Bidatia
Data iceberg: what shows above the water and everything that supports it below

Data · AI · Real Impact

We put AI to work for your business

We automate and optimise your key processes with reliable data, scalable architectures and full compliance with European artificial intelligence regulation.

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We help you with AI strategy, AI agents, Process automation, Assistants with your knowledge, Dashboards, Data governance, Data quality, Data architectures, Odoo and digitalisation, Public tenders with Radar, Project profitability with TIME, Data load monitoring with AlmIA, and we work with Microsoft Fabric, Power BI, Azure AI Foundry, Claude, ChatGPT, Gemini, Databricks, Snowflake, Purview, OpenMetadata, erwin by Quest, Odoo, n8n.

WHY BIDATIA

AI creates value when it improves the business

Responding to a customer sooner. Automating tasks that eat up hours. Finding the knowledge we need. Making decisions with reliable information.
That is what matters.
To get there you need the right processes, quality data, integration, governance and people ready to use the technology.
At Bidatia we connect all those pieces to take AI from potential to results.

Choose what you want to achieve:

What it takes to «serve your customers faster and better»

  • Clear processesWe know which steps there are, who decides and where AI adds value before touching the technology. Essential for this goal.
  • Reliable dataA single record per customer, product or order, with its quality measured and an owner.
  • Connected systemsERP, CRM, email and documents talk to each other, with no keying in the same thing twice.
  • Accessible knowledgeThe company's documentation and experience, available to whoever needs it, with the source cited. Essential for this goal.
  • People supportedTraining and change management so the team uses the solution and can carry on alone. Essential for this goal.
  • Control and compliancePermissions, traces and regulation (GDPR, Spain's ENS and the EU AI Act) sorted from the start.
  • Measured resultsHours saved, sales or errors before and after: AI is justified with numbers.

SERVICES

Seven lines of work, one team

We help companies gain competitive advantage and operational improvements by integrating data and AI into their processes.

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And we advise on funding and grants so public funding covers part of the investment.

HOW WE SUPPORT YOU

We help you get the most out of AI

IMPACT AI™ · From curiosity about AI to measurable, governed and sustainable adoption.

We don't leave you with a demo. With IMPACT AI™ we go through six phases with you, each with a decision and a deliverable, until AI is used in your processes, its results are measured and your team can carry on alone.

  1. Identify

    We interview leadership and the people doing the work, and map real processes and friction.

    Decision 1: Do we understand the problem and the opportunities?

    Deliverable: AI Opportunity Canvas™ and Process & Pain Map™

  2. Measure

    We measure readiness across six dimensions, backed by evidence, and data maturity with UNE 0080.

    Decision 2: Is the company ready?

    Deliverable: AI Readiness Index™ and gaps to close

  3. Prioritize

    We score value, feasibility, adoption, effort and risk, and decide GO / NO GO.

    Decision 3: Which case deserves to go first?

    Deliverable: AI Opportunity Portfolio™ and GO / NO GO decision

  4. Activate

    We train the team on the use case itself and pilot with controlled scope and defined KPIs.

    Decision 4: Does the solution prove its value?

    Deliverable: Use Case Canvas™, Pilot Charter and measured result

  5. Consolidate

    We measure usage, efficiency and business impact, and adjust adoption.

    Decision 5: Is it used and does it deliver results?

    Deliverable: Adoption Plan, AI Governance Lite™ and Success Dashboard

  6. Transfer

    We leave capability in place by role, plus a backlog, owners and a roadmap.

    Decision 6: Can the company carry on?

    Deliverable: AI Action Plan™ and roadmap

Explore IMPACT AI™ in detail

CASE STUDIES

Real problems, solved in production

Representative examples of our work. Clients remain anonymous.

See all case studies

Furniture and interior design company

AI furniture design with automatic quoting

Challenge
Customers could not picture how the furniture would look in their home, and every interior design proposal and its quote was prepared by hand, with days of waiting before they had a clear idea of the result and the price.
Solution
An AI interior designer embedded in their website with FastRender: the customer uploads a photo of the room, picks pieces from the catalogue or asks for a set matched to their budget, and the AI generates several proposals on their own photo, which they can adjust with “Request a change”. Each design works out the list of pieces and a preliminary quote with the catalogue prices.
Result
Customers see their space furnished with real catalogue products and a price estimate in minutes, and the sales team receives the opportunity with the photo, the design and the quote ready to close.
  • FastRender
  • Generative image AI
  • Furniture catalogue
  • Quote calculation
FastRender

