The following first appeared on IronSpark Analysis’s Chief Analyst Salvatore Salamone’s Substack newsletter, ABR Intelligence Report. Get insights on the latest advances in Artificial, Business, and Real-time Intelligence in your inbox. Sign up now
Welcome to the ABR Intelligence Report, which explores advances in Artificial, Business, and Real-time Intelligence, and how they are converging to shape the next generation of digital enterprises. Each edition will unpack key developments, innovations, and ideas driving these interconnected domains, along with expert commentary on what they mean for data leaders, architects, and technologists.
We’re launching the ABR Intelligence Report at a critical time in the industry. Up to now, there has been a great focus on each of the three areas as stand-alone technologies. Increasingly, however, organizations find they can realize significant synergies by combining two or more of these three forms of intelligence. Examples include using an AI agent to analyze business intelligence reports to spot trends and actionable items, or incorporating real-time insights into an AI model.
Enabling this melding is the fact that the three forms of intelligence share a common foundation. They all require secure, timely access to data wherever it resides or is generated, distributed compute resources to process and act on that data, and data architectures that enable streaming, sharing, and synchronization across massive, dynamic datasets.
ABR Intelligence News Analysis
AI Needs Real-time Data
One indication of the interdependency of the various types of intelligence could be found at this week’s Current conference, the annual event for the data streaming community. The conference is hosted by Confluent, which has been known for years for Apache Kafka and for creating a platform for data-in-motion that enables real-time data streaming.
This year’s conference theme is “where real-time data and AI come together.” To that end, Confluent used the conference to introduce Confluent Intelligence, a solution that provides everything organizations need to launch and scale event-driven AI systems.
MCP Support Grows
The industry continues to embrace the Model Context Protocol (MCP), which supports the development of AI agents capable of performing complex tasks by interacting with multiple data sources and tools in real time. This month alone, Amplitude, Apollo GraphQL, BigID, Graphwise, Lenses.io, and Snowflake announced MCP servers.
Given Snowflake’s prominent role in supporting analytics, AI, and data engineering applications, its new managed MCP server is particularly interesting. The server helps organizations to easily and securely harness their own proprietary data and third-party data in Snowflake from partners including FactSet, MSCI, Nasdaq eVestment, and The Associated Press. Organizations will then be able to leverage the server to connect their data to apps and agent platforms such as Anthropic, CrewAI, Cursor, Devin by Cognition, Salesforce’s Agentforce, UiPath, and Windsurf to build context-rich AI agents and apps.
Other vendors such as Nasuni, OutSystems, and Zapier announced solutions that include support for MCP.