OpenRAILs AI | Creating a Chatbot Quickly, Securely & Easily скачать в хорошем качестве

OpenRAILs AI | Creating a Chatbot Quickly, Securely & Easily

In this video, Ron from Clarity walks step-by-step through how to create, configure, and test a brand-new chatbot inside the OpenRAILs AI platform. If you’ve been wondering how to move from “we should use AI” to actually deploying a secure, usable chatbot inside your organization, this is where it starts. We begin inside the Inference menu and navigate to the Chatbots dashboard—the command center for creating, managing, testing, and deploying AI chatbots across your organization. From there, it’s as simple as selecting “New Chatbot,” giving it a name, adding an optional description, and choosing your preferred large language model (LLM). Here’s where things get powerful. OpenRAILs ships with open-source LLMs pre-installed, meaning you can deploy AI without paying additional per-user licensing fees. More importantly, you maintain ownership and control of your data. In an era where data privacy, compliance, and AI governance are top-of-mind—especially for healthcare, finance, and regulated industries—this matters. Next, we enable a Data Lake. This isn’t just storage. The Data Lake acts as the chatbot’s secure knowledge foundation. It can store inquiries, responses, feedback loops, fine-tuning rules, documents, and structured data. Instead of a generic AI responding with public internet knowledge, your chatbot can be trained on your company’s specific policies, product catalogs, SOPs, compliance documentation, and more. Then we select the data source the chatbot will use to generate responses. This could include internal documentation, product data, support archives, financial records (with proper role-based access), or department-specific knowledge repositories. OpenRAILs uses secure ingestion and retrieval mechanisms so your chatbot answers questions based on your enterprise data—not random external content. From there, you can choose a pre-built template or fully customize the chatbot’s behavior. Templates accelerate deployment, while custom configurations allow for deeper control—tone, rules, escalation workflows, response formatting, guardrails, and more. Once created, testing is straightforward. Locate your newly named bot and click “Test.” The testing interface allows you to simulate real-world interactions, validate response accuracy, provide feedback, and refine outputs before full deployment. This step is critical. AI systems improve through iteration, and OpenRAILs makes that refinement process practical and manageable. If adjustments are needed, simply select “Edit” and modify the template settings, rules, data connections, or behavioral parameters. No rebuilding from scratch. No complicated redevelopment cycle. Just controlled iteration. Why does this matter for businesses? Because AI adoption often stalls at the proof-of-concept stage. Industry research shows that while over 70% of companies experiment with AI, far fewer successfully deploy it at scale. The difference typically comes down to governance, secure data architecture, and ease of operationalization. Platforms like OpenRAILs bridge that gap—turning AI from an experiment into an enterprise tool. With OpenRAILs, you’re not just spinning up a chatbot. You’re creating a secure AI asset built on your data, controlled by your policies, and aligned with your business goals. Whether you’re building: • A customer support assistant • An internal HR policy bot • A finance reporting assistant • A sales enablement chatbot • A healthcare-compliant AI tool • Or a company-wide productivity assistant The process is simple. Yet the impact is powerful. Create from a template or from scratch. Connect it to a secure Data Lake. Test. Refine. Deploy. That’s it. If your organization is exploring AI, agentic architecture, enterprise data lakes, secure LLM deployment, or AI governance frameworks, this walkthrough gives you a practical starting point. Thanks for watching—and if you’re ready to move beyond AI theory and into real implementation, OpenRAILs is built to help you do exactly that. Narrated: Ron Halversen Video: Ron Halversen DISCLAIMER: This video showcases solutions, web pages, etc. that may or may not have been designed or created by Clarity. All Products, Trademarks or Registered Trademarks are the copyrighted and owned property of their respective companies. Clarity Disclaimer Statement: https://www.clarity-ventures.com/disc.... Keywords: enterprise AI platform, chatbot creation process, OpenRAILs AI, secure data lake, LLM deployment, AI governance, agentic architecture, enterprise chatbot software Hashtags: #EnterpriseAI #ChatbotDevelopment #DataLakes #AIPlatform #AgenticAI #OpenRAILs