Give the business the foundations to scale AI: governed data, answers accessible to business teams and a controlled platform, compliant with European regulations, with costs and energy consumption managed.
Start with actual work
Metrics conflict, BI requests accumulate or each project rebuilds its own components. You need to control access, response quality and costs while making AI easier to use.
A target architecture and deployment roadmap; shared AI services; an access and evaluation framework; performance and cost monitoring; and skills transfer.
Data and response reliability, component reuse, deployment lead time, availability, adoption and cost per use.
AI in practice
International banking group
Polynom defined target architecture, a migration roadmap and shared services: model access, search and memory. Ownership and access governance support implementation.
Explore the caseMajor retailer
With Synchrone, Polynom formalised questions and analysis methods, structured metrics and semantic views, then built the conversational journey. Answers are evaluated against reference figures and business approvals.
Explore the caseConfidential client
Polynom defined a data strategy and a data lake to organise scattered data. The result is a deployed data foundation.
Explore the caseFAQ
Architecture is defined around your hosting, access and integration requirements.
We size the foundation around priority use cases and the scaling roadmap.
Analyse actual work, data and constraints. Design the target operating process with teams and define success criteria.
Build an initial solution and test it with users. Measure benefits, quality, risks, costs and energy consumption.
Integrate the solution into operations, prepare teams and organise its running. Monitor use and improve both agents and processes.
A clear need or an early idea? Start with a conversation. We will reply within a few days.
