Challenge
Generic AI can't reason about specific assets.
Agnotic approach
We ground agents in your historian, asset registry, and manuals so answers cite real equipment and readings.
Oil & Gas AI Agents
Oil and Gas AI Agent Development
We build AI agents for oil & gas operations (grounded in asset, sensor, and field data) that monitor equipment, predict failures, assist field workers, and automate safety and reporting workflows across upstream and downstream.
IIoT / OPC UAIEC 62443On-prem / VPCField-ready
Trusted by global innovators
What is oil and gas AI agent development?
Oil and gas AI agent development is building software agents that read asset, sensor and field data and act on it within limits you set. Agnotic Technologies builds these agents for operators and oilfield service companies, grounded in historian, SCADA and maintenance records, with human approval on every action that affects safety or production.
Pumps, compressors, pipelines and sensors produce telemetry faster than any team can watch. An agent grounded in that data can catch a degrading asset before it fails, answer a field worker's question from the manual and live readings, or draft an incident report.
The hard part is trust in a remote, high-consequence setting with limited connectivity. We scope each agent's actions, keep a human in the loop for anything consequential and deploy inside your boundary.
How are oil and gas AI agents grounded?
See how we ground oil & gas AI agents: retrieval over historian and asset data, edge-tolerant delivery, and human-in-the-loop safety.
Common failure modes
Where do oil and gas AI projects fail?
Challenge
Safety-critical actions can't be automated blindly.
Agnotic approach
Scoped, reversible actions with human-in-the-loop approval and full audit logging on anything consequential.
Challenge
Field sites have limited connectivity.
Agnotic approach
Edge-tolerant delivery and caching so field agents work offline and sync when connected.
Challenge
Operational data can't leave the boundary.
Agnotic approach
On-prem / VPC deployment with private model endpoints so proprietary data stays internal.
Which oil and gas AI agents do we build?
The oil and gas AI agent development services we deliver for upstream and downstream operations.
Asset monitoring & prediction
Agents that watch equipment telemetry, flag anomalies, and predict failures before downtime.
Field-worker assistant
An assistant grounded in manuals, procedures, and live readings for technicians in the field.
Safety & incident automation
Agents that support permit-to-work, hazard checks, and draft incident reports from context.
Operational reporting
Automated production, downtime, and compliance reporting from operational systems.
Where it runs
Where do AI agents help oil and gas teams?
Predictive asset health
Failure prediction and maintenance recommendations from sensor data.
Field technician copilot
Answers from manuals and live readings, offline-capable.
Safety & permits
Support for permit-to-work, hazard identification, and checks.
Incident reporting
Draft incident and inspection reports from operational context.
Production optimization
Surface efficiency and yield opportunities from operational data.
Operational Q&A
Grounded answers over historian, asset, and document data.
Oil & gas AI built for high-consequence operations
Energy AI stalls when it can't be trusted at the edge. We build for grounding, safety, and offline field use.
One use case
Scoped first agent
Edge-ready
Works with limited connectivity
Human-in-loop
On every consequential action
Standards we build against
Oil & gas AI standards
OPC UAMQTTIEC 62443ISO 55000HistorianIEC 61508
Our Process
How do we build an oil and gas AI agent?
Use-case scoping, data grounding, and safety guardrails first.
1.
Use-case & data scoping
We pick a high-value use case and map the asset, historian, and document data to ground on.
Value-first
2.
Grounding & integration
Retrieval over historian and asset systems, edge-tolerant where field use is needed.
Grounded
3.
Agent build & guardrails
Scoped tool-use, human-in-the-loop approvals, and evaluation against real scenarios.
Guardrailed
4.
Deploy & monitor
On-prem / VPC deployment with logging, monitoring, and a feedback loop.
Observed
Facts and sources
Rules and frameworks behind field AI
Short facts we design around, each linked to its primary source.
The core of the NIST AI Risk Management Framework is made up of four functions: govern, map, measure and manage, each broken down into categories and subcategories.
Source: NIST AI RMF 1.0 (AI 100-1), CoreNIST SP 800-82 Rev. 3 covers how to secure operational technology such as industrial control systems, and lists common threats and vulnerabilities with recommended countermeasures.
Source: NIST SP 800-82 Rev. 3Under OSHA Process Safety Management (29 CFR 1910.119(k)), the employer must issue a hot work permit for hot work conducted on or near a covered process and keep it on file until the work is complete.
Source: 29 CFR 1910.119 (eCFR)Under 49 CFR 195.446, each hazardous liquid pipeline operator with a controller who monitors and controls the pipeline through a SCADA system must have and follow written control room management procedures.
Source: 49 CFR 195.446 (eCFR)
Why Partner With Us
15-Minute Scoping CallWhy do energy teams build AI agents with Agnotic?
Agents that are useful in the field and safe by design.
Safety-first
Scoped actions and human-in-the-loop on anything consequential.
Industrial depth
Fluent in historian, asset, and OT data, not just enterprise APIs.
Edge-ready
Delivery that works with the connectivity real field sites have.
Full-stack fluency
From sensor data to field UX, built as one grounded system.
Frequently Asked Questions
It depends on the use case and on how quickly the agent can reach the historian, asset and document data it grounds on. We start from one high-value use case rather than a platform, agree its scope, and give you a dated plan after the scoping call.
Cost scales with the number of agents, the data they ground on, and edge or on-prem constraints. A single grounded agent is a smaller engagement than a suite across asset health, field support and safety. We scope one use case first and share an estimate.
Yes. We build edge-tolerant agents that cache the data and models they need and sync when connected, so field technicians get useful answers even offline.
Agents are grounded in real asset and historian data so they cite sources, their actions are scoped and reversible, and anything consequential routes through human-in-the-loop approval with full audit logging.
Yes. We ground agents on historian and asset data over OPC UA and MQTT, and where those systems are not yet connected we handle the integration. See our SCADA integration services.
Yes. The first release is one agent for one use case, such as asset health alerts for a single facility, with its data sources, allowed actions and approval steps written down before the build starts.
AI tools help our engineers draft code and tests, but a person reviews every change, and it passes the same automated tests and security checks as any other code. Which tools may see your code or data is agreed with you at the start.
Ready to put AI to work across your assets?
Tell us one high-value use case and your data. We will return a grounded, safe oil & gas AI agent plan scoped to pilot.
contact@agnotic.com
Partnerships
contact@agnotic.com