Rewriting technical summaries for 52,000 products was unscalable. AI optimized 10,000+ descriptions and enabled semantic search.
A global specialty chemicals distributor connecting 3,000 suppliers to customers via a complex catalog of 52,000 products and extensive technical documentation.
Rapid growth through mergers created a fragmented data landscape, while the reliance on unstructured documents containing text, tables, and diagrams...
“Handling technical documents at this scale means we're constantly navigating through different formats, languages, and levels of detail. Our goal is to make sense of all this information quickly and reliably to support smarter decisions.”
Global distributor of specialty chemicals and food ingredients.
Cloud-based data warehousing, processing, and analytics platform.
IMCD's Product search and automation is part of this use case:
Related implementations across industries and use cases
Searching 17,000 pages of technical documents delayed customer replies. Now, an AI assistant instantly surfaces exact specs for sales reps.
Email orders took 42 hours to process across five systems. AI agents now parse files and trigger ERP actions in under one minute.
Sellers dug through scattered records for pricing and contracts. Now, they ask a voice AI to instantly generate visual dashboards.
Merchandisers manually updated rules weekly to decode trade slang. Now, AI continuously trains on live data to process complex queries.
Standard AI misinterpreted technical queries. A custom model trained on 154k vetted docs now delivers precise chemical insights.
Manual 12-day checks for EU deforestation rules created risk. Now, an AI traces the supply chain in 3 minutes, ensuring full compliance.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
Staff missed the 30% of leads arriving after hours. AI agents now field 24/7 chats and book tours, prioritizing ready buyers.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.
Rewriting technical summaries for 52,000 products was unscalable. AI optimized 10,000+ descriptions and enabled semantic search.
A global specialty chemicals distributor connecting 3,000 suppliers to customers via a complex catalog of 52,000 products and extensive technical documentation.
Rapid growth through mergers created a fragmented data landscape, while the reliance on unstructured documents containing text, tables, and diagrams...
“Handling technical documents at this scale means we're constantly navigating through different formats, languages, and levels of detail. Our goal is to make sense of all this information quickly and reliably to support smarter decisions.”
Global distributor of specialty chemicals and food ingredients.
Cloud-based data warehousing, processing, and analytics platform.
IMCD's Product search and automation is part of this use case:
Related implementations across industries and use cases
Searching 17,000 pages of technical documents delayed customer replies. Now, an AI assistant instantly surfaces exact specs for sales reps.
Email orders took 42 hours to process across five systems. AI agents now parse files and trigger ERP actions in under one minute.
Sellers dug through scattered records for pricing and contracts. Now, they ask a voice AI to instantly generate visual dashboards.
Merchandisers manually updated rules weekly to decode trade slang. Now, AI continuously trains on live data to process complex queries.
Standard AI misinterpreted technical queries. A custom model trained on 154k vetted docs now delivers precise chemical insights.
Manual 12-day checks for EU deforestation rules created risk. Now, an AI traces the supply chain in 3 minutes, ensuring full compliance.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
Staff missed the 30% of leads arriving after hours. AI agents now field 24/7 chats and book tours, prioritizing ready buyers.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.