> ## Documentation Index
> Fetch the complete documentation index at: https://docs.envole.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Multi-Assistant Collaboration
> Bring together expertise from multiple assistants with simple @-mentions
Sometimes one assistant isn't enough. When you're tackling complex challenges that require diverse expertise—like launching a product that needs both technical and marketing insights, or solving a customer issue that spans support and sales—Envole lets you bring the right specialists together in one seamless conversation.
The magic of multi-assistant collaboration is its simplicity: just @-mention the assistants you need, and Envole coordinates everything behind the scenes to deliver comprehensive, well-rounded responses.
## Why Collaborate with Multiple Assistants?
**Get Diverse Perspectives**: Different assistants bring specialized knowledge and unique viewpoints to your challenges, ensuring you don't miss important considerations.
**Save Time**: Instead of having separate conversations with different assistants and manually combining their insights, get everything you need in one comprehensive response.
**Improve Quality**: Multiple perspectives often lead to better solutions, catching potential issues or opportunities that a single viewpoint might miss.
**Ensure Completeness**: Complex projects benefit from cross-functional input—collaboration ensures all aspects are covered.
## How Multi-Assistant Collaboration Works
### Step 1: Discover Available Assistants
When you're in any conversation, simply type the @ symbol to see all the assistants available in your organization.
**What you'll see:**
* Your Team Personal Assistant (always available)
* Sub-Assistants created by your team
* Published assistants from other teams
* Specialized assistants for different functions (sales, marketing, engineering, etc.)
Each assistant has a clear name that indicates their specialization, making it easy to choose the right expertise for your request.
### Step 2: Mention Multiple Assistants Naturally
Write your request in natural language and @-mention the assistants whose expertise you need. There's no special syntax to remember—just communicate as you normally would.
**Example scenarios:**
* "@sales-assistant @marketing-assistant help me create a go-to-market strategy for our new feature"
* "@engineering-assistant @product-assistant review this technical specification and suggest improvements"
* "@support-assistant @billing-assistant help resolve this customer's payment and service issue"
### Step 3: Automatic Coordination
Once Envole detects multiple assistant mentions, it automatically initiates the collaboration process. The system:
* Ensures all assistants understand the full context
* Coordinates their responses to complement each other
* Manages the conversation flow
* Presents a unified, comprehensive response
You don't need to manage anything—just wait for the collaborative response.
### Step 4: Receive Comprehensive Insights
The result is a response that combines specialized expertise from all mentioned assistants. You'll see:
* **Clear attribution**: Which assistant contributed which insights
* **Complementary perspectives**: How different viewpoints address your request
* **Unified recommendations**: Coordinated advice that works together
* **Follow-up coordination**: Your primary assistant often synthesizes everything into actionable next steps
## Real-World Collaboration Examples
### Product Launch Planning
**Request**: "@product-assistant @marketing-assistant @sales-assistant help me plan the launch for our new analytics dashboard"
**Result**:
* Product assistant provides technical specifications and feature highlights
* Marketing assistant suggests positioning, messaging, and campaign strategies
* Sales assistant offers pricing insights, competitive analysis, and sales enablement needs
* Unified response with coordinated timeline and responsibilities
### Customer Issue Resolution
**Request**: "@support-assistant @engineering-assistant this customer is experiencing slow query performance"
**Result**:
* Support assistant provides customer context, impact assessment, and communication templates
* Engineering assistant analyzes technical logs, identifies root causes, and suggests fixes
* Coordinated response with both immediate customer communication and technical resolution
### Content Creation
**Request**: "@content-assistant @brand-assistant create a blog post about our security features"
**Result**:
* Content assistant provides structure, SEO optimization, and writing best practices
* Brand assistant ensures tone, messaging, and visual guidelines alignment
* Unified draft that meets both content quality and brand standards
## When to Use Multi-Assistant Collaboration
**Cross-Functional Projects**: When your task requires input from multiple departments or specializations.
**Complex Problem-Solving**: When challenges need diverse types of expertise to solve effectively.
**Comprehensive Planning**: When creating strategies, documents, or plans that benefit from multiple perspectives.
**Risk Assessment**: When you want different viewpoints to identify potential issues or opportunities.
**Learning and Exploration**: When entering unfamiliar territory and needing to understand various aspects of a topic.
## Best Practices for Effective Collaboration
### Be Specific About Your Needs
Instead of vague requests, provide context about what you're trying to achieve:
* ❌ "Help me with this project"
* ✅ "Help me create a customer onboarding process that reduces support tickets while improving user satisfaction"
### Choose the Right Mix of Assistants
Think strategically about what types of expertise your request requires:
* **For product decisions**: Product + Engineering + Design
* **For customer issues**: Support + Sales + Product
* **For content creation**: Content + Brand + Marketing
* **For process improvement**: Operations + relevant functional teams
### Provide Relevant Context
The more context you share, the better assistants can tailor their collaborative response:
* Share relevant documents, links, or background information
* Mention constraints, deadlines, or specific requirements
* Explain the broader goal, not just the immediate task
### Ask Follow-Up Questions
If the collaborative response raises new questions or you need deeper insight:
* Continue the conversation naturally
* Mention additional assistants if new expertise is needed
* Ask for clarification on specific aspects
## Collaboration vs. Individual Assistance
**Use individual assistants when:**
* You need focused expertise in one area
* The task is straightforward and doesn't require multiple perspectives
* You're iterating on work within a single domain
**Use multi-assistant collaboration when:**
* Your challenge spans multiple disciplines
* You need comprehensive coverage of a complex topic
* You want to validate ideas across different functional areas
* You're planning something that affects multiple teams
## What's Next?
Now that you understand how to leverage multiple assistants working together, you're ready to explore another powerful feature: understanding how Human-in-the-Loop approval works when assistants need your input before taking actions.
Understand how Envole ensures you stay in control when assistants take actions
## Ready to Try Multi-Assistant Collaboration?
Try @-mentions with your team's assistants
Explore advanced collaboration features