quicker breakthroughs, and reduced time-to-clinic.

Manufacturing Optimisation

Machine learning maximises yield and minimises downtime, improving output and consistency. Predictive analytics enable proactive maintenance, cutting downtime and costs by ~30-40%.

Digital Twins

Virtual simulations and digital replicas enable risk-free experimentation, reducing commissioning time and shortening development cycles by up to 90%.

Automated Visual Quality Control

AI vision systems inspect every product and package, ensuring 100% quality control, zero defects, and preventing costly recalls.

Data Mining for Innovation

AI analytics uncover patterns in vast datasets, guiding insight-driven innovation, accelerating research, and enabling faster product development and IP creation.

Areas of Expertise

Cleanroom CV & Annex 1 compliance
Protocol-deviation early warning (RBQM)
CGT in-process imaging at the edge
GxP data pipelines & validation (CSV)
MES/EBR/SCADA integration

How It Works:

The Technology Behind the Impact

Solves

Approach

Example

Our Technological Capabilities
Are Centred Around Three Core Pillars

Computer Vision Services

Transform your processes with advanced visual recognition and analysis. Our services feature expertise in classical computer vision, human-supervised system design for legal compliance, video pipeline optimisation with tools like FFmpeg, custom adaptable models, and explainable AI for ethical transparency.

Generative AI

We are leaders in generative AI, offering optimised inference for faster deployments, ethical AI systems with bias mitigation, intelligent automation for adaptive workflows, and advanced simulation and prototyping 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 can your system be validated for use in a GxP environment?

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We develop our solutions with a "validation-ready" mindset. We offer complete documentation and support for IQ/OQ. Our focus on explainable AI ensures our systems meet strict data integrity and audit trail rules. Annex 11 and 21 CFR Part 11 provide these rules, and people recognise them in the United States and around the world.

How does your cleanroom monitoring respect employee privacy?

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We prioritise privacy by design, focusing on process compliance without biometric identification. We are skilled in designing systems that involve human supervision. This means we handle all data following strict GDPR and GMP rules for data integrity.

Can your AI models adapt to our specific assays and imaging hardware?

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Yes. Our custom models are adaptable to diverse platforms. We specialise in creating strong, adaptable models. We can adjust them to work best with your lab conditions and tools.

Do your solutions comply with Annex 1 and 21 CFR Part 11 requirements?

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Yes. Our systems are engineered for Annex 1 cleanroom monitoring and Part 11 electronic records and signatures. We provide audit trails, role‑based access control, and change management features aligned with these regulations.

How do you ensure explainability and transparency in AI decisions?

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We include model cards, feature attribution, and fairness metrics as part of our xAI Governance Toolkit. This allows QA and regulatory teams to review and justify AI outputs during audits.

How do you handle latency and performance for real‑time visual inspection?

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We leverage GPU‑optimised pipelines, asynchronous compute, and multi‑GPU orchestration to achieve deterministic low latency. Our solutions are benchmarked for high throughput without compromising compliance.

Do you offer GPU acceleration for AI‑driven analytics in life sciences?

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Yes. We use CUDA, TensorRT, and vendor‑neutral optimisations to accelerate inference for imaging, QC, and clinical analytics. This ensures faster processing while maintaining validation‑ready controls.

How do you manage data integrity and audit readiness?

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All data handling follows ALCOA+ principles. We provide signed logs, versioned configurations, and exportable compliance snapshots for audits and regulatory submissions.

Can you support cloud, on‑prem, and hybrid deployments?

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Yes. We offer on‑prem and edge deployments for privacy‑sensitive environments, as well as hybrid architectures for scalability. All deployments include deterministic builds and signed binaries for compliance.

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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