Predictive maintenance in production, not in a pilot.
Asset integrity, predictive maintenance, OT-aware security and data platforms for upstream, midstream and utilities, delivered by teams that can take a model from proof of concept to a plant that depends on it.
The problems that arrive on a CIO's desk in this industry.
Pilots that never reach production
Predictive maintenance and digital twin initiatives stall between the data science proof of concept and a system operations will trust.
Scarce AI, DevOps and full-stack talent
An energy major can be eleven engineers short across three disciplines and lose a budget window waiting for direct hires.
OT and IT converging
Plant historians, sensors and control systems now feed enterprise data platforms, and the security boundary has to be engineered, not assumed.
HSE and integrity reporting
Inspection, permit-to-work and incident data live in separate systems, and the reporting burden grows every audit.
Teams and platforms shaped for the sector.
Predictive maintenance teams
AI / ML, data, DevOps and full-stack engineers under a Webist PM, SA and Cybersecurity Engineer, from the first model to production operation.
Asset, sensor and work order ontology
Asset, sensor, work order and crew objects feeding failure prediction, maintenance scheduling and dispatch with approval gates.
Asset integrity
Predictive maintenanceOT/IT data platform roadmap
Historian and sensor data brought into a governed platform with the security zones and conduits designed in from the start.
OT-aware cybersecurity
Cybersecurity Engineer as a service for segmentation, vulnerability management and incident response across plant and enterprise networks.
HSE and integrity systems
Inspection, permit-to-work and incident workflows integrated with ERP maintenance modules.
OperationsDigital twin and optimisation
Asset models used for scenario analysis, production optimisation and maintenance planning.
Obligations we design for from week one.
The Solution Architecture phase maps these to the target architecture, the security baseline and the team's KPIs, so compliance is built in rather than audited in.
- IEC 62443Industrial automation and control system security: zones, conduits and security levels for OT networks connected to enterprise platforms.
- ISO 55001Asset management systems standard that frames integrity, maintenance strategy and lifecycle decisions.
- Operator standardsNational oil company and operator technical standards and vendor registration requirements that govern systems delivered into their estates.
- Data historiansIntegration with plant historians and time-series platforms as the source for predictive models.
- HSEHealth, safety and environment reporting obligations that define audit trails for inspection, permit-to-work and incident records.
- Data protection and residencyPersonal Data Protection Act 2010 (Malaysia) for workforce data, plus operator requirements on where operational data may be hosted.
Designed in the roadmap phase, then recruited to it.
Illustrative. Every structure is set in the Solution Architecture phase against your roadmap and budget.
- LeadershipProject Manager, Solution Architect with industrial data experience
- PlatformDevOps Engineer, DBA, Cybersecurity Engineer with OT awareness
- AssuranceQA / Test Lead for data pipelines and model validation
- Engineers2–3 AI / ML, 2 data, 4–6 full-stack and backend
- WhereLeadership in Kuala Lumpur; engineers on managed cloud desktops; site visits as the roadmap requires
Technology Leadership Services
Senior specialists as a service, with your own engineering team built under them
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Engineering Team Build
Recruit · Train · Manage: in-house engineers who join your payroll
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Data + AI
Ontology-first data platforms and agentic AI that acts
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Tell us where you are. You get an estimated quotation within 48 hours, a clear plan, and a working team in eight weeks.