Getting the right answers isn't just about AI, it's also about learning and understanding your business. Numbers Station’s semantic catalog collects that knowledge to improve functionality throughout the process. Understanding your intent, guiding you to effective questions, injecting business logic into the conversation, and identifying which dataset is best able to help answer your question are all made possible, both by using the semantic catalog as a resource and by incorporating it into the AI using techniques like Retrieval Augmented Generation (RAG).
As you build more complex questions, Numbers Station retains the context of your data and your business. Together, you and Numbers Station rapidly collaborate to build different scenarios to answer an infinite range of questions from your massive datasets.
You see AI as a strategic asset, and so do we. With our fine-tuning option, you can own your AI forever.
Whether or not you opt for a private LLM, your data is never used to train our model or benefit other customers. Your data is your data.
We've been building data-aware AI as part of Stanford's AI Lab for the better part of a decade, and we're ready to guide you on the journey.
Playing with AI tools is a fun learning experience but wastes time. You need a solution now that knows your business, your data, and how to give meaningful answers. Let us show you how.
Numbers Station's work is based on decades of research and development with Stanford AI specialists, but we are far from academic. Our work is consistently applied to real world business and technology challenges, helping enterprises large and small build lasting and innovative solutions on our foundational AI platform.
support AI for a
competitive advantage
of retail executives plan to
adopt AI automation by 2025
AI will contribute $15.7
trillion to the global economy by 2030
Let us share what we've learned with you.
Despite the hype around LLMs and their potential, enterprises struggle to get these models in production. In this blog, we outline the challenges presented in today's environment and share key pillars to enable enterprises to successfully bring generative AI into production to supercharge analytics.
Read More ->Struggling with prototyping AI solutions? Wasting time using insecure and labor-intensive approaches? Want to use AI but don't know how to start? We can help. Drop us a note and we'll get you started on your AI journey!
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