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AI, automation and conversational BI

Use cases chosen for their value, automated processes and natural-language answers, on certified data

In brief

Indicative duration
2 to 4 weeks of workshops, 6 to 10 weeks of prototyping
Format
Fixed price per phase
Method step
Step 4, Create value

Who it is for

  • Companies whose AI prototypes never reach production
  • Leadership teams that want their people to refocus on their core business
  • Users who want to query their data without building a report

The problem we solve

An AI model reproduces the flaws of the data it is fed. Without certified, documented data, AI projects shine in demos and stall in production

How we work

  1. Value and feasibility workshops: use cases prioritised by impact and data availability
  2. A prototype on your data, with measurable success criteria
  3. Industrialisation: integration into processes, monitoring, security
  4. Conversational BI on your documented semantic models

What you get

  • A prioritised portfolio of use cases
  • An evaluated prototype
  • Industrialised automations
  • Conversational BI on a first domain
  • Value tracking in production

Tools

Microsoft Fabric, Power BI, Databricks, Snowflake, and your platform’s AI services

Frequently asked questions

What is conversational BI?

Asking your data a question in natural language, for example “Which regions are growing fastest this quarter?”, and getting a figure as the answer. It relies on documented semantic models

Is our data ready for AI?

The free online assessment gives you a first answer in 15 questions

Take the free assessment

Let’s talk about your data

30 minutes to review your context and identify the first useful project

Data documentation and certification

A catalogue, KPIs defined once and certified datasets

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Data, BI and AI readiness assessment

A scored baseline and a prioritised action plan

Learn more

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