AI Assistant for Oil & Gas Operations | Field Ops
AI Assistant for Oil & Gas Operations

Your in-house LLM expert on processes, documents and regulations

Leverage a custom-trained assistant that ingests your SOPs, engineering standards, compliance manuals and project docs to deliver on-demand, context-aware guidance. Ask natural-language questions and receive precise, policy-correct answers instantly.

Phone/WhatsApp: +351 123 4567

Control room with chat overlay concept

Benefits

75% fasterRamp-up for new engineers & techs
90% fewerErrors from outdated manuals
24/7On-demand guidance
CitedAnswers with sources
LowerSME load

Trusted By

Shell BP ExxonMobil

Key Modules

Knowledge Ingestion Engine

Secure RAG pipeline for SOPs, P&IDs, HSE manuals and vendor specs; version tracking to avoid stale procedures.

Contextual Conversational Interface

Session memory for follow-ups (e.g., “And what’s the safe working load?”) with traceable citations.

Regulation & Standards Checker

Auto-flags non-compliant steps vs. HSE/ISO 9001; alerts when referenced docs are outdated.

Analytics & Usage Dashboard

Top queries, gaps, satisfaction scores; drives content expansion and model improvement.

Access Control & SSO

Role-based permissions via Okta/Azure AD; least-privilege by default.

Embedded Assistants

Deploy in Teams, Slack, field mobile apps and control-room consoles.

Integration Capabilities

Enterprise Systems

  • SharePoint, SAP EHS, Oracle Primavera, in-house DMS
  • Secure APIs & attestable audit logs

Collaboration Platforms

  • Microsoft Teams, Slack, custom mobile apps
  • Contextual deep links into tasks & tickets

Access Control & SSO

  • Okta / Azure AD, role-based permissions
  • Per-document entitlements

Subtasks Addressed

  • On-demand SOP and permit-application guidance
  • Equipment startup/shutdown checklists
  • Regulatory queries (e.g., “Inspection interval for BOPs?”)
  • Incident-investigation references & corrective-actions
  • Vendor-spec lookup and cross-reference
  • Shift-handovers with cited context

Implementation Roadmap & Timeline

Phase 1 (0–4 weeks)

Knowledge Ingestion & Model Tuning

  • Ingest SOPs, training slides, P&IDs, regulatory filings
  • Fine-tune on terminology; validate accuracy with SME Q&A

Phase 2 (5–12 weeks)

Pilot & User Feedback

  • Deploy to a target BU (e.g., offshore operations)
  • Usage metrics, surveys; expand document coverage

Phase 3 (13–24 weeks)

Enterprise Rollout & Continuous Learning

  • Org-wide rollout; automated ingestion & versioning
  • “AI Champions” program for governance

Training & Change Management Support

  • Train-the-Trainer: certify internal champions for prompts & content updates
  • User Onboarding: role-specific interactive demos
  • Clinics: monthly feedback to expand coverage
  • 24/7 Support: troubleshooting & prompt engineering
Team training session with tablets

Expanded KPIs

< 15 sAlarm-to-Action latency
< 1 hIncident-report turnaround
95%+Compliance audit pass rate
90%+Regulatory query SLA
≥ 5Proactive flags /1k hrs
< 10%SME escalations
−50%Training time
≥ 75%User adoption (weekly)
100%Knowledge coverage
HighExtraction accuracy

Frequently Asked Questions

How is our confidential data kept secure?

All ingestion and inference run in your private cloud or on-prem. No data leaves your network.

Can it handle multi-step follow-ups?

Yes. Session memory keeps context; answers include confidence and citations.

How often is the knowledge base updated?

Schedule daily/weekly ingestion jobs; version tracking ensures the latest procedures.

What if an answer is uncertain?

Low-confidence answers are flagged for SME review and model retraining.

Ready to Empower Your Teams?

See It on Your Data

Request a guided demo tailored to your assets and workflows.

Request Demo

Get the Implementation Roadmap

Plan your rollout with timelines, roles and governance.

View Roadmap

Book a Field Trial

Hands-on pilot with your crews and supervisors.

Book Now
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