Today, multi-agent systems (MAS) have emerged as transformative technologies, driving innovation and efficiency across various industries. Comprising multiple autonomous agents working collaboratively ...

The industry hype says "more agents is all you need," but new data shows that strictly sequential tasks and tool-heavy ...

Varun is a Product management and AI leader, shaping the future of tech with strategic vision, AI platforms and agentic-AI experiences. Three weeks ago, I witnessed AI agents solving a complex ...

The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...

What if you could design a system where multiple specialized agents work together seamlessly, each tackling a specific task with precision and efficiency? This isn’t just a futuristic vision—it’s the ...

How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...

Enterprises are likely to shift from single-task AI to multi-agent systems, enabling autonomous, adaptive operations, but trust and orchestration remain problematic.

In mission-critical environments—think disaster response, financial systems, or supply chain logistics—success hinges on the seamless collaboration of multiple agents, whether they’re humans, machines ...

There is a lot of enterprise data trapped in PDF documents. To be sure, gen AI tools have been able to ingest and analyze PDFs, but accuracy, time and cost have been less than ideal. New technology ...