Introduction
An overview of the Qolaba Chatbot — what it is, who it's for, and a summary of everything it can do.
Qolaba's Chatbot is a multi-model AI assistant built for professional and team-based workflows. It goes beyond standard chat by combining access to multiple large language models, executable tools, custom agents, and knowledge-aware responses — all within your organization's workspace structure
Who It's For
The Qolaba Chatbot is built for teams and individuals who need more than a basic AI chat interface:
Startups & Creators — Rapid content generation, product documentation, growth experimentation
Marketing Teams — Campaign ideation, ad copy, SEO drafts
Agencies — Multi-client workspace management with shared credit pools
Developers — Prompt engineering, model comparison, AI experimentation
Enterprises — Structured AI collaboration with governance and audit trails
Key Capabilities
Five capabilities make the Qolaba Chatbot distinct from a standard AI chat tool.
1. Multi-LLM Access
Most AI tools lock you into a single model. Qolaba gives you access to six leading large language models from one interface — GPT, Gemini, Claude, DeepSeek, Grok, and Sonar (Perplexity) — and lets you switch between them freely.
This means you can:
Run the same prompt across multiple models and compare outputs
Choose the best model for a specific task — creative writing, coding, research, summarization
Optimize credit usage by matching task complexity to the right model
Avoid being locked into one provider's strengths or limitations
Learn more about Model Selection →
2. Agents
Agents are purpose-built AI assistants that go beyond a one-off chat. Each agent has a defined role, behavioral instructions, tone, and knowledge base — so it responds consistently, stays on-topic, and understands your context without you re-explaining it every session.
Qolaba offers two types:
Pre-built agents — Ready-to-use assistants for common roles like Marketing Strategist, Content Creator, and more. Select one and start immediately with no setup required.
Custom agents — Build your own from scratch. Define the agent's name, role, model, expertise, and attach knowledge bases so it answers with your specific context in mind.
Agents are persistent, reusable across sessions, and can be shared within a workspace — making them especially valuable for teams with recurring workflows.
3. Toolkit
The Toolkit turns the Chatbot from a conversational tool into an execution environment. Instead of just generating text, it can actively perform tasks — searching the web, generating media, running code, analyzing files, and more.
Tools can run in Auto mode, where Qolaba automatically selects the right tool based on your prompt, or you can enable them manually for full control.
Toolkit includes tools for web search, media generation, code execution, file and URL analysis, and output safety — covering most tasks a professional workflow demands, without leaving the chat interface.
Learn more about the Toolkit →
4. Knowledge Base & Files
Uploading knowledge base and files lets you extend the chatbot's context with your own material — so it can answer questions, summarize content, and extract insights from documents that are specific to your work.
You can:
Upload files directly into a chat — supported formats include PDF, CSV, Excel, and plain text
Create knowledge bases — organized collections of files that any agent or chat session can reference persistently
This transforms the Chatbot from a generic assistant into a domain-aware one that understands your products, processes, and data.
Learn more about Knowledge Bases & Files →
5. Chat Branching
When a response isn't quite right, you don't need to start over or manually re-prompt. Chat Branching lets you regenerate any response using a different model at any point in a conversation — and compare outputs side-by-side across LLMs.
This is particularly useful for:
Testing how different models interpret the same prompt
Selecting the best response before using it in production
Iterating on complex outputs like code, copy, or structured data without losing conversation context
Learn more about Chat Branching →
Additional Features
The Chatbot also includes several supporting features covered in their own pages:
Model Settings — Fine-tune Temperature and Thinking Depth to control response style and reasoning
Chat Management — Pin, rename, share, and delete conversations from your history
Prompt Management — Save, edit, and reuse prompts across chats and agents
What's Next
Follow the recommended flow to get started:
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