10 Top Oil and Gas Machine Learning Startups and Companies to Watch in 2026

Executive Summary: Which are the Top 10 Oil and Gas Machine Learning Startups to Watch?

1. PINN AI (USA) develops an AI platform that automates subsurface analysis using well logs, seismic data, and production records to predict drilling locations and optimize reservoirs.
2. Gain.Energy (USA) builds a marketplace of AI agents for petroleum engineers that automates reporting, risk assessment, and drilling analysis across upstream workflows.
3. rahd.AI (Australia) provides an AI platform that cleans and analyzes unstructured data to improve planning, compliance, and efficiency in oil and gas decommissioning.
4. AIEngineer (Australia) offers an AI platform that processes engineering documents and sensor data to deliver instant risk assessments and operational insights for oil, gas, and mining.
5. Rombo AI (Italy) develops an AutoML framework that connects to lab instruments to predict crude oil properties and refine processing.
6. Seleon (Argentina) builds ML models that enable predictive maintenance, demand forecasting, and data-driven decision-making to cut downtime and costs for gas utilities
7. aai agency (USA) creates AI agents that integrate with engineering tools to capture downtime insights, automate planning, and optimize well performance.
8. Wellvector (Norway) offers a platform that converts PDFs into structured insights with citations and audit trails, supporting exploration, drilling, and abandonment workflows.
9. GetVocal (France) builds a conversational AI system that transforms operational data into graph databases for accurate real-time communications and reduced errors in oilfield operations.
10. Applied Computing (UK) develops an AI platform combining time series, physics-based, and language models to detect anomalies, forecast trends, and optimize petrochemical processes.

Global Startup Heat Map highlights Emerging Oil and Gas Machine Learning Companies & Startups to Watch

Through the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 9M+ startups, 20K+ technology trends, plus 150M+ patents, news articles & market reports, we identified the top oil and gas machine learning startups.

The Global Startup Heat Map below highlights emerging machine learning companies in oil and gas you should watch in 2026, as well as the geo-distribution of 410+ startups & scaleups we analyzed for this research.

According to our data, we observe high startup activity in the USA and India, followed by the UK. The top 5 Startup Hubs for oil and gas machine learning are London, Bangalore, San Francisco, Houston, and Dubai.

Discover Emerging Oil & Gas Machine Learning Startups to Watch in 2026

We hand-picked startups to showcase in this report by filtering for their technology, founding year, location, funding, and other metrics. These emerging oil & gas machine learning startups work on solutions ranging from subsurface analysis and AI assistants to oil platform analytics and petrochemical metric analysis.

1. PINN AI – Subsurface Analysis

• Founding Year: 2024
• Location: Dallas, Texas, USA

PINN AI develops an AI and ML Software-as-a-Service (SaaS) platform that automates subsurface data analysis for the oil and gas industry. The platform processes diverse datasets, including well logs, seismic data, production records, and geological information. It integrates user-uploaded data with global datasets to enable rapid and secure evaluations without transferring data ownership.

Moreover, the platform features next-drill predictions, optimal landing zone identification, and 3D visualizations of reservoir characteristics, which assist geologists and engineers in making informed decisions.

2. Gain.Energy – AI Agents Marketplace

• Founding Year: 2023
• Location: Denver, Colorado, USA

Gain.Energy is an American startup that develops Upstrima, an AI agent platform for petroleum engineers. It leverages a proprietary OGAI LLM framework to deliver industry-specific intelligence across drilling, completions, production, reservoir engineering, geosteering, petrophysics, geothermal, carbon capture, and supply chain workflows.

The platform offers static and live AI agents that automate reporting, casing wear analysis, risk assessments, rig selection, regulatory documentation, and drilling key performance indicators (KPI) analytics.

Engineers access these agents as micro AI applications through a web-based SaaS system that synchronizes data from corporate structured query language (SQL) databases, Google Drive, OneDrive, and SharePoint. Each agent adapts to individual workflows to provide hyper-personalized support while preserving existing processes and compliance requirements.

3. rahd.AI – Oil Platform Analytics

• Founding Year: 2023
• Location: West Perth, Australia

rahd·AI is an Australian startup that offers decomGPT, an AI-driven platform that streamlines decommissioning in the oil and gas sector. It applies ML to clean, harmonize, and enrich unstructured data for accurate insights. The platform provides automated data processing, predictive analytics, and regulatory compliance checks.

Also, its audit trail ensures data transparency, while quality controls allow quick review and corrections. As a result, the startup improves planning and optimizes schedules for reducing downtime and enhancing efficiency in decommissioning projects.

