Version 8.0 also anticipates the future. The catalogue has been updated to include a comprehensive database for Electric Vehicle (EV) components, aligning with India’s pivot towards green mobility. This ensures that as the nation’s fleet transitions from internal combustion engines to electric drivetrains, the supply chain infrastructure is ready to support the new technology.
: Ensures dealers have access to updated price lists, including historical price tracking, to prevent billing conflicts between dealers and OEMs.
Implementing Intelli Catalogue ML - Version 8.0 in India requires a structured approach to ensure smooth integration and minimal disruption to business operations. The solution provider offers a range of services, including:
+-----------------------------------------------------------------------+ | Intelli Catalogue ML 8.0 | +-----------------------------------------------------------------------+ | [AI Visual Search] --> [ML Supersession Engine] --> [ERP Bridge] | | (Camera/Image) (Part History/Options) (Live Pricing)| +-----------------------------------------------------------------------+ | Core Data Layer | | (Interactive 2D/3D Hotspots & Regional Analytics) | +-----------------------------------------------------------------------+ 1. Machine Learning-Powered Visual Search intelli catalogue ml - version 8.0 -india-
is an advanced, AI-powered Electronic Parts Catalogue (EPC) software engineered specifically for Indian Original Equipment Manufacturers (OEMs) to optimize their aftermarket spare parts supply chains . Developed by Intellinet Systems , this specialized platform serves as a digital bridge between automotive, agricultural, and industrial manufacturing companies and their nationwide dealer networks.
: Automatically updates catalogs when parts are replaced by newer versions, preventing the ordering of obsolete stock.
Customers can find products using colloquial terms or descriptive phrases, not just exact part numbers. Version 8
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
The catalogue uses an inference layer built on TensorFlow Lite, optimized for ARM-based servers (common in Indian edge data centers). This allows real-time tagging as data is ingested, with a latency of under 200 milliseconds per asset.
Instead of typing complex serial numbers, a field technician can simply upload a photo of a worn-out or damaged component. The underlying machine learning model scans the part’s geometry, maps it against the OEM's global CAD repository, and instantly identifies the exact part number and its corresponding model variant. 2. Natural Language Processing (NLP) for Regional Terms : Ensures dealers have access to updated price
: Accurate identification through 3D diagrams significantly cuts down on costly part returns.
Recognizing the rapid digitization of service centers in India, Version 8.0 is optimized for mobile devices, enabling mechanics to access the catalog directly on the service bay floor. Impact on the Indian Aftermarket Industry
: Faster parts identification leads to quicker vehicle turnaround times in service centers, directly boosting customer satisfaction and aftermarket revenue.
: This is a machine learning-driven demand forecasting tool. It uses historical sales data alongside secondary environmental factors—such as dealership location weather patterns
Intelli Catalog is widely used by major Indian automotive and industrial players, including and Maruti Suzuki .
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