Picture this: You're running a global financial powerhouse with 135 marketplaces across 55+ countries, drowning in 160 petabytes of data (that's enough to store every Netflix show ever made about 20,000 times). Your teams are scattered across different business units, each speaking their own tech language, and innovation is moving at the speed of molasses.

That was Nasdaq's reality. The challenge wasn't just technical—it was cultural. How do you create an AI platform that doesn't just work, but actually gets adopted by busy professionals who'd rather focus on markets than machine learning?

Nasdaq's answer was brilliantly simple: build an internal AI platform that feels as familiar as your favorite coffee shop. Using NVIDIA NeMo Retriever and NIM microservices, they created a unified AI ecosystem that lets employees across all business units tap into the company's vast data treasure trove without needing a PhD in computer science.

The platform works like a super-smart research assistant that can instantly pull insights from Nasdaq's entire data universe—from market analytics to regulatory documents—and serve them up in plain English.

Here's where Nasdaq got clever: instead of building everything from scratch, they leveraged NVIDIA's pre-built AI components like digital Lego blocks. The platform uses:

• NVIDIA NeMo Retriever for lightning-fast information extraction and sophisticated chatbots
• NIM microservices for scalable AI deployment and model management
• GPU-accelerated processing with NVIDIA L40 GPUs for handling massive data volumes
• Self-hosted GPU embeddings that dramatically cut costs compared to managed services

The beauty? Users get a no-code data integration experience with easy API linking, making AI accessible to everyone from marketing mavens to legal eagles.

Even tech giants hit speed bumps. Nasdaq's biggest hurdle? Getting people to actually use the platform. You can build the world's smartest AI, but if your team treats it like that expensive gym membership they never use, you're toast.

Initial challenges included:

• Slow embedding operations that were unacceptable for high-performance environments
• Escalating costs and high latency as usage grew
• Need for increased model accuracy as more users joined
• Ensuring accessibility across all skill levels while maintaining security

Their solution was genius: hackathons. Instead of top-down mandates, they let employees discover AI's potential through hands-on experimentation. Four global hackathons, each spanning three days per region, generated hundreds of hacks and provided valuable ROI data. The engineering department saw 50 hacks focused on internal processes, while customer service benefited from 30 efficient chatbot solutions.

The numbers don't lie—and they're impressive:

• 30% faster response times for data queries and analysis
• 30% improvement in accuracy across AI-powered tasks, reducing human intervention needs
• Substantial long-term cost savings through automation and optimized resource usage
• Real-time performance insights enabling swift issue identification and resolution
• Predictable costs and scalability through NVIDIA AI Enterprise subscription model

But here's the kicker: these aren't just vanity metrics. Faster, more accurate data analysis means better trading decisions, improved risk management, and ultimately, more profitable operations across Nasdaq's global empire.

Three golden rules from Nasdaq's AI transformation:

• Hackathons Beat Mandates: Nasdaq's global hackathons turned skeptics into AI evangelists by letting employees experiment hands-on. The engineering department saw 50 hacks focused on internal processes, while customer service benefited from 30 efficient chatbot solutions.
• User Experience Trumps Technology: The platform was designed to be user-friendly with no-code data integration. Marketing teams took the lead in usage while legal focused on risk and regulatory compliance.
• Start Internal, Scale External: Prove AI works for your own teams before selling it to customers. The hackathons demonstrated potential to significantly enhance daily efficiency across the company.

Think of Nasdaq's current AI platform as just the opening act—the real show is about to begin. With over 5,000 companies listing securities on Nasdaq's exchanges and technology powering 135 marketplaces in 55+ countries, the expansion potential is staggering.

The roadmap includes:

• Regulatory Pipeline Revolution: Using NVIDIA NeMo Retriever extraction to automate compliance processes that currently require armies of human reviewers. The multi-modal processing capabilities will handle both text and image data more efficiently.
• Beyond Text, Into Visual Territory: Extending the platform with image generation and multimodal guardrails, enabling users to generate content for images and charts on GPU clusters—dramatically improving quality and speed.
• GPU-Accelerated Vector Stores: Enhancing query performance with NVIDIA RAPIDS cuVS-accelerated vector stores to optimize handling of large datasets, ensuring data stores remain efficient even as platform usage explodes.

🐯 Tiger Takeaway:

Nasdaq cracked the code on enterprise AI adoption: make it useful, make it easy, and let users discover its power organically through hackathons. The result? A platform that doesn't just process data—it transforms how a global financial giant operates. Their secret sauce: treating AI adoption like a cultural transformation, not just a technology deployment.

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