Enterprise Knowledge Search
Nasdaq needed an enterprise AI platform that could search and retrieve business data quickly and accurately for internal and external use cases, but slow embeddings, high latency, rising costs, and accuracy issues limited adoption in a performance-sensitive financial environment.
Reported impact
Nasdaq improved response times by 30 percent, increased conversational accuracy by 30 percent, reduced long-term costs with self-hosted GPU embeddings and AI Enterprise pricing, and expanded adoption through hackathons that turned the platform into a daily workflow tool across the company.
Nasdaq modernized its AI platform with NVIDIA NeMo Retriever, NVIDIA NIM, and NVIDIA AI Enterprise to improve how employees and applications retrieve business and regulatory information. NeMo Retriever connects custom models to diverse enterprise data and generates higher-quality embeddings for chatbots and conversational interfaces, while NIM simplifies model deployment and exposes real-time performance feedback so the team can spot indexing and response issues quickly. Nasdaq also moved to self-hosted GPU embeddings and NVIDIA L40 GPU-backed infrastructure to speed up retrieval and lower costs in high-volume workloads. The platform was validated through four global hackathons that exercised coders and non-coders, shaping features such as API-based chat, no-code data connectivity, and broader tool integrations. Together, the stack creates a scalable retrieval platform that serves users across Nasdaq's financial-data ecosystem while remaining fast, predictable, and secure.
Enterprise and business data is embedded through NeMo Retriever, NIM serves the AI models and surfaces performance insights, users access chatbots or other conversational interfaces through the platform, and the resulting interactions feed back into live indexing and feature prioritization across Nasdaq's internal and external AI products.
"Moving to NeMo Retriever and NIM allowed us to build up more engagement with the platform, because it was coming back faster."
Built with NVIDIA NeMo™ Retriever and NVIDIA NIM™ microservices, part of NVIDIA AI Enterprise, Nasdaq's AI platform is designed to be scalable, secure, and user-friendly.
By implementing self-hosted GPU embeddings using NVIDIA NIM, Nasdaq significantly reduced expenses and optimized resource usage.
Chatbots and conversational interfaces saw a 30% boost in accuracy.
NeMo Retriever microservices enhanced search capabilities, leading to more accurate and relevant results.
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Scoring methodology
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Traceability
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