Snowflake AI Gets a Major Upgrade: Here's What Enterprise Teams Need to Know

Snowflake just dropped a significant update to its enterprise AI capabilities, and it’s designed to make building AI applications way simpler for organizations of all sizes. At Snowflake Summit 2024, the company rolled out enhancements to Snowflake Cortex AI and launched new AI & ML Studio features that fundamentally change how businesses interact with their data.

Talk to Your Data in Minutes, Not Months

The headline feature? Two new conversational AI capabilities that let you build chatbots against your enterprise data without the typical operational headaches.

Cortex Analyst (coming soon to public preview) taps Meta’s Llama 3 and Mistral Large to let teams quickly build applications on top of their analytical data. Rather than wrestling with dashboards and information overload, users can ask natural language questions directly against structured datasets and get instant answers with visualizations.

Cortex Search takes a different approach, combining retrieval technology from Neeva (acquired by Snowflake in 2023) with Snowflake Arctic embed. This means enterprises can search documents and unstructured text using hybrid search — blending vector and traditional text search into one service.

Zoom and Bayer are already using these capabilities to accelerate decision-making. Zoom’s teams built AI apps leveraging pre-trained large language models in just days. Bayer replaced time-consuming dashboard development with direct data queries, dramatically cutting development cycles.

Safety First: Introducing Cortex Guard

Building production-grade AI at scale demands serious security controls. Enter Cortex Guard (coming soon), which uses Meta’s Llama Guard to filter harmful content and protect organizational data. It flags everything from violence and hate speech to self-harm and criminal activity — ensuring your AI models stay trusted and compliant.

Pre-Built AI Tools That Actually Work

Beyond custom chat experiences, Snowflake is shipping pre-built tools:

Document AI (generally available soon) extracts key information — invoice amounts, contract terms, etc. — from documents using Snowflake’s multimodal LLM, Arctic-TILT, which outperforms GPT-4 on the DocVQA benchmark. Northern Trust is already using it to process documents at scale with higher accuracy.

Snowflake Copilot (generally available soon) combines Mistral Large with Snowflake’s proprietary SQL model, accelerating productivity for SQL users across your organization.

No-Code AI Development Gets Real

The new Snowflake AI & ML Studio (private preview) removes the technical barriers entirely. Teams can test and compare models from Google, Meta, Mistral AI, Reka, and Snowflake’s own Arctic LLM — then pick the most cost-effective option for their use case.

Want to customize models further? Cortex Fine-Tuning (now in public preview) lets you fine-tune Meta and Mistral models serverless-style through simple SQL functions. Fine-tuned models stay governed through Snowflake’s role-based access controls.

Managing AI at Scale: Snowflake ML in Action

Once models are in production, the real challenge begins — managing them across evolving datasets. That’s where Snowflake ML comes in, bringing MLOps to the AI Data Cloud.

The Model Registry (now generally available) centralizes governance of all AI models, enabling secure access and cost-saving automations.

New additions include the Feature Store (public preview) for creating and serving consistent ML features, and ML Lineage (private preview) to trace how features, datasets, and models flow through your entire ML lifecycle.

The Bottom Line

Enterprise AI just got more accessible. Snowflake’s unified platform removes friction from building, deploying, and governing AI applications — whether you’re data scientists, SQL users, or business teams. Less complexity, more control, trusted AI at scale.