Snowflake’s Evolution with Reka AI

In today’s world, generative models have become essential tools, shaping various aspects of our lives. From language models to multimodal counterparts, these technologies have already made significant impacts. However, we’re just scratching the surface of their potential. Looking ahead, the next decade promises even more remarkable advancements in this field. As researchers uncover new capabilities and make breakthroughs, we can expect further innovation, revolutionizing how we interact with AI in the years to come.

In this journey of innovation, the collaboration between Snowflake and Reka AI stands out, reshaping data platforms with advanced integration. This partnership brings cutting-edge multimodal models and ensures data security and governance, empowering businesses to thrive in the AI-driven future.

Snowflake and AI

The Partnership: Snowflake and Reka AI

A groundbreaking partnership emerged between Snowflake, the leading data cloud company led by Sridhar Ramaswamy, and Reka, an innovative AI startup founded by researchers from Google, Meta, and Deep. This collaboration is set to revolutionize data platforms by integrating Reka’s AI into Snowflake’s already robust infrastructure.

Through this integration, enterprises can now harness the power of generative AI applications, seamlessly working with text, images, and videos, opening doors to a plethora of possibilities in data analysis and utilization. Snowflake’s commitment to innovation is further demonstrated by its previous investment in Reka AI, showcasing its dedication to pushing the boundaries of data technology. This partnership marks a significant step forward in Snowflake’s journey towards providing unparalleled data analytics solutions, setting a new standard in the industry.

Reka AI and Why Invest in it?

Reka AI

Reka, headquartered in San Francisco, was founded by a team of visionary individuals. Drawing from their experience working on AI systems, the founders recognized the impracticality of deploying a single large Language Model (LLM) to address all potential use cases. This realization led to the development of Reka’s innovative approach to AI, tailored to meet the diverse needs of businesses and industries.

Reka’s Distinctive Approach To LLMs To Empower Businesses

  • Reka offers businesses access to Large Language Models (LLMs) without common trade-offs.
  • The Yasa models by Reka ensure data privacy and efficiency, distinguishing them from other solutions.
  • Businesses benefit from cost-effectiveness and energy efficiency with Reka’s models.
  • Reka’s approach eliminates the need for extensive in-house research teams to develop LLMs from scratch.
  • With the goal of every business becoming an “AI” business, Reka provides production-ready foundation models to empower enterprises.

What Technology Does Snowflake Use

Snowflake Tech Stack

  • Self-Managed Service:

No hardware or software to install or manage.

  • Cloud Infrastructure:

Runs entirely on public cloud infrastructures.

  • Unique Architecture:

A hybrid of shared-disk and shared-nothing database architectures.

  • Database Storage:

Data is stored in an optimized, compressed, columnar format in cloud storage.

  • Query Processing:

Executed in the processing layer.

  • Technologies Used:

Includes HTML5, jQuery, Google Analytics, and 67 other technologies.

Snowflake for AI and ML

Snowflake’s Role in AI and ML

In today’s rapidly evolving digital landscape, businesses are seeking innovative solutions to bridge the gap between AI technologies and tangible business value. Enter Snowflake, the leading data platform, offering a suite of tools tailored to streamline ML and AI integration seamlessly. Here’s how Snowflake data services empower enterprises to turn AI models into interactive applications and extract maximum value from their data:

  • AI Transformation:

Snowflake helps turn AI models into interactive apps using Streamlit, a powerful open-source tool. With Python, developers can quickly create and deploy feature-packed apps. Snowflake’s scalability and security ensure smooth deployment and sharing of these AI-powered apps, boosting efficiency and sparking innovation in businesses.

  • LLM Optimization:

Snowflake offers a protected space for refining Large Language Models (LLMs) within its platform. Users can effortlessly deploy, oversee, and expand containerized models, taking advantage of Snowflake’s managed infrastructure equipped with GPUs. This streamlined approach not only guarantees data security and adherence to regulations but also maximizes the efficiency of LLMs, thereby enhancing their effectiveness in real-world scenarios.

