Client story · Oil, Gas and Energy
How an energy major rescued a $12M predictive maintenance programme in 90 days, after 14 months of failed hiring.
An energy major operating in Southeast Asia. Client name withheld under NDA. Figures as reported at programme close.
Industry
Oil, Gas and Energy
Engagement
Combined specialists + team build
Team
14 people
First model live
90 days
What was stuck
The challenge
- A $12M predictive maintenance initiative had stalled for 14 months.
- The programme was 11 engineers short across AI/ML, DevOps and full-stack.
- A nine-month direct-hire cycle would have missed the budget window by six months.
- One year of failed internal recruitment and three failed agency engagements had produced no team.
What we designed
Solution Architecture first
- Four weeks of Solution Architecture: target architecture for sensor and historian data, model lifecycle and production operation.
- A one-year IT roadmap sequencing the first model, the data platform and the maintenance workflow integration.
- A 14-person team structure with capability slots for each discipline, and a budget locked at sign-off.
- Security baseline covering the OT/IT boundary and data residency for operational data.
Who we deployed
Recruit · Train · Manage
Specialists embedded as a service; engineers recruited as the client's own employees and managed by Webist.
- Six specialists as a service: Project Manager, Solution Architect, DBA, DevOps Engineer, Cybersecurity Engineer and QA Lead.
- Eight full-stack and backend engineers recruited to the roadmap's capability slots, approved by the client and onboarded as the in-house team.
- Team deployed within eight weeks of the discovery call, managed to KPIs agreed in week one.
- SpecialistsPM, SA, DBA, DevOps, Cybersecurity, QA
- Engineers8 full-stack and backend
- Timeline4 weeks design · 8 weeks to full team · 90 days to first model live
- GovernanceWebist Remote Management System; weekly delivery, people and budget report
What changed
Outcomes
90 days
First predictive maintenance model live in production
8 weeks
14-person team deployed from discovery call
0
Budget overruns against the locked budget
14 months
Of stalled hiring ended in one engagement
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