Data transformation
Giving your data its due by eliminating silos, democratising access and communicating insight across the organisation. Getting the infrastructure straight is what lowers the cost of every insight after it.
Data science services and solution development
Tap into data science services built to create a holistic data system — one that delivers insight rather than another dashboard nobody opens.
Your data, your toolsBenchmarked vs current processFrom 4 weeks
Foundation
A solid data foundation for your business model
Cross-functional data science and analytics at the intersection of current technology and capability that has actually shipped.
Machine learning
Matching your analytics challenges to the right supervised, unsupervised or reinforcement learning algorithm, then delivering solutions that run on their own.
Neural networks and deep learning
Deep learning expertise applied to forecasting, fraud detection and speech recognition — built for your project rather than adapted from a demo.
Natural language processing
Making sense of customer signals across every touchpoint, whatever the format, volume or complexity.
BI and visualisations
Sharpening performance by keeping teams focused on one outcome and putting insight in context, so it can actually be acted on.
Cloud environments
Migrating assets to a scalable, secure, innovation-ready foundation, and right-sizing cloud resources so the bill stays defensible.
Business cases
Data science solutions across business cases
The right tools for business challenges of any complexity.
AI language models
Custom language models built on a combination of AI and NLP. Automate customer service with interaction that reads as human, understand what customers actually mean, and reduce the administrative load.
- Solutions built on GPT-class models
- Sentiment analysis
- Natural language generation
- Document processing
Customer analytics and personalisation
Analytics and AI combined into custom models that size up your customers and your markets, so you can operate accordingly. Adapt to changing behaviour in real time and get value out of interactions.
- Unified analytics for omnichannel
- Customer behaviour analytics and prediction
- Customer segmentation
- Advanced analytics for CRM
Predictive analytics
Identify future trends, bring clarity to resource allocation, and increase production capacity by spotting emerging issues before they become incidents.
- Demand forecasting
- Risk calculation
- Fraud detection
- Predictive maintenance
Recommendation systems
Connect with customers at a level that supports smarter sales decisions and puts attention on the right products or services.
- Collaborative filtering
- Content-based filtering
- Hybrid recommendation systems
- Integration with existing software
Embedded operational intelligence
A better handle on real-time data and a shorter time to insight. Record and deliver performance analytics in a split second, and act on dynamic signals instead of historical ones.
- Real-time analysis
- Analysis of imagery and video
- IoT input analysis
- Stream processing and big data platforms
Optical character recognition
Simplify data entry, make document classification workable, and streamline the back end of the business. OCR development for multiple business cases and formats.
- Unstructured OCR scanning
- Structured data capture
- Optical barcode recognition
- Character recognition on raw images
Engagement
Data science as a service
The latest analytics capability without building the in-house competency first.
Strategy and consulting
Professional advisory on data science and software development from people who have shipped it. We help shape the strategy, estimate upcoming projects and pick the technology.
- Data science consulting
- Machine learning consulting
- Business case analysis
- Project planning
Data engineering
High-performance infrastructure that supports better decisions and adds traceability to your information flows. We prepare your existing input for model development and optimise how data is managed.
- Database and warehouse optimisation
- Platform migration
- Data discovery and augmentation
- ETL pipeline development
Solution development
ML engineers train and validate models, then deploy them in a tailored application. Following a ModelOps approach, that becomes a continuous operational cycle rather than a one-off handover.
- Collection and exploration
- Custom model development
- Model training and evaluation
- Data science app development
Maintenance and optimisation
Protecting the long-term value of the investment by building models that address evolving challenges. We monitor performance, enrich with new input, and re-evaluate accuracy continually.
- Model performance monitoring
- Data consistency analysis
- Model enrichment
- Stability monitoring and drift prevention
Stack
Technologies and tools
The tooling our data scientists reach for, and the new things we are testing.
Why us
Why teams work with InfuseAI
Data first, model second
Most AI problems turn out to be data problems wearing a disguise. We check that before proposing a model.
Senior people, directly
Senior data scientists and engineers on the work, not a junior team behind an account manager.
Benchmarked honestly
Every model is compared against your current process on held-out data, including the cases where it loses.
Yours at handover
Code, pipelines, trained models and documentation transfer to you. No license-back.
Start here
Tell us the problem. We'll tell you if it's worth solving.
Thirty minutes with an engineer, not a salesperson. You leave with a rough scope, a cost band and an honest read on feasibility.
30 minutes with an engineer · No slide deck · Reply within one business day