Anaconda, Tanium, Dell and Precisely Push Enterprise AI Toward Agent Coordination and Control

Anaconda expanded beyond Python software distribution with tools for AI agent swarms, security testing and production deployment. The release draws on three acquisitions: AI coding company Kilo Code Inc., security specialist Enkrypt AI Inc. and orchestration provider Outerbounds, the business name of Step Computing Inc. Chief Executive David DeSanto said, “We are moving Anaconda from being known as a Python package company into being known as an AI-native development platform, essentially helping people build their own enterprise AI applications.” The company’s swarm technology lets a task agent delegate parts of a project to subagents that work simultaneously, exchange information and select different models for different jobs. Anaconda provides a secure message board for agent communication and user observation. It is bringing swarms into Microsoft Corp.’s Visual Studio Code through technology acquired with Kilo. The new Kilo Desktop combines software development, data science and Python environment management, offers access to more than 500 models, supports local model execution and includes automatic model routing. Anaconda said its research found that 63% of respondents are moving toward swarms in some form, and some customers have deployed hundreds of agents. Security capabilities from Enkrypt include autonomous red-teaming agents that challenge models, agents and Model Context Protocol connections across more than 300 attack categories. Runtime controls can approve, modify or block risky behavior, and Anaconda provisions agents with least privilege. The platform also has a public Agent Incident Registry. Anaconda cited Enkrypt research finding vulnerabilities in 73% of agent tools examined across more than 25,000 MCP servers, including potential data leakage and other exposures.

Tanium expanded its Security Operations portfolio with detection, response and threat-hunting tools built on its Tanium Atlas agentic AI platform. The company describes the goal as a self-driving security operations center in which software agents work through investigation and response inside limits set by human operators. Tanium says live queries straight to the endpoint avoid the lag of data pulled earlier into security information and event management platforms, where information can already be hours old. The company pointed to Verizon Communications Inc.’s “Data Breach Investigations Report” this year, which ranked exploited vulnerabilities ahead of stolen credentials as the most common entry point for the first time in its 19-year history. New features include Endpoint Drift, which compares a device’s current behavior with its historical baseline, and the Insights Engine for advanced in-memory techniques. On response, actions run directly on the endpoint, and a new Federated SOC architecture lets separate teams work independently on one platform. Atlas adds Alert Prioritization and Triage, which sorts incoming alerts and attaches a recommended next step. Google LLC’s Google Threat Intelligence is now built into Tanium’s investigation and hunting workflows, and reputation data from five unnamed providers is meant to reduce false positives. Harman Kaur, chief technology officer at Tanium, said security teams “don’t need another tool that generates more alerts.” Kaur added, “The customer sets the rules and autonomy runs the workflow.” Tanium is also folding Atlas into Tanium HuntIQ, its expert-led threat-hunting service launched last November. All Security Operations additions are available now.

Dell expanded its AI Data Platform with a semantic layer and knowledge graph intended to give AI agents trusted context from company data, and it is speeding up data processing on Nvidia Corp. graphics chips. The Unified Semantic Layer gives applications the same business definitions and rules, including ontologies a company already maintains. The Enterprise Knowledge Graph tracks how data connects, so an agent can pull related tables and vector indexes it is allowed to see. Knowledge Agents are built on the graph, each covering a single topic and working only from assigned data. Customers decide what data an agent can see and how much it can spend. Nvidia’s Nemotron Retriever models handle reasoning and visual understanding, and the components run inside the customer’s own data center. Arthur Lewis, president of Dell’s Infrastructure Solutions Group, said an agent that can find a customer record but does not know what it means or whether it can be trusted “isn’t intelligent.” “It’s just fast,” he said. Dell’s Data Processing Engine will run on GPUs using Nvidia’s cuDF library. Dell’s September tests on a PowerEdge R770 server with Nvidia RTX PRO 4500 Blackwell Server Edition GPUs found Apache Spark jobs ran 3.9 times faster on average than on central processing units alone, with a 20.4-times speedup on a batch data mining job using default settings and no tuning. PowerScale storage will support up to 500 tenants in a single cluster, with granular role-based access control and encryption and authentication of file traffic over the Network File System protocol using mutual Transport Layer Security. The Unified Semantic Layer, Enterprise Knowledge Graph and Knowledge Agents are due in the first half of 2027. PowerScale’s multitenancy and security updates arrive in November, the accelerated Data Processing Engine follows in December, and more Apache Arrow acceleration is expected in the first half of next year.

Precisely introduced the Precisely Platform, a unified system designed to make enterprise data ready for artificial intelligence, and Precisely AI Studio, a library of ready-made AI agents and apps for developers. Precisely pitches the platform as an answer to the patchwork of point solutions enterprises use for data in cloud lakehouses as well as older mainframe and SAP systems. On the platform, data is managed where it lives rather than migrated first. Every tool, including master data management, draws on one metadata and semantic layer, so a rule or policy defined once applies across all of them. AI built into the platform handles work such as writing data quality rules and matching records. Every data asset can carry quality and governance scores. Matt Waxman, chief product officer at Precisely, said, “Agents don’t stop to question the data they’re given.” He added, “They act on it at scale, far faster than people can catch and correct errors.” Precisely calls location intelligence and built-in data enrichment distinctive capabilities, with enrichment data pre-linked to location and business attributes for more than 250 countries and territories. New Model Context Protocol servers open the platform and some existing Precisely products to assistants such as Claude, Microsoft Copilot and ChatGPT. AI Studio assets work with all three assistants, and Precisely says users can start prototyping within minutes. The Precisely Platform is in preview and is due for general availability in early 2027. AI Studio is available now with a free trial for new users. Precisely, known as Syncsort until 2020, will discuss both launches at a virtual event Thursday.

Editor's Summary Anaconda, Tanium, Dell and Precisely used the same day to push enterprise AI deeper into agent coordination, endpoint security, data context and data readiness. Their tools place controls around autonomous agents and aim to shorten the path from pilot projects to production.