As an AI and machine learning development company, we help you harness machine learning algorithms and current artificial intelligence tools and technologies to solve real business problems.
We start from your business goals and match them to what machine learning can realistically deliver, bringing years of combined experience in building AI-powered software.
Machine Learning
Using supervised, unsupervised and reinforcement learning, neural networks and deep learning, we build systems that learn from your data, with people in charge of key decisions.
Natural Language Processing
We build real-time speech recognition and conversational AI software that makes products easier and faster to use.
Computer Vision
From biometric authentication to CCTV monitoring and live video analysis, we develop computer vision software that recognises and interprets visual information.
Artificial intelligence can transform how a business runs. Here are a few examples of how our AI consulting and development services improve efficiency and the bottom line. For large language models and generative AI, see our LLM and generative AI development services.
Big Data driven ML models
ML models trained on 30 million+ utility meter records to cleanse data, remove duplicates, check mismatches and analyse error patterns.
Manual task automation
Optical character recognition (OCR) and data capture solutions that extract information from documents to eliminate manual processes.
Health insights prediction
Deep learning models that recognise patterns of health deterioration in an individual patient, using symptom, physiology and biologics data.
Vision Systems and Sensors
General-purpose vision systems, sensors, cameras and components for machine vision inspection.
In-Process Inspection Machines
Dynamic vision systems for in-process quality control in the automotive industry.
Quality Inspection Machines
Inspection machines for high-speed quality control.
We believe successful AI and machine learning adoption is a journey rather than a single build. These seven steps take a project from a clearly defined problem to a model that is monitored and improved in production. If you are still deciding where AI fits, our AI strategy and consulting service starts a step earlier.
Define the use case
Every project starts by clearly defining the problem or challenge we are helping the organisation to solve with AI.
Verify data availability
Once the use case is clearly defined, we check that the processes and systems in place can capture and track the data needed for the analysis.
Explore the data
We undertake a data exploration exercise to validate assumptions and understanding, making sure the data tells the right story based on subject matter expertise.
Build the model
We run tests to find which variables or features matter most, to validate the hypothesis and improve performance. Domain and business experts are involved throughout, giving continuous feedback to create a successful machine learning model.
Validate the model
We define performance measures to evaluate, compare and analyse results from multiple algorithms, and use them to refine the most promising models.
Automate and deploy
Once the model has been built and validated, it is rolled out into production, starting with a limited rollout of a few weeks or months. Business users give continuous feedback on the model’s behaviour and outcomes before it is rolled out to a wider audience.
Evaluate and refine
Once a model has been deployed, it is continuously monitored, so the organisation can check it remains valid and update it as required.
Technology
Utilities
Healthcare
TRUSTED BY SOME OF THE WORLD’S BEST TEAMS
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