SAN FRANCISCO, June 02, 2026 (GLOBE NEWSWIRE) -- RelationalAI, a leader in enterprise AI, today announced at Snowflake's annual user conference, Snowflake Summit 26, a series of new capabilities for Rel, its agentic decision intelligence system that runs natively in the Snowflake AI Data Cloud. With these new capabilities, joint customers can give decision agents the context, reasoning, and post-training needed to take action across the operations that drive the bottom line, including pricing, supply chain, network operations, and resource allocation.
Generative AI has unlocked extraordinary value for software development, but most enterprises still see a gap between what AI can do and what they are getting from it across the rest of the business. Today's release introduces the new Rel App, alongside the prescriptive and predictive reasoners, conversational decision intelligence inside Snowflake CoWork, and RelationalAI “push-button” post-training. Together, they give decision agents what they need to act with confidence: a model of the enterprise for context, reasoners as tools, and post-training to turn a general-purpose model into a business expert.
"Just like humans, agents have difficulty knowing how to make good decisions," said Molham Aref, Founder and CEO of RelationalAI. "With these capabilities running natively in the Snowflake AI Data Cloud, customers can close the AI value gap by giving their agents the context, tools, and post-training they need to take the best possible action in the face of uncertainty, at machine speed and at economics that scale across the enterprise."
The new Rel App captures a shared, governed representation of how a business works: the concepts, relationships, and rules that define how decisions get made. Domain experts can explore the model, follow connections, ask questions in natural language, and reason through decisions, with every interaction grounded in their own data inside Snowflake.
Today's release also includes RelationalAI's growing library of coding agent skills, which work across Snowflake CoCo, Claude Code, OpenAI Codex, and GitHub Copilot. Joint customers already use these skills to extend RelationalAI models directly from their preferred development environments, deepening the context their decision agents draw on.
The general availability of the prescriptive reasoner gives Snowflake customers a purpose-built tool for solving constrained optimization problems. The predictive reasoner applies graph neural networks to enterprise data inside Snowflake to forecast outcomes like demand, churn, and asset failure. Paired with the prescriptive reasoner, the predictive reasoner gives decision agents a full path from forecast to recommended action in a single workflow, all without moving data off the platform.
The RelationalAI suite of rule, graph, predictive, and prescriptive reasoners supports complex multi-domain reasoning in a single workflow. Decision agents working in Snowflake can now combine LLM-based reasoning with domain-specific reasoners, with measurable gains in accuracy and significant reductions in cost.
As a launch partner in the Open Semantic Interchange (OSI) initiative, RelationalAI also enables enterprises with existing ontology deployments, such as Palantir, to port semantic models into Snowflake via OSI and run advanced reasoning on RelationalAI with no rebuild required.
“At Snowflake, we’re focused on enabling secure, high-performance AI directly where data lives,” said Amy Kodl, SVP, Worldwide Alliances and Channels at Snowflake. “RelationalAI’s Rel App extends these capabilities by introducing powerful reasoning and semantic modeling within the Snowflake AI Data Cloud, helping customers accelerate the development of intelligent agents and decision intelligence systems.”
RelationalAI also now powers conversational decision intelligence inside Snowflake CoWork letting business users ask ad-hoc questions in natural language and receive governed, semantically grounded answers from RelationalAI's reasoners directly on private data in the Snowflake AI Data Cloud.
RelationalAI is also announcing the private preview of RelationalAI “push-button” post-training, a capability for specializing open-source LLMs against an enterprise's specific data and semantic estate inside Snowflake. Enterprise specific post-trained models, when combined with frontier models, can solve harder problems at a fraction of the cost, while learning the systems, terminology, and decision logic specific to the business they serve.
Check out keynotes from Snowflake Summit 26 live or on-demand here and stay on top of the latest news and announcements from Snowflake on LinkedIn and X.
About RelationalAI
RelationalAI extends the Snowflake AI Data Cloud with enterprise decision intelligence, helping customers close the gap between understanding their Snowflake data and acting on it. Powered by semantic models, advanced reasoners, and post-training of open-weight LLMs, RelationalAI helps organizations build agents that understand business context and drive measurable ROI, all without moving data. Our goal: AI that can help run a company. Learn more at relational.ai.
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