Diversified business holding

From SAP to a lakehouse in Microsoft Fabric

Challenge
Reports spread across SAP R/3, SAP BusinessObjects, several ERPs and CRMs. Without a single analytics environment, there was no way to add advanced analytics or contain licensing costs.
Solution
Analysis of the reports, roadmap and management model; a new architecture, migration of the developments to a lakehouse in Fabric with integrity validation, auditing and load control, row- and column-level security for sensitive data, and data governance implemented on Azure with Purview.
Result
Centralised reports, lower licensing and development costs, an analytics layer for self-service and data services for third parties, and a foundation ready for machine learning.
  • Microsoft Fabric
  • Power BI
  • Purview
  • SAP R/3
  • SAP BusinessObjects
  • PySpark
Data platforms

International door-to-door logistics operator

AI-powered digital platform on top of the ERP

Challenge
More than 30 price requests a day by email and phone, rates requested by hand from five or six suppliers with up to two days' wait, consolidation in Excel and no shipment visibility for the client.
Solution
External quoting and booking portal, internal rates portal, automated quoting engine and control tower on top of the ERP, with predictive analytics and data governance.
Result
Clients quote, book and track their shipments without calling, and rates go from two days of emails to a real-time comparison panel. A 24-month programme in two-week sprints.
  • Odoo
  • Python
  • Predictive analytics
Odoo and business digitalisation

Real-time digital advertising company

Migration to a cloud-native architecture with Databricks

Challenge
The data and analytics platform was not keeping pace with business growth: integration and reporting processes needed modernising, and the teams had no experience with the new technology.
Solution
Target architecture on AWS, migration of the integration and reporting processes to Databricks, and knowledge transfer to the teams.
Result
Scalable storage with orchestrated pipelines, a foundation ready for machine learning, and the client's teams running operations autonomously.
  • AWS
  • Databricks
  • Python
Data platforms

HR department of a city council

AI assistant for Human Resources in Microsoft Teams

Challenge
More than 60 requests a week from staff about sick leave, absences, holidays and the collective agreement. Every query and every supporting document was read, interpreted and classified by hand.
Solution
A conversational assistant in Teams with RAG over the collective agreement and three years of real requests, which processes attached documents and asks HR for approval when in doubt.
Result
Immediate answers for employees with the source cited, less repetitive work for HR, and human decisions where they are needed. A foundation that can be extended to other internal procedures.
  • Microsoft Teams
  • RAG
AI automation

Large local authority with its own data office

Selecting the data and AI governance tool

Challenge
From among the leading data governance tools on the market, the one that best fitted the client had to be selected to govern BigQuery and the dashboards, and to integrate the data governance tools available in the cloud.
Solution
Maturity assessment, requirements catalogue and weighted scoring matrix; ten tools evaluated with the vendors and cross-checked with Microsoft, Google and Anjana.
Result
Three finalists and a reasoned decision, reusable criteria, and compliance assessed against UNE 0077-0080, UNE 0085 and the EU AI Act.
  • Microsoft Purview
  • BigQuery
  • Power BI
  • Fabric
Data governance

Several ministries of Spain's central government

Common criteria for choosing a data governance tool

Challenge
Data governance initiatives running in parallel across different ministries, with no common criteria for choosing a tool and the requirement to fit public administration regulations.
Solution
Gathering of functional and technical requirements for each ministry, comparison of the tools on the market, open-source ones included, assessment of data maturity against the UNE standards and a recommendation for each usage scenario. Theoretical and hands-on training on real cases, and support during roll-out.
Result
A decision backed by consistent criteria reusable across ministries, and a basis for starting implementation without redoing the analysis.
  • Requirements
  • Market comparison
  • Open source
  • UNE 0077-0079
Data governance

Public body managing data from more than 200 organisations

Purview and automatic documentation with AI

Challenge
Fabric, SQL Server, AWS S3 and Purview coexisting, unmonitored loads, no guaranteed quality, and knowledge concentrated in suppliers that was lost with every turnover.
Solution
Maturity audit and target organisational model, phased roadmap, Purview with domains, data products and glossary, and AI accelerators to document the models.
Result
Documentation generated automatically with minimal supervision, owners and roles identified, a two-year roadmap and a self-sufficient technical team.
  • Microsoft Purview
  • Fabric
  • SQL Server
  • AWS S3
Data governance

Bank

Data governance and information architecture

Challenge
More than 60,000 tables neither classified nor organised by subject area, with no catalogue accessible to the business and no common modelling criteria.
Solution
Classification by subject area with erwin Data Modeler, a catalogue for business and technical users, an architecture review and a methodological framework based on DAMA and Kimball.
Result
A governance methodology applicable to every platform, data the business can understand, and modelling defects identified.
  • erwin Data Modeler
  • Teradata
  • DAMA
  • Kimball
Data governance

