Predictive models, recommendation engines and anomaly detection turned into production systems with monitoring, retraining and clear business metrics.
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Senior Engineers
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Machine learning
Most ML projects die in notebooks. Ours ship: every model we build comes with a serving API, monitoring, retraining pipeline and a dashboard the business reads.
Our data scientists and ML engineers have delivered demand forecasting, particle and image analysis, health insights and fraud signals for clients in retail, manufacturing, finance and healthcare.
We start from the decision the model has to improve and work back to the data, not the other way round.
Who we work with
Demand forecasting, pricing and recommendations.
Predictive maintenance and image-based quality analysis.
Risk scoring, fraud detection and trading analytics.
Patient insights from wearables and clinical data.
ETA prediction, routing and capacity planning.
What we build
Forecast demand, churn, failures and risk with measurable lift over current rules.
Personalised products, content and offers in real time.
Spot fraud, defects and equipment issues before they cost money.
Classification, extraction and search over documents and tickets.
Pipelines, feature stores and warehouses that make ML possible.
Model registry, CI/CD for models, drift monitoring and automated retraining.
Typical challenges
The problems we meet most often in machine learning projects, and how our teams solve them.
Our approach:
We build the pipelines and feature store first, then the model.
Technology
The stack we use for machine learning: proven, maintainable and chosen for your product, not for fashion.
Modelling
Data
MLOps
DockerCloud
AWS
Azure
Google CloudWe combine technical expertise, product thinking and a flexible approach to help businesses build reliable digital products and solve complex challenges with confidence.
Experienced engineers, designers and product specialists working on complex digital products.
We look beyond individual features and consider how technology supports the wider business and user experience.
From full product development to extending an existing engineering team.
We take responsibility for the quality of what we build — from technical decisions to final delivery.
An internal evaluation and observability platform for a fintech's customer assistant: regression suites, LLM-as-judge scoring, production tracing and release gates that let the team ship model changes weekly instead of quarterly.
View Case StudyPowerful 2D and 3D image processing, enhancement and analysis software with extensive measurement and customization features to accelerate material inspection.
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A mobile app and platform based on machine learning that gives users accurate insights into their body and mental state, with personalized training plans and daily routines.
View Case StudyClient needed to develop a trading platform that is stable, efficient, and offers valuable features to traders. The platform needs to provide a seamless chatting experience by dividing rooms based on currency types, allowing traders to communicate and share insights effectively.
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A data-driven solution that uses computer vision to analyze store shelves, providing actionable insights for trade promotion and category management for tobacco products.
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Defect detection for finding defects on objects, then identifying and tracking them. The solution processes visual information and monitors it consistently to support quality control and operational decisions.
View Case StudyLLMs, copilots and RAG embedded into the software and data you already run, with evaluation built in.
Computer vision, generative AI and intelligent automation built around a measurable business outcome.
LLM agents that operate inside your processes with tools, approval gates and audit trails.
End-to-end development of business systems, internal platforms and integrations.
FAQ
Have a project in mind or looking for the right technology partner? Tell us what you're working on, and our team will get back to you to explore how we can help bring it to life.