Knowledge Bots B2B Guide (EN)
  • Overview
    • 🤖Welcome to Blockbrain!
    • 🗓️Book a Demo
    • 📝Working with Knowledgebots
    • 📚Glossary
  • Use Cases
    • 👩‍💻Company GPT
    • ⏳Sales Automation
    • 🧩Employee Support
    • 🧐Hotline Helper
    • 📘Risk & Compliance Management
    • 📠Machinery
    • 📂Tender Analysis
    • 💡More Use Cases
  • FOR USERS
    • 👨‍💻Account Setup
    • ✍️Prompt Guide for Better Answers from AI
    • 🚀How to use Knowledge Bots
      • Chat with Knowledge Bots
      • Manage your Databases in Knowledge Management
      • Use Insights Efficiently
    • 🧰Guide on Advanced Knowledge Bot Features
      • Maximize Agent Use
      • Maximize Workflow Use
      • Maximize Intent Agent Use
      • Maximize Insight Use
      • Maximize Contribute Knowledge Use
    • ⛏️Pick your LLM
    • 🔫Troubleshooting
  • FOR BUILDERS
    • ⚒️How to build a Knowledgebot
    • 🖋️Prompting for Agents and Workflows
    • Build and Apply Advanced Features
      • More on Knowledgebot Settings & Management
      • Create an Agent
      • Set Up Workflows
      • Prepare Intent Agent
      • Use Insights
      • Optimize Contributed Knowledge
    • 🔏Manage Access
    • 🔫Troubleshooting
  • FOR ADMINS
    • 👨‍🦱Manage your Domain
    • 🔵Integrations
    • 🥽Google SSO
    • 🕸️Web Component
    • 🤵‍♂️Legal & Compliance
    • 🚑Admin Support
  • MOBILE APP
    • 📱Save Knowledgebots as an App
    • ⬇️Download Blockbrain App
    • How it works
    • Mobile Use Cases
  • NEWS
    • 📈Features & Updates
    • ⏲️Coming soon
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On this page
  • What is an AI Chatbot?
  • How does an AI Chatbot work?
  • From AI Chatbot to Knowledgebot
  1. Overview

Working with Knowledgebots

What is an AI Chatbot?

An AI chatbot is a program that uses artificial intelligence (AI) to conduct human-like conversations. It can answer questions, perform tasks, and provide information. These chatbots leverage natural language processing (NLP) to understand and respond to user inputs in a coherent and contextually appropriate manner. They are commonly used in customer service, virtual assistants, and various online platforms to enhance user interaction and automate routine tasks.

How does an AI Chatbot work?

1. Input

The user enters a question or instruction (prompt).

2. Processing

  • The chatbot analyzes and understands the input.

  • The chatbot identifies the intent of the input.

  • The chatbot extracts relevant entities from the input.

3. Response Generation

Based on the recognized intent and extracted entities, the chatbot generates an appropriate response or performs an action.

4. Output

The chatbot returns the response to the user.

From AI Chatbot to Knowledgebot

Our Knowledge Bots are based on conventional AI chatbots. However, they can respond much more effectively through linked knowledge. By understanding context and selected information, answers become more personalized, smarter, avoid hallucinations, and are more tailored. Custom-created databases (multimodal) and insights (knowledge extractions, notes, or messages resulting from AI processing of your company's data) can be linked to transform an AI chatbot into a Knowledge Bot.

  • Integrate your own Data: Utilize powerful Large Language Models (LLMs) linked to your specific data to receive tailored and contextual responses. In a Knowledgebot, your information can be either connected via:

    • Databases (long-term memory) consisting of uploaded documents, imported websites, previously generated Bot-Insights

    • Files (short-term memory) ingested directly into the chatroom

    • Email

  • Web search: Gain access to current information from the web to constantly expand and update your knowledge base.

  • Dynamic knowledge development: Feed the output back into your databases to continuously generate and integrate new knowledge.

  • Agents: Deploy specialized agents to automate recurring tasks and efficiently design complex assignments. These agents can be linked to various data sources to extract and process relevant information.

  • Workflows: In a workflow designed as a sequence of agents, each agent performs a specific task in a predefined order, with its output serving as the input for the next agent. This setup ensures a streamlined process where tasks are completed efficiently and dependencies are managed effectively.

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Last updated 27 days ago

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