AI Transformation
One-stop shop for AI and ML consulting and managed services
fioriFox takes enterprises from a business problem to production AI and ongoing managed services, across industries.
Industry use cases
Where AI earns its keep, by industry
A working map of the use cases we take from problem to production, grouped by the industries we have shipped in.
Healthcare
- Predictive analytics for patient outcomes
- Medical imaging and diagnostics
- Personalized treatment plans
- Virtual health assistants
- Drug discovery
Finance
- Fraud detection and prevention
- Algorithmic trading
- Credit scoring and risk assessment
- Personalized financial planning
- Chatbots for customer support
Retail
- Personalized recommendations
- Inventory optimization
- Visual search
- Dynamic pricing
- Customer sentiment analysis
Manufacturing
- Predictive maintenance
- Quality control
- Supply chain optimization
- Robotics and automation
- Production scheduling
Transportation and Logistics
- Autonomous vehicles
- Route optimization
- Fleet management
- Supply chain visibility
- Demand forecasting
Education
- Personalized learning
- Automated grading
- Intelligent tutoring systems
- Classroom engagement analytics
- AI-powered content creation
Energy
- Smart grid optimization
- Energy consumption forecasting
- Predictive maintenance for equipment
- Smart building management
- Energy trading
Telecommunications
- Network optimization
- Customer service automation
- Churn prediction
- Fraud detection
- 5G rollout optimization
Hospitality
- Personalized guest experiences
- Dynamic pricing
- Chatbots for reservations and inquiries
- Sentiment analysis
- Predictive maintenance
The journey
From discovery to managed services
A phased path that moves from a business problem to a validated MVP, then to production and ongoing managed services.
- 1
Discovery
- Analyse the business problem and define goals
- Design the architecture and technologies
- Derive the ML problems from the goals, for example regression or classification
- Understand the data required: is it available, where, and how to get it
- Connect to raw data for initial analysis
- 2
Model finalization
- Identify data sources and define the collection process
- Store data and run feature engineering
- Train models across hyperparameters and multiple algorithms
- Analyse performance and select the best-performing model
- 3
MVP
- Deploy the best model on a limited dataset
- Customer stakeholders validate the results
- Customer gives the go-ahead for production
- 4
Production system
- Deploy to production
- Measure effectiveness against the existing method
- Monitor with tools such as Power BI or Tableau
- 5
Managed services
- Model monitoring and data visualization
- Model-drift detection across input features, target variable, and data change
- Handle new use cases and requirements
Discovery to MVP, the business track
Production to Managed Services
How we work
Capabilities across the lifecycle
The platform behind the engagements: data engineering, experimentation, serving, and monitoring, delivered as one practice rather than a stack of tools.
FAQ
Frequently asked questions
fioriFox takes enterprises from a business problem to production AI and ongoing managed services across industries, covering AI consulting and advanced analytics, data engineering, model training and validation, model serving, and continuous monitoring.
An engagement runs from Discovery to MVP and then from Production to Managed Services: fioriFox analyses the business problem, prepares the data and engineers features, trains and selects the best model, validates an MVP with your stakeholders, deploys to production, and then monitors for model drift and new use cases.
fioriFox delivers AI across industries including Healthcare, Finance, Retail, Manufacturing, Transportation and Logistics, Education, Energy, Telecommunications, and Hospitality.
After production deployment fioriFox provides managed services: model monitoring and data visualization, model-drift detection across input features, the target variable, and data change, and handling of new use cases and requirements.