We've spent decades working across oil and gas operations, finance, and technology. We've seen the same problem at every operator we've worked with — and we believe AI is finally ready to solve it.
The Problem
Every small to mid-size E&P company has the same story. Accounting lives in Quorum or PakEnergy. Production volumes come from field systems. Reserves sit in PHDWin or Aries. Land records are somewhere else entirely. And the only thing connecting all of it is a spreadsheet that someone maintains manually — when they have time.
The result? Decisions made on stale data. Revenue that falls through the cracks on non-op properties. Hours of analyst time spent reconciling systems instead of analyzing results. It's not a technology problem — the individual systems work fine. It's an integration problem, and nobody has solved it for the operators who need it most.
The majors have dedicated data teams and eight-figure IT budgets. The 20-person operator running 200 wells across three basins does not. But they have the same data challenges.
The Vision
That's why we're starting Tauris Softworks.
The vision is straightforward: build a single source of truth for upstream oil and gas data. Connect accounting, production, reserves, land, and compliance into one platform that stays current without manual intervention. Give small operators the same data visibility that the majors take for granted — without requiring them to hire a data engineering team.
We're not building another analytics dashboard or another reporting tool. We're building the data layer underneath all of it — the connective tissue between the systems operators already use and trust.
Why AI Changes Everything
The integration problem isn't new. What's new is the toolset available to solve it. AI and machine learning give us the ability to do things that weren't practical even a few years ago:
- Automated document processing — Operator reports arrive as PDFs, spreadsheets, and email attachments in dozens of different formats. AI can identify, classify, and extract structured data from unstructured documents without hard-coded templates for every operator.
- Intelligent data matching — Matching wells across systems where naming conventions differ (and they always differ) is a problem that scales poorly with human effort. Machine learning handles it naturally.
- Anomaly detection and QAQC — AI can flag data quality issues — missing wells, volume discrepancies, reporting gaps — across thousands of records in the time it takes an analyst to open a spreadsheet.
- Continuous learning — Every document processed and every correction made improves the system. The more data flows through Tauris, the smarter and more accurate it becomes.
We're not using AI as a buzzword. We're using it to solve specific, well-defined problems that have made upstream data integration impractical at scale for small operators. The technology has reached the point where a two-person team with the right architecture can deliver what used to require a department.
What's Next
We're starting with the foundation: a data warehouse architecture purpose-built for upstream O&G, with AI-powered connectors for the systems our target clients actually run. The first integrations will focus on production data and reserves, with accounting to follow.
It's early. We're a small team in Houston with a clear problem to solve, the right experience to understand it, and a strong opinion about how AI can finally crack it. If you're an operator who's tired of spreadsheet hell, we'd love to talk.