ETL systems for scattered data,
readable in every language
We build pipelines that collect data from portals, APIs, files and devices, clean and classify it, translate it automatically and load it into search, dashboards and the systems your team already uses.
Six stages, each with its own log
Every stage runs and fails on its own, so one broken source or a slow model does not stop the rest of the pipeline.
Collection and extraction
Adapters for public portals, partner APIs, RSS, file drops, email attachments and industrial devices. Each source has a schedule, a rate limit and a run log.
Normalisation, deduplication and quality
Fields are mapped to one model, dates, amounts and currencies are normalised, and the same record from two sources is stored once. Records that fail quality rules go to a review queue.
Enrichment and classification
Rules first, then a model where rules are not enough: category, relevance, status and links to related records, each with the evidence that led to it.
Automatic translation
Texts are translated in batches into the languages your team and customers read. Originals are kept, the source language is shown, and the model can run on your own hardware.
Loading, search and dashboards
Data lands in a database, full-text search, dashboards, alerts or your CRM and ERP, with an API for other systems.
Monitoring and operations
Run history, error counts per source, queue sizes and freshness of every dataset are visible, so a silent failure is noticed in hours, not weeks.
Financial analysis on local AI, without sending company data to the cloud
We build finance pipelines that run inside infrastructure your company controls. Figures are calculated by SQL and code, so results can be checked line by line. The local model classifies transactions and explains changes in plain language, and a finance specialist reviews the result.
Ingest ERP, accounting and bank exports
Scheduled imports from ERP and accounting systems, bank statements and spreadsheets, with each file and row traceable back to its source.
Normalise, reconcile and validate
Accounts and counterparties mapped to one chart, currencies converted, bank lines matched to ledger entries, and gaps or duplicates sent to a review list.
Cash flow and expense analysis
Cash flow by period, expenses by category, supplier and project, with the local model suggesting categories for unclassified transactions.
Plan versus actual and anomaly flags
Budget deviations, unusual payments and sudden changes are flagged by rules and thresholds you agree on, each flag linked to the underlying transactions.
Management reports with sources
Monthly reports where every figure links to its query and source rows, plus a plain-language summary that an accountant or finance manager approves before it is shared.
How data stays inside the company
Deployment you control
Models, embeddings, databases and logs run on your servers or private cloud. The design blocks outbound connections for inference, and no telemetry with customer data leaves the environment.
Access, audit and retention
Role-based access, an audit log of who viewed or changed what, and retention periods you configure for raw files, results and logs.
Honest limits
This is an implementation service, not financial or investment advice and not a certification. AI explanations support people; decisions and sign-off stay with your finance team.
Note: public pages of this website are translated by our own local translation service. That is separate from client finance projects, which run only in the client's infrastructure.
What we build and how we keep it safe
Typical uses
Tender, grant and market monitoring; supplier and product catalogues; document intake for back office; production and equipment data for operators; migration of data between old and new systems.
Review, privacy and control
People review uncertain records before they are used. Personal data is minimised, sources that block access are respected, and each automated decision is logged with its reason.
About ETL systems
Have data spread across many sources?
Tell us where it comes from, who needs it and in which languages. We reply within one business day.