Real-Time Lubricant Recommendation Platform for Global Energy Brands
Engineered a multi-tenant SaaS platform and automated ETL validation engine that maps OEM equipment specifications to fluid catalogs for Castrol, Liqui Moly, Penrite, and Petronas across 23+ regional markets.
Building a Real-Time Lubricant Recommendation SaaS Platform for Global Energy Brands
Modern automotive engines, heavy industrial machinery, and commercial vehicles demand precise fluid specifications. Recommending the wrong oil grade can cause catastrophic mechanical failure and void equipment warranties.
Global lubricant manufacturers operate in a demanding technical environment where product accuracy is everything. Companies like Castrol, Liqui Moly, Penrite, and Petronas maintain thousands of fluid formulations that must stay synchronized with constantly evolving manufacturer specifications across automotive, agricultural, and industrial sectors.
Historically, matching commercial lubricants to original equipment manufacturer (OEM) technical standards was an agonizing manual process managed through spreadsheets and slow quarterly publishing cycles. Zediant was brought in to architect, build, and deploy an enterprise SaaS platform that automates OEM specification mapping, validates data accuracy through automated pipelines, and delivers instant recommendations to technicians and consumers across web and mobile.
The Bottlenecks of Manual Specification Management
Before this initiative, publishing accurate fluid recommendations at enterprise scale suffered from four major operational bottlenecks:
Slow Quarterly Release Cycles
Updates were processed in slow batch cycles every three months. When an oil company formulated a new synthetic lubricant, it often took up to 90 days before retail buyers and workshops could look it up.
Manual Data Entry Overhead
Technical teams mapped manufacturer approvals, viscosity grades, and fluid capacities into internal systems by hand, creating heavy backlogs and high labor overhead.
Fragmented Product Catalogs
Different markets and distribution channels used separate product databases, leading to conflicting recommendation results between websites, retail store kiosks, and mobile apps.
Risk of Mechanical Misapplication
With thousands of vehicle trims and transmission variants on the road, manual data entry increased the risk of recommending the wrong fluid for sensitive vehicle components.
Four Core Engineering Challenges We Solved
Building a platform that handles millions of monthly lookups across international brands required solving four structural engineering problems:
Large-Scale Data Migration
Migrating complex OEM databases, historical product approvals, and legacy product catalogs without breaking relationships between vehicle models and component compartments.
Automated Validation Logic
Building strict validation rules into the ingestion engine to flag missing data, invalid viscosity entries, and duplicate vehicle trims before publishing to live users.
Real-Time Publishing Engine
Replacing batch database dumps with an event-driven publishing pipeline that pushes catalog adjustments to consumer apps and third-party APIs instantly.
Multi-Tenant Brand Isolation
Allowing competing lubricant brands to manage their own proprietary product catalogs and pricing tiers on a shared, secure infrastructure without data leakage.
The 6-Component Platform Architecture
Zediant designed a decoupled, multi-tenant SaaS architecture on AWS, separating data ingestion, business mapping logic, and public-facing APIs:
SSIS Data Transformation & Ingestion Engine
Extracts, transforms, and loads raw OEM specification updates and manufacturer tables into structured relational stores.
Microsoft SQL Server Core
Maintains normalized tables for equipment categories, engine compartments, oil capacities, and verified fluid approval codes.
Java Spring Boot Mapping & Validation Engine
Executes compatibility algorithms that match OEM requirements with each brand's product lines, enforcing business rules and brand preferences.
RESTful API Gateway
Delivers low-latency search endpoints for license plate lookups, vehicle make/model selectors, and product detail queries.
AngularJS Brand Administration Console
Allows technical analysts from oil companies to audit recommendations, manage product lines, and update specifications securely.
AWS Hosting, Observability & Delivery
Scalable cloud infrastructure supporting high consumer search traffic across web, retail counter kiosks, and mobile apps.
Designed for Technical Teams and End Users Alike
How It Works for Oil Companies
Brand technical analysts log into the secure portal to review new vehicle fluid specifications. They map their corresponding oils, coolants, and greases directly to the OEM requirements, review automated validation checks, and publish new product lines to the market with a single click.
How It Works for Mechanics & Drivers
End users simply type in a vehicle license plate number or select their make, model, and year. The platform instantly displays the approved engine, transmission, brake, and differential fluids, along with exact sump capacities and service intervals.
The Four Phases of Delivery
Our cross-functional team included a Delivery Manager, Technical Lead, Backend and Frontend Engineers, QA Specialists, and DevOps Engineers:
Discovery and Schema Normalization
We audited legacy product databases, analyzed OEM fluid specification hierarchies, and structured a unified relational schema to eliminate duplicate vehicle records.
Backend Architecture and Pipeline Engineering
We developed the Java Spring Boot service layer, created high-throughput SSIS data pipelines, and engineered automated validation checks to flag mapping errors.
Integration and Multi-Brand Verification
We built REST API contracts for web and mobile clients, conducted rigorous data validation with client technical teams, and ensured multi-tenant brand isolation.
Cloud Deployment and Performance Tuning
We deployed the platform to AWS, implemented automated CI/CD deployment pipelines, and optimised SQL Server queries to handle high-frequency search spikes.
Measurable Operational and Commercial Outcomes
The transformed platform now powers the digital fluid recommendation tools for the most recognized names in the lubrication industry:
- 70% to 80% Drop in Manual Work: Automated ETL workflows and validation algorithms freed technical specialists from repetitive data entry.
- Instant Publishing Turnaround: Replaced 90-day quarterly release backlogs with immediate, near real-time publishing for newly released lubricants.
- Adopted by Over 23 Leading Brands: Deployed as the trusted recommendation engine for Castrol, Liqui Moly, Penrite, Petronas, and regional manufacturers.
- Consistent Multi-Channel Accuracy: Technicians and consumers receive identical, verified recommendations whether checking online, on mobile, or via in-store touchscreens.
Why This Mattered to the Industry
For major oil companies, recommendation tools are not just reference guides; they are direct drivers of retail and commercial sales. If a workshop technician cannot find an approval match for a customer's car, they will buy a competitor's oil off the shelf. By building a reliable, automated platform, Zediant helped global oil brands get their newest products in front of buyers the moment they hit the market while eliminating the risk of expensive mechanical misapplication.
Positioned for Long-Term Innovation
The platform was engineered as an extensible SaaS foundation, allowing for ongoing feature expansion:
Self-Service Onboarding
Streamlined tenant provisioning allowing new regional oil brands to onboard their catalogs in days rather than months.
ERP & Point-of-Sale Connectivity
Direct integration with dealership and workshop parts counter software to allow instant one-click ordering of recommended oils.
Predictive Fluid Matching
Using machine learning to evaluate new OEM engine announcements and automatically suggest optimal matching formulations from existing catalogs.
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