Altair RapidMiner Data Analytics and AI Platform Features Expanded Agentic AI

Altair shares major updates across Altair RapidMiner, its data analytics and AI platform, to help organizations operationalize intelligence, bridging human insight, data automation, and agentic AI collaboration across a unified ecosystem, the company reports.

The latest updates strengthen Altair’s data analytics and AI ecosystem, allowing organizations to build scalable, intelligent data environments.

“The latest updates help organizations move from isolated analytics to fully connected intelligence,” says Sam Mahalingham, chief technology officer, Altair, and head of simulation, Siemens Digital Industries Software. “By bringing together AI, data governance, and real-time decisioning, Altair enables every team—from business analysts to data scientists—to turn data into action faster and more confidently than ever before.”

Connected Intelligence

Altair AI Cloud delivers a secure foundation for deploying intelligent, multi-agent systems at scale, the company shares. Through the new Agent Studio, users can build and orchestrate agentic workflows combining large language models (LLMs), machine learning, and enterprise data in one environment. Enhanced multi-agent collaboration allows agents to reason, retrieve, and automate tasks collectively. 

Altair Graph Studio anchors Altair’s ecosystem with semantic data intelligence and governance for agentic systems. With Model Context Protocol (MCP) integration, agents directly interact with Graph Studio to query, reason and make decisions, while embedded LLM-powered copilots simplify metadata management and ontology creation. The release also introduces granular attribute-based access controls and policy-driven governance for improved privacy, compliance, and lifecycle management, according to Altair.

With Altair Panopticon, the update introduces a rebuilt network graph visualization with node-edge detail, customizable labels, and advanced styling options. A new guided workbook experience walks users through dashboard creation, while automatic data refresh keeps visualizations aligned with live data. 

Unified Analytics

Altair SLC broadens language coverage and data connectivity with a new Databricks connector, expanded HDFS and Tagsets.RTF support, and dozens of enhanced and new SAS procedures. Running across major operating systems and environments, Altair SLC empowers users to execute SAS, Python, R, and SQL in one unified framework.

Altair SLC Hub delivers centralized orchestration, scheduling, and resource management for SLC clusters. The latest release introduces a command-line interface (HubCLI) and Windows credential integration, with upcoming support for single sign-on and high availability.

Altair Analytics Workbench builds on the integration between Altair SLC and SLC Hub, giving users a single, multi-language workspace to build, run, and deploy analytics. Now available on Windows, Linux, and macOS, the latest version adds a stand-alone SQL query block, a workflow import accelerator, and an AI-powered copilot for code generation, documentation, and data exploration. 

Smarter Data Preparation

The Altair Monarch release introduces support for writing Monarch expressions to filter data directly from ODBC sources like SQL Server, Oracle, MySQL, and DB2. Enhanced OData connector capabilities simplify data consumption from Mendix endpoints, while improved search and lineage functions make it easier to trace data origins and maintain transparency across the preparation process, the company shares.

Extending Monarch’s capabilities to the enterprise, Altair Monarch Server provides scalable report storage, process orchestration, and automation within a centralized, high-availability environment. The new release adds support for SQL Azure instance deployment, a unified job view combining logs from multiple workflows, and a consolidated interface for pre-mined table access. 

To learn more about Altair RapidMiner and explore the latest updates, visit altair.com/altair-rapidminer.

Sources: Press materials received from the company and additional information gleaned from the company’s website.