Stockouts derail operational timelines. The Intelli Forecast module uses ML models to look beyond flat historical sales data.
represents the next generation of cloud-based, AI-driven Electronic Parts Catalogue (EPC) solutions tailored for original equipment manufacturers (OEMs) and dealership networks . Primarily utilized across India's booming automotive, agricultural machinery, and industrial manufacturing sectors, this enterprise software acts as a single, synchronized hub for publishing interactive parts manuals, processing B2B spare parts orders, and managing after-sales service documentation. By embedding specialized Machine Learning (ML) layers into Version 8.0, the platform addresses long-standing challenges in inventory forecasting, inaccurate parts identification, and complex supply chain distributions common to the Indian market. Core Architecture and Features of Version 8.0
Redefining Spare Parts Excellence: Introducing Intelli Catalog ML 8.0
The new version leverages high-definition 2D and 3D exploded-view illustrations. A critical feature is "hotspotting"—clicking on a specific part in a 3D model automatically pulls up its inventory status, price, and supersession history. For complex machinery prevalent in India’s industrial sector, this visual accuracy is a game-changer, preventing the costly error of ordering the wrong hydraulic valve or gear assembly. intelli catalogue ml - version 8.0 -india-
Understanding data origin is critical for financial auditing and regulatory reporting. Version 8.0 traces data from its ingestion source through transformations (ETL/ELT pipelines) down to the final BI dashboards, providing clear end-to-end visibility. 4. Industry-Specific Use Cases Banking and Financial Services (BFSI)
to streamline parts identification and dealer communication. The Evolution of Spare Parts Management
India is witnessing a digital revolution unlike any other. From the rapid expansion of 5G services in Tier-2 cities to the Smart City Mission’s deployment of thousands of IoT sensors, the volume of geospatial and network data generated daily has reached petabytes. For telecom operators, infrastructure providers, and government agencies, managing this data is no longer a logistical challenge—it is a survival metric. Stockouts derail operational timelines
Version 8.0 introduces several core upgrades designed to handle the complexity of modern inventory:
: Manufacturers can update prices and part enhancements globally, ensuring dealers never work with outdated information.
: Simplifies queries by matching informal user phrases (e.g., "front brake ring line") with rigid, official technical descriptions stored by engineering departments. A critical feature is "hotspotting"—clicking on a specific
Available as a light web interface and optimized for native Android and iOS apps, ensuring seamless usability on mobile devices used by field mechanics.
Allows users to click a 3D model area (e.g., front bumper assembly) to instantly generate an associated parts list. 3. Machine Learning (ML) & Predictive Analytics
From the snowy peaks of Ladakh to the dense mangrove forests of Sundarbans, terrain data varies wildly. Version 8.0 includes a "Geozone Classifier" ML model that auto-tags assets based on terrain risk. For instance, a tower catalogue entry in Himachal Pradesh automatically receives "Avalanche Zone: Low" or "Landslide Zone: Medium" tags based on ISRO satellite data integration.
Intelli has already announced for Q4 2025, focusing on Generative AI. This upcoming release will allow users to ask natural language questions like, "Show me all 4G towers in Kerala that have a power backup less than 3 hours" and receive an instant SQL query and visual map.