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Key Concepts & Platform Basics

Welcome to B-Bot Hub - a platform for creating, training, and deploying specialized AI experts. This guide covers the fundamental concepts you need to understand to get the most out of the platform.

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Core Architecture

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The Three-Layer Model

B-Bot Hub operates on a simple but powerful three-layer architecture: 
Layer 1: EXPERTS
    ↓
Layer 2: DISTRIBUTION CHANNELS
    ↓
Layer 3: END USERS
1

Experts (Layer 1)

Your AI AgentsExperts are specialized AI agents you create with:
  • Unique personality and identity
  • Custom training and knowledge
  • Specific capabilities and tools
  • Configured modalities (voice, image, etc.)
Think of experts as your AI employees - each with their own role, expertise, and way of working.
2

Distribution Channels (Layer 2)

Deployment MethodsHow your experts reach users:
  • B-Bot Chat: Internal chat interface
  • Embed Widget: Website chat widgets
  • API: Custom integrations
  • Tasks: Scheduled automation
  • Templates: Public marketplace sharing
One expert can be deployed through multiple channels simultaneously.
3

End Users (Layer 3)

Your AudienceWho interacts with your experts:
  • Customers
  • Team members
  • Website visitors
  • API consumers
  • Automated systems

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Key Features

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1. Expert Creation & Management

8-Step Creation Process

  1. Basic Information
  2. Profile Picture (AI-generated option!)
  3. Abilities & Behaviors
  4. Quick-Start Templates
  5. Models & Modalities
  6. App Connections
  7. Team Configuration
  8. Review & Deploy

Expert Configuration

Each expert includes:
  • Name, profession, description
  • System prompt (personality)
  • Abilities (behavior modes)
  • Templates (quick prompts)
  • Model selection
  • Tools & apps
  • Voice settings

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2. Fine-Tuning & Training

Transform generic models into specialists:
Collect training data naturally:
  1. Chat with your expert
  2. When you get a perfect response, mark it
  3. Build up 50-500+ examples
  4. Expert learns from these interactions
Benefits:
  • No manual data creation
  • Real-world examples
  • Continuous improvement
  • Natural workflow
Learn more: Fine-Tuning | Model Distillation

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3. Provider Keys Management

Unified API key management:
Manage keys for language models:
  • OpenAI (GPT-4, GPT-3.5)
  • Anthropic (Claude 3)
  • Google (Gemini)
  • Mistral, DeepSeek, Cohere
  • Groq, Azure, Ollama
  • And 10+ more
Benefits:
  • One place for all keys
  • Primary & fallback keys
  • Key validation
  • Usage tracking
Text-to-speech and speech-to-text:
  • OpenAI TTS & Whisper
  • ElevenLabs
  • Google TTS
  • Azure Speech
  • Browser native
Flexibility:
  • Different keys for voice vs text
  • Multiple accounts
  • Separate billing
Image generation services:
  • OpenAI DALL-E
  • Stability AI
  • Midjourney
  • BFL FLUX (profile pictures)
Uses:
  • Expert profile pictures
  • Content generation
  • Visual assets
Learn more: Provider Keys

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4. Multimodal Capabilities

Beyond text interactions:

Voice Input

Speech-to-Text:
  • Real-time voice recording
  • Multiple languages
  • Hands-free operation
  • Mobile-friendly
Powered by:
  • OpenAI Whisper
  • Google Speech-to-Text
  • Azure Speech
  • Browser native

Voice Output

Text-to-Speech:
  • Natural-sounding voices
  • Multiple voice options
  • Streaming audio
  • Auto-play settings
Powered by:
  • OpenAI TTS (6 voices)
  • ElevenLabs (100+ voices)
  • Google TTS (WaveNet)
  • Azure Neural Voices

Image Processing

Visual AI:
  • AI-generated profile pics
  • Image analysis
  • Screenshot understanding
  • Diagram explanations
Capabilities:
  • OCR (text extraction)
  • Object recognition
  • Visual Q&A
  • Image generation

File Handling

Document Processing:
  • PDF, Word, Excel
  • Code files
  • CSV data analysis
  • JSON/XML parsing
Operations:
  • Read and analyze
  • Extract information
  • Generate summaries
  • Answer questions
Learn more: Modalities | Multimodal AI