  • Streamlined Development:

Snowflake’s Snowpark ML simplifies the process for data scientists to create and deploy machine learning models. Using familiar Python coding, developers can build and train models directly within Snowflake’s platform, without needing to move data elsewhere. With features like Snowpark ML Modeling and the Snowpark Model Registry, businesses can easily manage and scale their models, ensuring smooth integration into their existing workflows.

  • AI Integration:

Snowflake Cortex, currently available for public preview, is a smart, fully managed service crafted to seamlessly blend Generative AI and LLMs into business data ecosystems. This service enables companies to swiftly and securely analyze data and create AI applications utilizing top-notch LLMs and vector functions. By doing so, businesses unlock fresh insights and foster innovation across their organizations.

Which Cloud is Best for AI and ML

Which Cloud for AI and ML

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Choosing the Best Cloud Platform for AI & ML

Snowflake offers a robust platform for AI and ML providing a scalable and consistent data delivery layer for all cases.

  • Cortex:

It provides pre-built AI functions and supports custom AI applications, making it easy for users to access and utilize AI capabilities. With its user-friendly interface and low risk, Cortex is set to transform AI and ML development within the Snowflake platform.

  • Scalability for Dynamic AI Workloads:

Snowflake’s scalability is like having a super-flexible tool for AI. It lets companies easily adjust how much computing power they need for different AI tasks. Whether it’s training a model or crunching a lot of data, Snowflake can handle it smoothly without hassles.

  • Snowflake Marketplace:

The Snowflake Marketplace lets users seamlessly discover and integrate third-party data and solutions. It expands Snowflake’s capabilities by offering access to various datasets and applications, improving AI models, and delivering value to businesses

  • Snowpark ML:

Snowpark ML within Snowflake simplifies machine-learning tasks. It offers streamlined data preparation, model training, and deployment, all integrated into Snowflake’s platform. Users can easily fine-tune features, manage models, and access data for efficient ML workflows. Additionally, Snowpark Container Services enables seamless deployment of containerized applications, fostering innovation in AI development.

How is AI used in Snowflake

Exploring Snowflake’s Innovative Uses of Reka AI

This collaboration between Snowflake Data Cloud and Reka AI isn’t just reshaping data platforms; it’s revolutionizing entire industries. With more than 400 enterprises already harnessing the power of Snowflake’s Cortex and the hosted models, the landscape of generative AI applications is evolving rapidly. From bolstering cybersecurity measures with advanced vulnerability analysis to enhancing patient care through seamless interactions with intelligent chatbots, the potential for innovation knows no bounds. This partnership is not just about transforming data; it’s about transforming how businesses operate and deliver value in an increasingly digital world.

User Excitement and Adoption

Customers eagerly anticipate applications like chart-interpreting chatbots and automated content generation in entertainment, reflecting over 400 enterprises leveraging Cortex and its hosted models. These applications span diverse domains, from analyzing service ticket vulnerabilities to facilitating healthcare provider interactions with insurer data.

Reka AI Inclusion: Use Cases and Applications

Snowflake users can extend generative AI applications beyond text. These applications seamlessly incorporate images and videos, unlocking myriad use cases such as video captioning, image labeling, dynamic product descriptions, and data-driven insights derived from charts. It enhances capabilities such as chart-interpreting chatbots and content generation from visual assets. Cortex, already hosting various LLMs, including those from Mistral and Google, will offer a total of twelve models with Reka AI inclusion.

  • Captioning Videos:

Snowflake users can leverage Reka AI to automatically generate accurate and contextually relevant captions for videos, enhancing accessibility and user experience.

  • Labeling Images:

By integrating Reka AI, Snowflake enables users to efficiently label and categorize images, facilitating easier organization and retrieval of visual data for various applications such as content management and analysis.

  • Generating Product Descriptions:

Reka AI empower Snowflake users to automate the process of creating compelling and informative product descriptions. This capability streamlines e-commerce operations, improves product visibility, and enhances customer engagement.

