In Data Intelligence we help companies put their data in order before putting AI on top: without knowing what data you have, who governs it and what opportunities it hides, any AI project starts from a false foundation. We diagnose, govern, build and deploy, end to end.
Some of the services within this area of action:
What state is your data in?
Maps where the company's data lives, its quality and its real exposure, before putting AI on top. The mandatory starting point for any serious AI initiative on your own data: without knowing what exists and what state it is in, any later project starts from a false foundation.
For whom: Companies that want to use AI on their own data but do not know what state it is in.
Who is in charge of your data?
Policies, ownership and data lifecycle as the groundwork for any AI initiative. Defines who is responsible for each piece of data, how it is updated, who can access it and under which criteria, preventing each department from answering these questions on its own and differently.
For whom: Mid-sized companies with several departments generating data without a common criterion.
What can you do today with the data you already have?
Identifies which internal processes could benefit from AI applied to the data the company already has, before investing in development. The result is a prioritized map of concrete business cases, not a generic trends report.
For whom: Operations and innovation leads looking for concrete business cases, not technology for technology's sake.
Make your AI answer with your information, not the internet's
Design and construction of retrieval-augmented generation (RAG) systems on top of the company's own documentation and knowledge: manuals, contracts, procedures, project history. The AI stops giving generic answers and starts answering with the real knowledge of the business, in a traceable and verifiable way. Delivered as a packaged service, with scope and price closed from the start.
For whom: Companies that want their AI to answer with real internal knowledge (manuals, contracts, technical documentation) instead of generic answers from a model without context.
Design and construction of the complete infrastructure (pipelines, storage, catalog) and development of the AI use case end to end, from pilot to a solution running in production. Montevive does not stop at preparing the ground: we build the solution that runs on it.
For whom: Companies that already completed an AI pilot and want to scale it, but the data cannot keep up, or that need someone to build the complete solution end to end.
The questions that come up most before putting AI on top of a company's data. If yours is not here, write to us.
With the Data Audit and Assessment: we map where the data is, what state it is in and how exposed it really is, before putting AI on top. It is the mandatory starting point, because without knowing what you have, every later project rests on a false premise.
Not perfect, but known. The AI Opportunity Assessment identifies which processes can benefit from AI today with the data that already exists, and returns a prioritised map of concrete business cases rather than a generic trends report.
It is a knowledge base built on your own documentation (manuals, contracts, procedures, project history) so the AI answers with your business information instead of generic replies, in a traceable and verifiable way. It ships as a packaged service, with scope and price fixed from the start.
We build it. We design the architecture (pipelines, storage, catalogue) and develop the AI use case end to end, from pilot to a solution running in production. We do not stop at preparing the ground.
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