Tessera Analytics provides AI‑native data analytics platforms for oil and gas operators, enabling production optimization and reservoir characterization directly within existing workflows. Their solution integrates wells, production, drilling, and geoscience data from disparate silos into a unified, decision‑ready system built by a combined subsurface and AI team, allowing operators to own and control the technology on their own cloud infrastructure.
Funding
Funding not disclosed
Founders
Product
Problem
Oil and gas operators often store wells, production, drilling & completion, geology, diagnostics, and operations data in separate silos, leading to fragmented dashboards rather than integrated, actionable systems. This disjointed data landscape hampers accurate reservoir characterization, production optimization, and timely decision‑making, resulting in lost revenue and inefficient operations.
Solution
Tessera Analytics delivers an AI‑native platform that unifies all upstream data sources directly within the operator’s existing cloud environment. By combining subsurface expertise with machine‑learning models, the platform transforms siloed datasets into a single, decision‑ready system for production optimization, drainage modeling, and recovery inventory management. The solution is built collaboratively with the operator’s team, ensuring the models reflect the specific basin characteristics and workflow requirements. All analytics and tools are owned and hosted by the operator, eliminating vendor lock‑in while providing continuous, real‑time insights that can be acted upon within existing operational processes.
Target Audience
Primary customers are upstream oil and gas operators and their engineering teams responsible for reservoir management, production optimization, and field development planning.
Features
- Integrated data lake that consolidates wells, production, D&C, G&G, diagnostics, and operations data into a unified schema
- AI‑native production intelligence (RTAi) that delivers real‑time optimization recommendations
- Pad and base optimization modules that evaluate well placement and field development scenarios
- Drainage modeling and recovery inventory tools for accurate reservoir characterization and forecasting
- Collaborative model development workflow that pairs subsurface engineers with AI/ML specialists
- Deployment on the operator’s own cloud infrastructure with full data ownership and no vendor lock‑in