Multinational executive search and recruitment firm

Operations dashboard connected to the database

Challenge
The dashboard read from manually generated Excel files, with no history to compare KPIs and a model full of unused fields and relationships.
Solution
A gateway on AWS to connect Power BI directly to the database, a redesigned model, three years of history and global filters by sector, business unit and client.
Result
Up-to-date data without manual files, historical comparisons and consistent KPIs, and users trained to make the most of it.
  • Power BI
  • AWS
Data and analytics

Road passenger transport operator

AI transformation roadmap

Challenge
A growth plan with technology as an ally, and the need to know which processes to improve and what AI could automate across the company.
Solution
Review of processes in Operations, IT, Sales, Finance and HR through workshops and sessions with management, and a technology recommendation for each challenge: generative AI, RAG, agents and hyperautomation.
Result
Specific reports and roadmaps for each area, with the AI use cases prioritised.
  • Generative AI
  • RAG
  • Agents
Digital strategy

Specialist veterinary clinic

Digitalisation plan for clinical and administrative processes

Challenge
Processes with a lot of manual handling, clinical and financial information scattered across tools, and no management indicators.
Solution
Automation opportunities, document digitalisation, integration of clinical and financial information, target processes and management indicators.
Result
End-to-end traceability, less administrative work, and decisions based on data rather than impressions.
  • Automation
  • Dashboards
Digital strategy

Public university

Governance portal for a federated data space

Challenge
The use cases depended on proprietary GIS technology, creating barriers to entry for new municipalities, and the chain of trust and the catalogue had to be managed autonomously.
Solution
A neutral governance portal, software for the provider, promoter and consumer roles, a federated catalogue on EDC and the DSP protocol, and GAIA-X credentials.
Result
New municipalities join without GIS licences, and the governance logic lives in the data space itself.
  • EDC connectors
  • DSP protocol
  • GAIA-X
  • Python
  • PostgreSQL
  • Docker
Data platforms

Financial advisory firm

Automated email and document processing with AI

Challenge
Hours every day sorting email and keying in invoice and case file data.
Solution
Classification and routing of incoming email, document extraction and case file matching with AI.
Result
The team reviews exceptions instead of typing data.
  • Document extraction
  • n8n
AI automation

Professional services consultancy

Project profitability and working-time recording with TIME

Challenge
Hours were logged in spreadsheets and clocking-in lived in a separate system: no visibility of which projects and clients made money, no reconciliation between clocked and logged hours, and the legally required working-time record handled by hand.
Solution
Roll-out of TIME: daily time logging per project, date-based rates and costs, margin and utilisation reports by project, client and person, and electronic recording of each employee's working day (clock-in, clock-out and breaks) with the official work calendar and a monthly report ready for a labour inspection.
Result
Staffing and pricing decisions based on real margin, clocked and logged hours in one place, and a digital working-time record ready to adapt to Spain's upcoming working-time recording rules.
  • TIME
  • Time recording
  • Margin reports
TIME

Regional cybersecurity agency

A data governance model with a first data domain and product

Challenge
Many data sources at different levels of maturity and an architecture not designed to govern them: no shared view of what data existed, who was accountable for it and how to use it with confidence.
Solution
Assessment of the maturity of the data sources and of the existing architecture, gap analysis, design of the architecture supporting data governance, and roll-out of the model with a first data domain and product.
Result
A data governance model in place, prioritised gaps and a working data product that serves as the pattern for the next domains.
  • Data maturity
  • Data architecture
  • Data domains and products
Data governance

Spanish central government ministry

Data governance training and OpenMetadata roll-out

Challenge
Technical and business teams had to take on data governance without a shared set of concepts or a catalogue tool in place.
Solution
Training sessions for technical and business teams on data governance methodology and techniques, and roll-out of OpenMetadata as the catalogue.
Result
Teams sharing the same data governance language and criteria, and a working open-source catalogue to build on.
  • OpenMetadata
  • Training
Data governance

Diversified business holding

From SAP BusinessObjects to Power BI on Microsoft Fabric

Challenge
The group's dashboards lived in SAP BusinessObjects on top of SAP R/3: expensive to maintain, slow to evolve and hard to combine with the rest of the group's data.
Solution
Migration of the reporting layer to the Microsoft Fabric ecosystem: load notebooks in PySpark and new Power BI dashboards, with semantic models and row- and column-level security.
Result
Power BI dashboards on the group's lakehouse, a single version of the data and a report catalogue that is easier to maintain and extend.
  • Power BI
  • Microsoft Fabric
  • PySpark
  • SAP BusinessObjects
  • SAP R/3
Data and analytics

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CONTACT

Tell us what you want to achieve

In a first 30-minute conversation we review your case and tell you where we'd start. No strings attached.