See how we engineered a multimodal RAG system for an auto parts giant that searches across ERPs, documents, emails, and databases - processing millions of products with instant semantic search and complete source attribution.
"Single search interface replaced 5 different systems. Our teams now find any information in seconds with complete source tracking."
David Martinez
CTO, Auto Parts Manufacturer
Enterprise RAG Stack
Answer: Synthetic motor oil covers up to 300,000 miles or 10 years. However, it is recommended to change every 7,500 miles or 12 months.
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Related Questions:
Our client, a major auto parts manufacturer, was struggling with information scattered across legacy ERPs, modern systems, emails, and documents. Teams couldn't find what they needed.
5 different search systems
Teams had to search multiple places
No source attribution
Couldn't verify information accuracy
Keyword-only search
Missed relevant results with different wording
30+ min to find answers
Product information scattered everywhere
Single unified interface
All systems searchable from one place
Complete source citations
Every answer linked to original source
Semantic understanding
Finds answers regardless of wording
< 1 second responses
Instant access to all information
Our sophisticated multimodal RAG system combines vector search, semantic understanding, and intelligent retrieval to deliver instant, accurate answers with full source attribution.
Processes ERPs, documents, emails, and databases in real-time
Vector embeddings and semantic search across all content
LLM-powered answers with complete source attribution
Data Ingestion
Continuously indexes ERPs, documents, emails, databases
Vector Processing
Creates embeddings and stores in Pinecone vector DB
Query Understanding
Processes natural language queries semantically
Hybrid Search
Combines vector + keyword search for best results
Answer Generation
LLM generates answer with full source citations
Every feature designed to make enterprise search instant, accurate, and verifiable
Every answer includes exact source citations - document, page, section, and even specific reviews or Q&As
Search across text, images, PDFs, spreadsheets, emails, and any document format in your enterprise
AI suggests related questions based on product Q&As, reviews, and common queries for deeper insights
Search within specific products or across entire database, with granular control over search scope
New documents, emails, and data are indexed instantly - search results always current
RESTful APIs for easy integration with WhatsApp, web chat, and any enterprise application