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5. DeepAgents Workspace

Advanced autonomous capabilities:
Hierarchical todos:
Main Goal
├─ Subtask 1
│  ├─ Step 1.1
│  └─ Step 1.2
└─ Subtask 2
   └─ Step 2.1
Features:
  • Automatic task breakdown
  • Status tracking (pending, in_progress, completed)
  • Progress monitoring
  • Priority management
Use for:
  • Multi-step projects
  • Complex workflows
  • Autonomous execution
Learn more: DeepAgents Workspace | DeepAgents Concepts

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6. Distribution Channels

Deploy your experts everywhere:
Internal chat application:
  • Direct integration
  • Full feature access
  • User management
  • Team collaboration
  • Real-time conversations
Best for:
  • Internal teams
  • Secure environments
  • Full-featured usage
  • Power users
Learn more: Distribution Channels

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7. App Integrations

Connect to external services:

Google Workspace

  • Gmail
  • Drive
  • Calendar
  • Sheets
  • Docs

Communication

  • Slack
  • Discord
  • Microsoft Teams
  • WhatsApp (coming soon)

Development

  • GitHub
  • GitLab
  • Bitbucket
  • Jira
  • Linear

Productivity

  • Notion
  • Trello
  • Asana
  • Monday.com
  • Airtable

CRM & Sales

  • Salesforce
  • HubSpot
  • Pipedrive
  • Zendesk

Data & Analytics

  • Databases
  • APIs
  • Webhooks
  • Analytics tools
Each expert can:
  • Use different apps
  • Have unique credentials
  • Connect multiple services
  • Automate workflows
Learn more: Apps & Integrations

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Common Workflows

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Workflow 1: Customer Support Expert

1. Create Expert
   ├─ Name: "Support Assistant"
   ├─ Profession: "Customer Support Specialist"
   └─ Abilities: Handle inquiries, troubleshoot, escalate

2. Fine-Tune
   ├─ Mark 200 perfect support conversations
   └─ Train custom model

3. Connect Apps
   ├─ Zendesk (ticket system)
   ├─ Knowledge base
   └─ CRM

4. Deploy via Embed
   └─ Add chat widget to website

5. Monitor & Improve
   ├─ Track satisfaction
   ├─ Mark new good examples
   └─ Retrain monthly

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Workflow 2: Data Analysis Expert

1. Create Expert
   ├─ Name: "Data Analyst AI"
   ├─ Enable DeepAgents mode
   └─ Configure file handling

2. Connect Apps
   ├─ Database connections
   ├─ Google Sheets
   └─ Visualization tools

3. Deploy via Tasks
   ├─ Schedule: Daily at 8 AM
   ├─ Input: Latest data
   └─ Output: Analysis report

4. Use Workspace
   ├─ Generate analysis files
   ├─ Create visualizations
   └─ Write summary reports

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Workflow 3: Content Creation Expert

1. Create Expert
   ├─ Fine-tune on brand voice
   └─ Connect to content tools

2. Use Model Distillation
   ├─ Generate examples with GPT-4
   ├─ Train GPT-3.5
   └─ 93% cost reduction

3. Deploy via API
   └─ Integrate with CMS

4. Multi-Channel
   ├─ Social media posts
   ├─ Blog drafts
   └─ Email campaigns

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Getting Started Checklist

1

Set Up Provider Keys

Add API keys for the services you’ll use
  • OpenAI, Anthropic, or others
  • Voice providers (optional)
  • Image providers (optional)
→ Provider Keys Setup
2

Create Your First Expert

Follow the 8-step creation wizard
  • Define personality
  • Choose model
  • Configure capabilities
→ Create Expert Guide
3

Test in Chat

Have conversations to refine behavior
  • Test different scenarios
  • Mark good responses (QA marking)
  • Adjust abilities as needed
→ Chat Features
4

Optional: Fine-Tune

Train on your specific use case
  • Collect 50-500 examples
  • Train custom model
  • Deploy fine-tuned version
→ Training Guide
5

Deploy via Distribution Channel

Make your expert available to users
  • Choose channel (Chat, Embed, API, Tasks)
  • Configure settings
  • Launch!
→ Distribution Channels
6

Monitor & Improve

Continuous improvement cycle
  • Collect user feedback
  • Mark new examples
  • Retrain periodically
  • Update configuration

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Next Steps

Create Your Expert

Start building your first AI expert

Fine-Tuning

Learn about training custom models

DeepAgents

Understand autonomous capabilities

Distribution

Deploy your expert everywhere