Overcoming AI implementation hurdles: EOT.ai's collaborative approach
summary
EOT.ai positions its platform as a practical path from OT systems into production AI demonstrating customers in production since 2020 and partnerships with AWS and clients like Hilcorp, BPX, NOV. It moves raw OT into Databricks, Snowflake and data lakes, ranks use cases by ROI and implementation speed, and offers a packaged install that claims three months to production. The rollout follows a three‑step adopter sequence so early wins scale into company‑wide deployment.
AI-written summary · about
chapters (6)
- 0:00Introduction
- 2:10What is the best mindset to approach AI
- 5:46Avoiding POC Purgatory
- 8:02Choosing the first use case
- 13:40The biggest hurdles
- 17:55Conclusion
related talks
16mFrom OT Data Challenges to AI-Driven Operations on
56mAI War Stories: Real world learnings delivering enterprise AI solutions
36mBeyond the Hype
29mAI Operationalization: Where the AI Rubber Hits the Road for the Enterprise
30mEnterprise AI: How To Operationalize Data Analytics At Scale
13mBuilding Scalable AI/ML Platforms for Industrial IoT
14mFrom 18 Months to 5 Days with Agentic AI on
10mAI Data Platform for Health and Life Sciences
