Bryter Launches 'Beamon AI' – Legal Agent Suite

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In Today’s Report:

🕒 Estimated Reading Time: 5 minutes 35 seconds

📌 Top News:

• ServiceNow and NVIDIA expand their partnership, launching a new class of intelligent AI agents called Apriel Nemotron 15B, and introducing the AI Control Tower for centralized governance.

⚡️Trending AI Reports:

• Bryter, a legal automation company, unveils 'Beamon AI,' a suite of AI agents tailored for legal professionals, focusing on actionable AI integrated with workflow automation.

• kama.ai launches Trustworthy Hybrid AI Agents, combining deterministic and generative AI to provide reliable and accurate information for enterprises.

• Thunderbit introduces its vertical AI web data extraction agent, built specifically for business users to easily extract structured data from the web for various applications.

💻 Top Tutorials:

• Building Enterprise AI Agents with ServiceNow and NVIDIA: Learn how the expanded partnership aims to create intelligent agents for various business workflows.

• Automating Legal Tasks with Bryter's Beamon AI: Discover the capabilities of AI agents designed to assist legal professionals with drafting, reviewing, and managing legal documents.

• Leveraging Thunderbit for Automated Web Data Extraction: A step-by-step guide on using Thunderbit's AI agent to efficiently gather and structure data from websites for business intelligence.

🛠️ How-to:

• Build Multi-Agent AI Systems with CrewAI

📰 BREAKING NEWS

ServiceNow and NVIDIA Expand Partnership, Launch New AI Agent

Overview

ServiceNow and NVIDIA have announced a significant expansion of their collaboration, marked by the debut of Apriel Nemotron 15B, a new high-performance AI reasoning model, and the AI Control Tower for unified AI agent management within the ServiceNow platform.

Key Features:

• Apriel Nemotron 15B: A jointly developed AI model designed for evaluating relationships, applying rules, and making informed decisions across enterprise workflows.

• AI Control Tower: A centralized command center within ServiceNow for governing, managing, securing, and optimizing AI agents and workflows.

• AI Agent Fabric: A new solution to facilitate enhanced communication and collaboration between AI agents and multi-model systems.

• Partner Integrations: Major partners are set to offer integrations with ServiceNow's AI Agent Fabric for seamless third-party agent workflows.

• Focus on Autonomous Enterprise: The expanded partnership aims to empower enterprises with self-defending AI capabilities and real-time integrated operations.

⚡️TRENDING AI REPORTS

Bryter Launches 'Beamon AI' – Legal Agent Suite

Overview: Bryter, a legal tech company, has introduced 'Beamon AI,' a comprehensive suite of AI agents designed to empower legal professionals with intelligent automation for various tasks.

Key Features:

• Assist: A chat-based AI assistant to support legal professionals with information retrieval and guidance.

• Draft: A Microsoft Word add-in for AI-powered legal drafting, including redlining and document comparison.

• Review: An AI agent focused on efficient and accurate review of legal documents.

• Actionable AI: Bryter emphasizes integrating AI agents directly into legal workflows to automate end-to-end processes.

• Intelligent Task Selection: Beamon AI can select the most suitable AI agent and Large Language Model for specific legal tasks, optimizing performance.

kama.ai Launches Trustworthy Hybrid AI Agents

Overview: kama.ai has released its Hybrid AI Agents, powered by GenAI's Sober Second Mind®, which combines the reliability of knowledge graph AI with the real-time responsiveness of generative AI for enterprise applications.

Key Points:

• Hybrid Architecture: Blends deterministic and generative AI for enhanced accuracy and context.

• Enterprise Focus: Designed to serve enterprises with minimal risk and maximum brand control.

• Human-AI Collaboration: Incorporates feedback loops for continuous improvement based on expert review.

• Integration Ready: Offers APIs for integration with various enterprise systems.

• Emphasis on Trust: Aims to provide trustworthy AI agents for critical customer-facing solutions.

Thunderbit Launches Vertical AI Web Data Extraction Agent

Overview: Thunderbit, a new AI platform, has launched a vertical AI agent specifically for business users to extract structured data from the web with ease and precision.

Key Points:

• Vertical Focus: Optimized for web data extraction for sales, marketing, e-commerce, and research.

• Natural Language Extraction: Users can describe desired data in plain English.

• 2-Click Scraping: Simplifies data extraction from web pages, including documents and images.

• Subpage Navigation: Automatically explores and aggregates data from multiple pages.

• Real-Time Structuring: Instantly formats extracted data for direct use and export to various workspaces.

💻 TOP TUTORIALS

1. Building Enterprise AI Agents with ServiceNow and NVIDIA

Explore the potential of the expanded ServiceNow and NVIDIA partnership to create intelligent AI agents for streamlining enterprise workflows across various departments. Learn about the new Apriel Nemotron 15B model and the AI Control Tower's capabilities in managing a fleet of AI agents.

2. Automating Legal Tasks with Bryter's Beamon AI

Discover how legal professionals can leverage the Beamon AI suite to automate key tasks such as document drafting, review, and analysis. Understand the different agents within the suite and how they integrate into existing legal workflows to enhance productivity.

3. Leveraging Thunderbit for Automated Web Data Extraction

Learn how to use the Thunderbit Chrome Extension to automate the extraction of structured data from websites. Follow a step-by-step guide on defining the data you need in natural language and using the 2-click scraping feature to gather and format information for your business needs.

🎥 HOW TO

Build Multi-Agent AI Systems with CrewAI

Overview: This tutorial guides you through building AI agents using the CrewAI framework, which simplifies the creation of multi-agent systems where AI agents collaborate to achieve complex goals. It's designed for beginners and covers the fundamental concepts and practical implementation of CrewAI.

Steps:

1. Introduction to CrewAI:

   • Understand the core concepts of CrewAI and its advantages for building collaborative AI workflows.

   • Learn how CrewAI facilitates the definition of agent roles, tasks, and communication.

2. Project Setup:

   • Set up your development environment with Python and install the CrewAI library. “pip install crewai“

   • Configure any necessary API keys or access credentials for the LLMs you intend to use.

3. Define Agents:

   • Learn how to create individual AI agents within CrewAI, specifying their:

     • Roles (e.g., "Researcher," "Writer," "Developer").

     • Goals and objectives.

     • Backstory and context.

     • LLM (Large Language Model) to use.

     • Tools they have access to.

4. Define Tasks:

   • Learn how to define the specific tasks that each agent will perform, including:

     • Task descriptions and instructions.

     • Expected outputs.

     • Agent assignment.

5. Orchestrate a Crew:

   • Learn how to create a "Crew" in CrewAI to manage the interaction and workflow between agents.

   • Define the sequence of tasks and how agents will collaborate to achieve the overall goal.

   • Explore CrewAI's features for:

     • Task delegation.

     • Information sharing between agents.

     • Workflow management.

6. Implement Tools:

   • Learn how to integrate tools into your AI agents, enabling them to:

     • Access external information (e.g., web search).

     • Perform specific actions (e.g., code execution).

     • Interact with APIs.

7. Test and Iterate:

   • Thoroughly test your CrewAI system to ensure it functions as expected.

   • Analyze the agent interactions and refine their roles, tasks, and workflows to optimize performance.

8. Advanced Concepts:

   • Explore more advanced CrewAI features, such as:

     • Memory management.

     • Agent communication protocols.

     • Error handling.

     • Parallel task execution.

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Jahanzaib