Engineers of a manufacturing company sat on decades of technical reports nobody could easily search. Modulai built a secure, self-hosted multimodal RAG system that ingests documents, images, and tables, so R&D teams tap the company's collective knowledge in seconds.
Stats
100K+
Documents indexed
1000s
Engineers served
10+
Departments served
Challenge
The R&D department had accumulated years of technical reports covering designs, tests, and experiments, but that knowledge was scattered across formats and hard to find. Engineers repeated work and missed prior learnings simply because the relevant report was buried. The data was also highly sensitive, so any solution had to meet strict security requirements and keep proprietary information fully under the company's control.
Solution
Modulai built an advanced multimodal RAG system on a complex ingestion pipeline that parses technical documents and embeds and indexes their text, images, and tables alike. Engineers query it in natural language and retrieve grounded answers drawn from the full archive, whatever format the source took. It runs on self-hosted LLMs so sensitive data never leaves the company's environment, deployed on cloud infrastructure defined entirely as code.
Tools
The system pairs self-hosted large language models with a retrieval pipeline that handles mixed-format content, embedding and indexing text, images, and tables for unified search. A complex ingestion pipeline parses varied technical documents into retrievable pieces. Everything runs on cloud infrastructure provisioned through infrastructure as code, giving a reproducible, secure deployment that meets the department's strict data-handling rules.
Value created
Engineers can now reach decades of accumulated R&D knowledge through a single search, pulling specifics on past designs, tests, and results without digging through archives. That saves time and surfaces prior learnings that would otherwise stay siloed, so research and development can build on what the company already knows. Because the system is self-hosted and built with infrastructure as code, it does this while keeping sensitive data secure.
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