Snowflake Intelligence, aimed at non-technical staff, is among the platforms on the market today that advertise an ability to execute tasks inside existing business workflows. Users can describe to the LLM what they’d like to see happen in natural language, and it execute given tasks. Snowflake lists preparing presentations, running multi-step analyses, and sending follow-up messages as some of the uses it envisages. Data can be drawn from an organisation’s internal and linked digital assets, including structured and unstructured data, with external sourcese connected by various protocols and pre-built connectors.

User queries and ensuing workflows will be carefully limited in terms of access permissions and organisational governance, helping to prevent incidents of data loss and non-compliance.

New interfaces using MCP (Model Context Protocol) are available, and the company has named the Google business suite, Jira, and Salesforce (including Slack) as among the systems Snowflake Intelligence can now interface with. Also in the works is an iOS app for Snowflake Intelligence which will enter public preview “soon”.

Snowflake says its Intelligence platform becomes more personalised over time, learning from user behaviour. Users will be able to save and share workflows so that work can be reused. Longer context windows – personalisation – mean that users addressing the large language model should not have to repeat long, contextualised prompts to get the results they want.

The updates have come about as a result of feedback from Project SnowWork, a research project launched last month to showcase the platform and garner users’ preferences as to what features they’d like to see from an AI platform.

Cortex Code is designed for software development teams in the enterprise, an area in which AI algorithms can prove successful at lower level tasks. Cortex Code is described in company press release as a coding and orchestration “layer” with new options for integration with external data sources, now supporting AWS Glue, Databricks, and Postgres. Cortex Code can also connect to other language models via MCP and ACP (agent communication protocol), the more commerce-driven protocol that emerged around the same time as the Anthropic-stewarded MCP.

VS Code users will soon see Cortex Code as an extension (it’s currently in private preview), and a Snowflake plugin for Claude Code is currently under development. Snowflake’s Agent Software Development Kit for Python and TypeScript is available, so teams can embed Cortex Code functions in their own applications.

Cloud Agents, also in private preview, are to appear in Snowsight, Snowflake’s browser-based interface. Plan Mode lets users preview and approve workflows before AI execution, and the company is working on a facility by which end-users can see detail of longer research processes the LLM undertakes to vet the veracity of its processes.

Snowflake says more than 9,100 customers use its AI products weekly. Since its launch six months ago, Snowflake says more than half of its customers are using Snowflake Intelligence and Cortex Code.

The company’s dual-pronged approach – mainstream business users and software development teams – doubles down on the company’s core technical market, but widens its the platform’s adoption among general business function users. The new software connectors, mobile app, and browser-based options will create a broader market of users, and the additional support for existing systems will widen its appeal among enterprises with embedded workflows and software platforms.

Sameer Vuyyuru, chief AI and product officer at Capita, said: “Snowflake helps us deploy AI securely and with the right governance across highly regulated, citizen-facing services where performance, compliance and trust are critical.”

(Image source: “The snow” by telafree is licensed under CC BY-NC 2.0.)

 

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