Non-operated working interest owners face a persistent data challenge: production reports arrive as PDFs, spreadsheets, and email attachments from dozens of operators — each with their own format, naming conventions, and delivery schedule. Manually keying this data into economic models or reserve databases is slow, error-prone, and doesn't scale.
Tauris-AI was built to solve this. Our data ingestion pipeline takes unstructured operator documents and transforms them into clean, validated, export-ready records that flow directly into ComboCurve — or any downstream system your team relies on.
Here's how the six-step workflow operates:
Why This Matters
The traditional approach to non-op data management relies on analysts manually downloading attachments, re-keying values into spreadsheets, and reconciling across systems. A single operator's monthly report might contain 30+ wells — and a typical non-op portfolio works with dozens of operators.
With Tauris-AI handling ingestion, parsing, and matching, your team can redirect hours of manual work toward analysis, forecasting, and decision-making. The data arrives validated, matched to the correct well, and formatted for your target system.
Built for ComboCurve — and Beyond
While ComboCurve is our primary export target, the pipeline architecture is system-agnostic. The same validated, aggregated data can feed Aries, PHDWin, internal data warehouses, or custom BI dashboards. The key is getting clean data in — Tauris handles the rest.
If your team is spending time on manual data entry from operator reports, we'd love to show you how this pipeline works in practice.