Machine Learning & AI

Production-grade models, deployed and maintained

Machine learning is no longer an experimental capability — it's woven into operations across finance, retail, healthcare, logistics, and beyond. As deployment has become easier and inference costs have dropped, the bar for what counts as a competitive ML feature keeps rising.

You no longer need to build every model from scratch. Three deployment layers now exist:

  • Managed ML platforms for classical ML and computer-vision workloads — AWS SageMaker, Google Cloud AI, Azure Machine Learning.
  • Hosted LLM APIs for conversational AI, retrieval-augmented generation (RAG), and agentic workflows — Claude, ChatGPT, Gemini, DeepSeek.
  • Open-source models for privacy-sensitive deployments in your private cloud or on-premises — DeepSeek, Kimi, Qwen, Llama, Mistral.

Vantino designs and ships across all three. We help you pick the right layer for each use case — managed pipelines where total cost of ownership matters, hosted APIs where speed of integration matters, and self-hosted open-source models where data sovereignty rules out external services.

How can your business benefit from ML and AI?

Financial sector

  • Fraud detection: learn from past patterns and live signals (transaction, location, device, graph) to flag fraud in real time.
  • Credit assessment from audited statements and alternative-data signals.
  • Forecasting: cash flow, churn, demand planning.
  • LLM-powered analysis: summarise filings, extract contract clauses, generate first-draft memos.

Retail & e-commerce

  • Recommender systems: surface the right product at the right moment.
  • Consumer segmentation: predict conversion likelihood, personalise offers, lower churn.
  • Generative product content: descriptions, image captions, SEO copy at scale.
  • Conversational shopping: LLM chatbots grounded in your catalogue (RAG).

Healthcare

  • ML diagnostic tools (imaging, structured EHR).
  • Clinical-knowledge assistants grounded in your guidelines (RAG over protocols and SOPs).
  • Document summarisation of records and trial reports.

Customer support & operations

  • LLM chatbots grounded in your knowledge base — accurate, citable, on-policy.
  • Ticket triage, intent classification, auto-drafted responses for human review.
  • Internal search across wikis, contracts, tickets via RAG.

Marketing

  • Sentiment analysis across reviews and social.
  • Generative copy variations for A/B testing and localisation.
  • Propensity modelling and audience segmentation.

Security

  • Anomaly detection and authentication.
  • Log triage and alert summarisation with LLMs.

These are the industries we work with and examples of solutions that benefit our clients — with machine learning the options keep expanding, so don't hesitate to contact us for an individual consultation.

More details on our Machine Learning & AI Consulting page.