AI Applications
AI that answers from your own documents and links each answer to its source.
Data Platforms that give your teams one version of each figure
We bring your records, documents and external feeds into one clean, current data model. Dashboards, maps, search and AI then read the same figures, each traceable to its source.
From source systems to one data model
A data platform is the layer between the systems that produce data and the people who need answers from it. It pulls data from each source, cleans and links it, then publishes it to reports, maps, search and AI. Structured records sit beside PDFs, web pages and other documents, with intelligent search across both.
Problems it solves
The data exists, but the same question gets different answers.
- The same figure differs between departments because each keeps its own copy.
- Monthly reports are assembled by hand from exports.
- Public or partner data arrives in different formats and must be reconciled first.
- An AI project stalls because no one can say which data is current.
How we work on a data platform
Each stage ends with figures you can compare against the ones you already trust.
Discovery
We agree on the first questions, then produce a source map (owners, refresh cycles, data quality) and a target data model.
Pilot on your data
We connect the key sources and build one working view (a dashboard, map, search page or API).
Production
We add the remaining sources, scheduled refreshes, quality checks, access control and monitoring.
One figure everyone agrees on
We choose one figure that different teams report differently, for example open cases or active customers. We trace it to its sources, agree on one definition and build the pipeline that produces it every day. The pilot ends with a dashboard your teams compare against the numbers they trust today.
What we need from you
We need access to each source or an export, the person who owns it and the figures your team trusts today.
What you get
- A source map and a target data model
- Pipelines for each source, with scheduled refresh
- Quality checks, with alerts when a source changes or fails
- Dashboards, maps or APIs for the agreed uses
- Access control by role and data set
- Documentation of every source, field and processing step
Related solutions
Systems Integration
Connect AI and new software to the systems you already run.
Frequently asked questions
Do you replace our existing databases or data warehouse?
Not by default. We build on what works and add what is missing: pipelines, a clean data model, search or a publishing layer. Replacement is a separate decision, discussed in Discovery.
Can the platform include documents as well as tables?
Yes. We extract text, tables and key fields from reports and PDFs, including scanned files, and index them next to your structured data. That also prepares the platform for AI.
How do we know the numbers are right?
Each pipeline runs data quality checks, and every figure on a dashboard or map can be traced back to its source and refresh date.
Bring us the report you rebuild every month
Show us where its numbers come from. We will map its sources and show what automating it would take.