4. AIEngineer – AI Risk Assessment

• Founding Year: 2024
• Location: Perth, Australia

Australian startup AIEngineer provides an AI-powered platform for engineering and operational intelligence in the oil, gas, and mining industries. It applies ML and large language models (LLMs) to decode complex engineering documents and equipment data. Further, it ingests and understands internal documents such as datasheets, piping and instrumentation diagrams, and specifications.

Then, it connects insights with real-time sensor data to enable fast and accurate decision-making. Engineers receive instant answers to technical queries while reducing delays in operations and maintenance. Thus, the platform works as a virtual expert and supports frontline teams with context-aware responses and knowledge retention.

5. Rombo AI – Spectral Analysis

• Founding Year: 2023
• Location: Cagliari, Italy

Argentine startup Rombo AI builds SpectraAI, an AutoML framework for spectral data analysis. The framework automates the processing of spectroscopy inputs such as nuclear magnetic resonance (NMR), infrared spectroscopy (IR), and gas chromatography-mass spectrometry (GC-MS) by connecting directly to lab instruments. It enables real-time predictions on crude oil properties and refining parameters.

Further, the framework combines chemio-informed ML with generative AI to improve precision, accelerate model development, and reduce reliance on manual chemometrics. With no-code to low-code flexibility, it supports both domain experts and data scientists while maintaining compatibility with industry-standard formats.

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6. Seleon – AI Utility Operations

• Founding Year: 2024
• Location: Cordoba, Argentina

Argentine startup Seleon develops ML models that optimize utility operations for the gas providers. The models enable predictive maintenance by anticipating equipment failures and reducing downtime. Likewise, demand forecasting ensures accurate resource distribution to minimize waste and improve efficiency.

Moreover, the startup gathers and analyzes operational data to deliver strategic insights that guide better decision-making. By combining AI, data integration, and cloud solutions with robust cybersecurity, Seleon increases efficiency, reduces costs, and improves service delivery in public resource management.

7. aai agency – AI Agents

• Founding Year: 2025
• Location: Dallas, Texas, USA

aai agency builds AI agents for the oil and gas industry, including Petry, a copilot for operational workflows. These agents integrate with tools like Excel and Spotfire, and leverage ML to capture insights from downtime events and asset data. They automate repetitive tasks, streamline planning workflows, and optimize well performance, helping teams stay aligned and efficient.

Users benefit from reduced manual work, faster decision-making, and improved operational visibility across upstream, midstream, and downstream operations.

8. Wellvector – Petroleum AI

• Founding Year: 2024
• Location: Sandnes, Norway

Norwegian startup Wellvector converts petroleum documents into usable insights through its intelligent platform. It organizes unstructured PDFs from exploration to abandonment while adding precise citations and clear audit trails. The system works with SharePoint, Microsoft Teams, and Azure environments.

Human feedback continually improves the accuracy of document retrieval and analysis. The platform supports geologists, drilling engineers, and petroleum professionals who need quick and reliable access to information.

9. GetVocal – AI Phone Agents

• Founding Year: 2023
• Location: Paris, France
• Funding: EUR 2.7 million (Pre-seed)
• Partnership: Capita

GetVocal is a French startup that offers a graph-based conversational operating system. It converts unstructured data from documents, call transcripts, and operational logs into a proprietary conversational graph database. This enables structured storage, retrieval, and analysis of communication patterns.

Further, its engine combines deterministic logic with generative AI to ensure both accuracy and adaptability in mission-critical interactions.

By converting each exchange into measurable tensors, the system provides transparency on performance metrics like intent, sentiment, and conversion. Also, it avoids unpredictable outputs through steerable conversation maps and continuous feedback loops. This allows oil and gas operators to manage real-time field communications, streamline process monitoring, and reduce costly errors.

10. Applied Computing – Petrochemical Metric Analysis

• Founding Year: 2023
• Location: London, UK
• Funding: GBP 9 million (Seed)

UK-based startup Applied Computing develops Orbital, an AI platform for oil and gas operations. It uses a time series model, a physics-based model, and a language model. The time series model connects to distributed control systems, historians, and laboratory information management systems. It learns from raw data, detects anomalies, and forecasts operational trends.

The physics-based model extracts equations from manuals and literature. It estimates unknown variables from live data and ensures predictions follow mass balance, energy conservation, and reaction kinetics.

The language model interprets piping and instrumentation diagrams, standard operating procedures, and work orders. It delivers clear insights and practical recommendations for engineers and operators in upstream, refining, and liquefied natural gas operations.

Discover All Emerging Oil & Gas Startups

The oil & gas startups showcased in this report are only a small sample of all startups we identified through our data-driven startup scouting approach. Download our free Oil & Gas Innovation Report for a broad overview of the industry or get in touch for quick & exhaustive research on the latest technologies & emerging solutions that will impact your company in 2026!