  • Answering Analytical Questions:

Snowflake users can utilize Reka AI to generate insightful responses to analytical inquiries, facilitating data-driven decision-making processes across various industries and business functions.

How to Use AI Assistant in Snowflake

Use AI Assistant in Snowflake

Snowflake’s innovative approach to leveraging generative AI development services opens up new possibilities for data analysis and application development, promising greater efficiency and value for businesses across industries. Snowflake is changing how businesses use AI by making advanced generative AI models accessible to everyone. This ground-breaking service allows users of any expertise level to utilize top-tier AI models, LLMs, and beyond right within the Snowflake platform.

  • Cost-Effective Models for Unstructured Data:

Snowflake Cortex provides cost-effective LLM-based models for tasks such as answer extraction, sentiment detection, text summarization, and translation. These models are ideal for working with unstructured data and offer efficient solutions for various use cases.

  • Serverless Functions in Snowflake Cortex:

Snowflake Cortex offers a suite of serverless functions designed to streamline analytics and app development. Users can easily access specialized ML and LLM models with just a single line of SQL or Python, eliminating the need for complex infrastructure management.

  • Snowflake Copilot:

Snowflake Copilot is an LLM-powered assistant that generates SQL queries using natural language. This feature simplifies the data querying process and enables users to refine queries through conversation, improving efficiency and productivity.

  • ML-Based Models for Data Analysis:

Snowflake Cortex offers ML-based models for tasks like forecasting, anomaly detection, and contribution exploration. These models enable users to gain valuable insights from their data and make informed decisions.

  • Universal Search and Document AI:

Universal Search allows users to quickly discover and access data and apps within the Snowflake platform. Additionally, Document AI enables data extraction from various document formats, offering a scalable solution for automation and resource optimization.

  • State-of-the-Art Models for General Use:

Snowflake Cortex includes state-of-the-art models that can be used for more general purposes, such as text completion and text-to-SQL conversion. These models empower users to build powerful AI applications with ease.

  • Native LLM Experiences on Snowflake Cortex:

Snowflake Cortex enhances the user experience with pre-built interfaces, high-performance LLMs, and search capabilities. Features like Snowflake Copilot and Universal Search provide intuitive ways to interact with data and streamline workflows.

Reka AI Partnership Benefits for Snowflake

Snowflake is dedicated to empowering its customers with the transformative capabilities of Reka AI, enabling them to make informed decisions, enhance productivity, and extend their reach to a broader customer base by leveraging diverse datasets.

  • Ensuring Data Security and Governance:

Teaming up with Reka AI, Snowflake makes sure its users can make the most of different types of data using advanced AI in a safe environment. With Snowflake’s built-in security and governance, businesses can explore new ideas without worrying about data safety, giving them the confidence to innovate freely.

  • Supporting Multimodal Models:

Working together, Snowflake and Reka AI have greatly improved support for flexible multimodal models in the Cortex. This includes adding Flash, which is great for everyday queries, and continuing to enhance support for Core, Reka AI’s most powerful model yet.

  • Access to Cutting-Edge AI Technologies:

With Reka AI, Snowflake users now have the opportunity to tap into the top-notch multimodal assistant. This means they can easily utilize advanced AI tools right within their Snowflake setup. With this smooth integration, users can deploy and adjust AI models hassle-free, all through the familiar Snowflake interface they’re accustomed to.

  • Investment in AI Excellence:

Snowflake and Reka AI’s joining forces show how serious Snowflake is about making AI accessible to everyone. They focus on making AI easy to use, secure, and quick to set up, whether you’re a business expert or a tech pro. This partnership is all about investing in better AI tools to help businesses grow and innovate.


Snowflake’s collaboration with Reka AI marks a significant milestone in expanding Snowflake’s AI capabilities, equipping its customers with robust tools to develop sophisticated AI applications. By joining forces, Snowflake and Reka are poised to drive innovation, enabling businesses to thrive in the era of AI-driven transformation.

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