Enterprise Knowledge Search · Real-time Analytics
TinyFish needed retrieval technology accurate enough to let thousands of AI agents automate web research, product matching, and data extraction for enterprise users without forcing customers to wait weeks for conventional ETL-driven reporting.
Reported impact
TinyFish gives enterprise knowledge workers access to fresh, structured web intelligence without waiting for long ETL cycles, accelerating decisions in product matching, pricing analysis, and related research-heavy workflows.
TinyFish built its intelligent web engine around Voyage AI models and MongoDB so specialized agents can turn noisy internet content into structured business intelligence. The platform deploys thousands of collaborating AI agents that browse sites, extract information, and assemble fresh web data for use cases such as retailer product matching, competitive pricing analysis, and social sentiment tracking. Voyage AI's voyage-3.5 embedding model is used to index competitor catalogs and retrieve an initial candidate set, while rerank-2.5 refines the results to the most relevant matches. MongoDB Atlas provides the document-oriented data layer for storing unstructured web content and the structured outputs those agents create, giving TinyFish a flexible foundation for enterprise-scale retrieval and fast iteration as new research workflows are added.
TinyFish's web agents gather internet and catalog data, voyage-3.5 turns that content into embeddings for initial retrieval, rerank-2.5 narrows the candidate set, and MongoDB Atlas stores both extracted documents and structured intelligence so enterprises can act on fresh results immediately.
“Instead of waiting weeks for data to move through traditional ETL processes and dashboard updates, businesses can make decisions based on fresh, accurate information extracted in real time.”
“The Voyage AI rerank-2.5 reranking model then refines the results to surface the most relevant options.”
“The company’s platform deploys thousands of specialized AI agents that autonomously perform the web-based research and data extraction tasks that typically consume knowledge workers’ most valuable time.”
“The platform uses the Voyage AI voyage-3.5 embedding model to index competitor catalogs and quickly identify an initial set of similar products to what vendors are selling.”
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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