01 What it includes
We prepare the technical foundation for AI to run on reliable data. We evaluate your data source quality, design integration architecture and establish the necessary pipelines to feed AI models.
02 How we do it
- Data source and quality audit
- Cleaning and normalization of critical data
- Integration architecture design
- Automated pipeline implementation
03 Concrete benefits
- AI running on clean, integrated and reliable data
- Reduction of errors and bias in models
- Scalable foundation for future AI initiatives
04 Real example
A healthcare company unified data from 5 legacy systems into a data warehouse. Data quality improved from 60% to 95%, enabling patient readmission predictive models.
Frequently asked questions
Data & Process Foundations
- What are data foundations and why do they matter for AI?
- They are the technical base that makes AI reliable: centralized data, consistent definitions, measurable quality and traceable origin. Without that base, any model produces answers nobody can verify or sustain over time.
- Do we have to replace our data warehouse?
- Not necessarily. In most cases the foundation is built on what already exists: critical sources are cleaned, definitions unified and lineage documented. Replacing the platform is only justified when the cost of keeping it exceeds the cost of migrating.
- How do you measure data quality?
- We define controls per dataset: completeness, uniqueness, format validity and freshness. Each control leaves a record and raises an alert when it breaks. Without quality metrics the conversation about AI becomes an argument of opinions about whether the data is good enough.
- How long until the foundation is ready for AI?
- A first version usable for one concrete use case takes four to eight weeks, scoped to the sources that case needs. Extending coverage across the whole organization is ongoing work, not a project that closes once.
Other services
- AI Opportunity Diagnosis We map your processes, identify where time is lost and detect concrete opportunities where artificial intelligence can generate savings, efficiency or new capabilities.
- Internal AI Agents We design and deploy internal chatbots and autonomous agents that work with your company documents, policies, manuals and knowledge bases. They integrate with Slack, Teams, WhatsApp and email. A support agent can process hundreds of daily requests and resolve up to 60% without human intervention. Available 24/7.
- Executive Workshop Working sessions with leaders and key teams to align expectations, understand constraints and define success criteria before any development begins.
- Training & Adoption We train your teams to use AI in a practical and secure way. We offer workshops for product and engineering teams on using AI in development workflows: code assistants, AI-powered code review, test generation and SPEC-driven development as a working methodology. We support adoption, measure results and scale what works.
- Strategy & Roadmap We prioritize use cases by potential impact, return on investment, technical feasibility, risks and effort. The result is a clear roadmap with timelines, resources and expected outcomes that scale with your operations.
- Document automation and normalization We normalize PDF and scanned documents and process information from emails, contracts, forms, invoices and reports. We extract and structure the relevant fields, validate against your systems of record and keep every value linked to its source document.
- Integration with Existing Systems We connect AI solutions with your CRM, ERP, databases, intranet, APIs and internal tools. We develop intelligent dashboards, AI-powered web applications and internal portals with integrated agents. Without replacing what already works.
Shall we talk about your case?
In a first conversation we review your operation and tell you plainly what can be automated and what cannot, yet.