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Astera ReportMiner Demo (Version 11.1)

In this demo, you will see how Astera ReportMiner can ingest data from any source, extract it from any format, process it, and deliver it to your preferred destinations with complete end-to-end automation. This removes the need for manual effort, improves data accuracy, and gives you full control over your document processing workflows. From invoices and purchase orders to scanned PDFs and complex reports, ReportMiner helps you automate the entire document lifecycle. It handles everything from extraction and validation to integration, all within a unified and no-code platform.

Why Data Teams Are Best-Positioned For Agentic AI Success With Data Integration and MCPs

Building AI agents is the first step, and it’s positive to see enterprises exploring this avenue. But it’s only the first step. For true enterprise value, these agents must seamlessly connect to your data ecosystem through robust integration, standardized protocols, and be guided by knowledgeable data teams. The need to give AI agents access to data and connect them to the necessary tools and functions has led to the creation of the Model Context Protocol (MCP).

How I Built a Sales Agent Without Complex Coding Using Astera AI Agent Builder #aiagents

What if you could build your own sales agent without relying on complex coding or technical expertise? Sadiq Abbas, part of our Growth Team, did just that using Astera’s drag-and-drop visual builder. With Astera AI Agent Builder, we aim to empower businesses to create autonomous AI agents that automate workflows using their enterprise data. Whether it's for customer support, scheduling demo meetings or lead qualification, our simple drag-and-drop interface lets you design agents that fit your specific needs.

What Astera AI Agent Builder can do for you? #aiagents

Creating AI agents is now faster, easier, and more unified than ever. Jay Mishra, our Chief Product and Technology Officer, shares how the Astera AI Agent Builder empowers teams to design and deploy enterprise-grade agents using a fully visual, drag-and-drop interface. With built-in state management, seamless MCP integration and direct access to business systems, our agents are context-aware and capable of making real-time, data-driven decisions.

AI Agent vs. AI Assistant: Understanding The Differences

Thanks to artificial intelligence’s increasing influence in everyday life, many previously uncommon terms have become part of the zeitgeist, much like AI itself. Chances are, you’ve already come across the terms ‘AI agent’ and ‘AI assistant’. You might even have seen them being used interchangeably. While the two terms sound similar, what each of them represents is very different.

AI Agent Framework: What it is and How to Choose The Right One

Just like every impressive building starts with a strong foundation, every remarkable capability in an AI agent can be traced back to its framework. AI agent frameworks or agentic AI frameworks make it possible to create smart, efficient AI agents that can serve as simple chatbots, facilitate agentic automation, or contribute to complex use cases in finance, supply chain, healthcare, manufacturing, and robotics as part of a multi-agent system. But what are AI agent frameworks?

What AI Approach is Right for You: LLM Apps, Agents, or Copilots?

The generative AI hype train doesn’t appear to be slowing down, with organizational adoption rising from 33% in 2023 to 78% by the end of 2024. In fact, bigger companies are leading the way in GenAI adoption, with the global AI market projected to grow annually by 36.6% between 2024 and 2030. However, GenAI growth isn’t following a linear path. Organizations are utilizing different AI approaches, depending on their specific use cases.

Prompt Engineering Best Practices You Should Know

Look around yourself. We are swarming in the world of data and AI. From students at school using ChatGPT to complete their assignments to professionals using AI for market research, content creation, or even debugging code, everyone is leveraging the power of large language models (LLMs). Mr. Smith isn’t Googling his tax questions anymore; he’s asking an AI assistant.

How to Build an AI Agent: A Step-By-Step Guide

A recent study by PwC suggests that AI could contribute up to $15.7 trillion to the global economy by 2030, with automation playing a key role in boosting efficiency and innovation. AI agents are central to this transformation, streamlining workflows, handling repetitive tasks, and enabling data-driven decision-making. From virtual assistants in customer service to intelligent fraud detection in finance, these agents are reshaping industries and driving business growth.