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Observability Platform for Messaging, Event Processing, and Streaming Across Hybrid Cloud (MESH).

Observability Platform for Messaging, Event Processing, and Streaming Across Hybrid Cloud (MESH).

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Agentiq Sports announced a funding of $4 million to launch a revolutionary investment platform that connects fans with their favorite athletes.

Observability Platform for Messaging, Event Processing, and Streaming Across Hybrid Cloud (MESH).

Observability Platform for Messaging, Event Processing, and Streaming Across Hybrid Cloud (MESH).

BigID on September 21, 2026 announced the launch of AgentIQ, an agentic automation interface that lets customers operate their data security and compliance programs from a prompt or an AI agent, either inside BigID or directly from Claude, Copilot, GPT, or Gemini. What AgentIQ Does The release describes AgentIQ as a fully agentic automation interface to BigID. Customers can write custom prompts or use pre-built BigID agents to retrieve, report, respond, or remediate data and AI security and compliance violations, and BigID says running a query requires neither a new interface nor a security analyst. Custom enterprise agents and internal AI platforms are supported surfaces alongside BigID itself. BigID groups the product’s functions under a set of operating labels. Ask handles questions about the data and AI landscape, spanning cloud, SaaS, on-premises systems, databases, and files, with custom reporting returned. Investigate works data and access violations to determine who and what was impacted. Consult and Reason lets customers work with their model of choice on regulatory compliance, security frameworks, and industry best practices. Assess Risk ranks findings by sensitivity, exposure, activity, and business context. Act executes the response: revoking access, remediating exposure, applying retention, quarantining, enforcing policy, and fulfilling requests...

BigID has unveiled AgentIQ, an automated interface that improves data security and compliance. This innovation enables seamless operations from platforms like Claude and Copilot, empowering users to oversee data autonomously.

As enterprises look to adopt agents and agentic AI to boost the efficiency of their applications, Nvidia this week introduced a new open-source software library — AgentIQ toolkit — to help developers connect disparate agents and agent frameworks. The toolkit, according to the chipmaker, packs in a variety of tools, including ones to weave in RAG, search, and conversational UI into agentic AI applications. “It’s essentially a connectivity layer for AI agents. It lets you connect, profile, and optimize teams of AI agents that were built using different frameworks including our own platform,” said Paul Chada, co-founder of agentic AI-based software-providing startup DoozerAI. While Nvidia’s intention with the toolkit is to help enterprises break down silos between different agent systems, According to Chada, several similar systems can offer similar capabilities. These include LangChain, CrewAI, and Microsoft’s Semantic Kernel. The Nvidia toolkit also includes a configuration builder that allows developers to prototype new Agentic AI applications and a set of reusable tools, pipelines, and agentic workflows to ease the development of agentic AI systems. In addition, the toolkit comes with telemetry, profiling, and optimizing tools to enhance the accuracy and performance of the agentic systems being built, the chipmaker said, adding that developers can use Dynamo to accelerate agent performance further. ## How does it help developers and enterprises? AgentIQ, according to analysts and experts, is business friendly as it is open source and doesn’t require modifications to be shared back with the community. For developers, Chada said that AgentIQ will act as a time-saver allowing easier orchestration between different agent frameworks. For enterprises, the toolkit kit will provide enterprises visibility into their AI operations helping identify bottlenecks and reduce response times dramatically. The Futurum Group’s lead of CIO practice said that AgentIQ’s granular telemetry data is highly valuable for enterprises looking to fine-tune AI performance and cost-efficiency in real time, especially with agents that interface with the real world. According to IDC’s research vice president Arnal Dayaratna, AgentIQ will also allow enterprises to build custom agents that reflect the specificities of their own organization’s business processes and workflows instead of having to configure commercial, off-the-shelf agents that are being offered by some vendors. AgentIQ could also help enterprises avoid vendor lock-in by creating interoperability between different AI agent platforms. “Rather than forcing businesses to choose one ecosystem and stick with it, Nvidia’s approach lets them use multiple frameworks side-by-side. They can pick the best tools for specific tasks while still having everything work together seamlessly,” Chada said. ## Considerations before adoption Enterprises may need to consider a few things before looking to adopt AgentIQ. “AgentIQ’s development framework approach requires coding and the adoption of a new design framework, which creates a significant barrier for many potential users or enterprises,” Chada said. Some enterprises might find vendors who offer the ability to create AI agents without coding more attractive as a no-code approach democratizes agent creation, allowing business users and subject matter experts to build functional AI agents through intuitive interfaces rather than requiring developer resources, Chada said.

Today, we’re excited to announce our collaboration with NVIDIA. In Azure AI Foundry, we’ve integrated NVIDIA NIM microservices and the NVIDIA AgentIQ toolkit into Azure AI Foundry—unlocking unprecedented efficiency, performance, and cost optimization for your AI projects. Read more on the announcement here. Optimizing performance with NVIDIA AgentIQ and Semantic Kernel Once your NVIDIA NIM […]

The toolkit is designed to help developers save time by acting as a connective tissue between agent frameworks.