AI agents and MCP: Revolutionary Anthropic, the firm that created the Claude AI assistant, has an open-standard, open-source framework called the Model Context Protocol (MCP). It standardises how large language models (LLMs) and artificial intelligence (AI) interface with other tools and systems. The AI community is quite excited about MCP,
We’re thrilled to share several cutting-edge AI-powered features in Zoho Flow that will revolutionise how you create, improve, and manage your workflows. These features have been in the works for some time; rather than merely implementing AI, we focused on providing useful intelligence that makes your processes more efficient and
A company must be allowed to construct telephone infrastructure that can grow as its needs change. Even if local carrier usage is outside the scope of the solution, scalable telephony solutions should support it and meet your contact centre needs. To allow you to use your favourite carrier while still
AI governance is becoming the central bottleneck for deploying powerful AI systems safely at scale, especially for agentic systems like the ones you’re exploring. Here’s a clear, structured map of the field across ethics → risk → management → regulation → implementation. 1. What “AI Governance” Actually Means AI governance
Below is a technical blueprint and conceptual framing for building a human-level, deep research, agentic system using a Time-Test Diffusion Algorithm (TTDA)—treated as a reasoning-and-verification diffusion process across time, hypotheses, and evidence. 1. Problem Framing Goal: Create an agentic system that can: Conduct multi-week–level research in hours Generate, test, revise,
Orchestration matters because AI agents are no longer single models answering prompts—they are systems of models, tools, memory, workflows, and humans that must work together reliably. Without orchestration, AI agents quickly become brittle, expensive, unsafe, or impossible to scale. Below is a structured explanation of why orchestration matters, the common
Businesses today create more data than ever before, ranging from digital transactions and IoT sensors to consumer interactions and backend systems. However, without cognitive tools, this raw data stays underutilised, confined in data silos and unable to inform business choices. This is where artificial intelligence and data analytics come into
With their capacity for autonomous problem-solving, flexible workflows, and scalability, artificial intelligence (AI) agents are poised to revolutionise business processes. However, creating better models isn’t the true challenge. In addition to having access to tools and data, agents must be able to exchange information between systems and make their outputs
Get rid of the old and replace it with the new? Not precisely, though. As everyone knows, SEO is always changing, but Google has really turned us upside down. Once more, we must adjust—sink or swim, anyone? Marketers will now need to truly grasp AI-driven SEO tactics to stay ahead
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