htmlIndustrial Reliability & Asset Data Services | VILI AI

RELIABILITY ENGINEERING × INTELLIGENT AUTOMATION

Industrial Data.
Engineered Intelligence.

VILI | AI helps manufacturers build, clean, standardize, and validate the asset information behind effective maintenance and reliability programs—from P&IDs and OEM documentation to CMMS-ready data, equipment BOMs, and preventive maintenance strategies.

Engineering-ledSource-traceableBuilt for implementation
Industrial intelligence symbol
VILI|AI

Verified Industrial Logic & Intelligence

Industrial Reliability | Data Engineering | AI Automation

THE PROBLEM WE SOLVE

Unreliable asset data creates unnecessary work.

Equipment tags in one spreadsheet, different descriptions in SAP, missing part references, and drawings that do not match field records: small inconsistencies compound into larger maintenance and reliability problems.

VILI | AI converts P&IDs, equipment lists, OEM manuals, walkdowns, and CMMS exports into structured data your team can review, govern, and use.

WHAT WE DO

Technical depth.
Scalable execution.

Clear inputs, traceable technical decisions, and review-ready deliverables—not just automated output.

01 / DATA FOUNDATION
⌘

Asset Hierarchy Development

Identify equipment and process relationships from P&IDs, then reconcile them with equipment lists, drawings, site standards, and field evidence to build review-ready asset and functional location structures.

  • P&ID tag and equipment extraction
  • Functional location and equipment hierarchy
  • Classifications, attributes, and naming rules
  • Source references, missing tags, and exception log
02 / DATA QUALITY
≋

CMMS Data Cleansing & Standardization

Improve the consistency and usability of legacy asset and material records while preserving client-defined naming conventions and data dictionaries.

  • Equipment and material description standards
  • Duplicate, conflict, and attribute checks
  • Missing or misplaced field identification
  • Corrected records with QC exceptions
03 / MATERIALS
▤

Equipment BOM Development

Build equipment-to-spare-part relationships from OEM manuals, drawings, walkdown evidence, and existing materials data—separating confirmed matches from candidates.

  • OEM part identification and cross-references
  • SAP material and inventory reconciliation
  • Equipment-to-component assignments
  • Match confidence and unresolved items
04 / RELIABILITY
◇

Preventive Maintenance & FMEA Strategies

Develop and optimize maintenance tasks using equipment functions, failure modes, criticality, and applicable condition-monitoring methods.

  • FMEA-to-task traceability
  • Condition-based and inspection task selection
  • PM task content and frequency review
  • Corporate standards and site applicability
05 / SYSTEM READINESS
▦

SAP PM & Maximo Data Readiness

Prepare and validate asset and maintenance records for CMMS/EAM review, migration, and loading according to client templates and business rules.

  • Asset hierarchy and equipment master data
  • Load-sheet formatting and field mapping
  • Legacy-to-target reconciliation
  • Validation results and open exceptions
06 / INTELLIGENCE
✳

Industrial AI Analytics & Automation

Apply AI-assisted extraction, matching, classification, and analysis to repetitive technical work, with defined rules and engineering review.

  • Document and drawing data extraction
  • Automated checks and exception detection
  • Repeatable engineering workflows
  • Data quality summaries and decision support

WHAT YOU RECEIVE

Structured data, with the evidence behind it.

Deliverables are tailored to the client's standards, systems, and approval process.

Review-ready datasets

Asset registers, functional location structures, equipment BOMs, PM task content, and standardized master data in agreed formats.

Traceability & exceptions

Source references, match rationale, conflicting records, missing attributes, and open questions requiring client resolution.

Quality-control summaries

Documented validation checks, completeness findings, and clear separation of confirmed information from recommendations.

OUR APPROACH

AI does the heavy lifting.
Engineering owns the result.

Speed is valuable only when the output can be trusted.

01

Scope

Confirm asset scope, source priorities, governing standards, and required output fields.

02

Extract & Build

Extract and structure data from approved drawings, manuals, records, and field observations.

03

Reconcile

Compare records across sources, document discrepancies, and distinguish confirmed facts from candidate matches.

04

Validate & Deliver

Apply technical QC, deliver client-format datasets, and clearly identify items requiring approval or further evidence.

ABOUT VILI | AI

Turning Chaos Into Clarity.

Industrial facilities generate enormous amounts of valuable information, but that information is often scattered across engineering drawings, equipment records, OEM manuals, spreadsheets, and maintenance systems. What should provide a clear picture of an operation can become fragmented, inconsistent, and difficult to trust.

VILI | AI was built around a straightforward principle: turn chaos into order, complexity into clarity, and disconnected information into actionable intelligence.

Backed by over 25 years of experience in industrial operations, maintenance, and reliability, we understand the challenges of building and maintaining accurate asset information. We combine that practical engineering experience with AI-assisted technology to organize, reconcile, and validate data that supports better maintenance and reliability decisions.

Our focus is not simply producing information faster. It is delivering structured, traceable, and technically defensible results that customers can confidently review and put to work.

VILIVerified Industrial Logic & Intelligence

LET'S TALK

Have an asset data problem
worth solving?

Tell us what you're working with—P&IDs, equipment lists, manuals, spreadsheets, or existing CMMS exports—and what the finished deliverable needs to look like.

Business email and domain will be connected before public launch. This preview does not collect submissions.

PROJECT STARTING POINTS

Asset hierarchy builds

Legacy data cleanup

BOM and PM development

Engineering workflow automation

Email setup pending