AI-Powered Assistant
Your Intelligent Partner for Business Operations
The Kaman AI Assistant transforms how your team works by understanding natural language requests, accessing your organization's knowledge, and executing complex tasks across multiple systems - all while maintaining complete transparency and control through visible thinking and reasoning.
What Can the AI Assistant Do?
Key Capabilities
Natural Language Understanding
Communicate with Kaman the way you'd talk to a colleague. No need to learn special commands or syntax - simply describe what you need in plain language.
Examples:
- "Show me all customer complaints from last month and identify common themes"
- "Generate a summary report of our Q3 sales performance with charts"
- "Find all documents related to the Johnson account and create a timeline"
- "Analyze this CSV and suggest data quality improvements"
Sub-Agent Delegation
For complex tasks, the AI Assistant can spawn specialized sub-agents that handle specific aspects of the work:
Sub-Agent Types:
| Agent Type | Specialization |
|---|---|
| Data Analyst | Complex queries, statistical analysis, visualizations |
| Code Generator | Scripts, applications, automation code |
| Researcher | Document search, web research, knowledge synthesis |
| Workflow Executor | Multi-step process automation |
Transparent Thinking
See exactly how the AI reasons through your requests with visible thinking indicators:
What You See:
- Thinking bubbles showing the AI's reasoning process
- Tool progress indicators for each action being taken
- Step-by-step explanations of what's happening
- Confidence levels for conclusions and recommendations
Multi-Model Support & System Model Configuration
Choose the right AI model for your needs:
| Model | Best For |
|---|---|
| GPT-4 | Complex reasoning, analysis |
| Claude | Long documents, nuanced tasks |
| Gemini | Multimodal content |
| Groq | Fast inference, real-time tasks |
| Custom Models | Specialized domain tasks |
System Model Configuration: Administrators can assign specific models for different agent purposes:
| Purpose | Description |
|---|---|
| Think | Model used for reasoning and planning steps |
| Summarize | Model used for final response generation |
| Research | Model used for deep research and analysis |
Models can be configured globally or per-organization, with automatic fallback chains if the primary model is unavailable. Manage system models from the Super Admin > System Models dashboard.
Rich Artifact Generation
Generate sophisticated outputs directly from conversation:
Artifact Types:
- Charts & Visualizations - Interactive charts from your data
- HTML Applications - Functional web applications
- Reports & Documents - Formatted business documents
- Code & Scripts - Ready-to-use automation scripts
- Data Tables - Structured data outputs
Context-Aware Responses
The AI Assistant maintains awareness of:
- Your conversation history
- Your role within the organization
- Department-specific vocabulary
- Previous interactions and preferences
- Relevant organizational knowledge
How It Works
Understanding Your Request
- Parse - The assistant analyzes your request to understand intent
- Contextualize - It considers your role, permissions, and conversation history
- Plan - It determines the steps needed, potentially involving sub-agents
- Verify - For sensitive operations, it confirms before proceeding
Executing Tasks
Transparency at Every Step
Every action taken by the AI Assistant is:
- Visible - Watch thinking and reasoning in real-time
- Logged - Complete audit trail of all operations
- Explainable - Clear reasoning for decisions and actions
- Controllable - Stop or modify operations at any point
- Reviewable - Full history available for compliance and analysis
Skill System
The AI Assistant learns and improves through automatic skill extraction:
How Skills Work
Skill Lifecycle:
- Extraction - Successful interaction patterns are identified
- Validation - Skills are tested and refined
- Evolution - Skills improve with usage feedback
- Sharing - Proven skills become available organization-wide
Skill Sources
| Source | Description |
|---|---|
| Auto-Extracted | Skills discovered from user interactions |
| GitHub Import | Import curated skills from Anthropic, OpenAI, and Superpowers repositories |
| Custom | Organization-created skills with supporting files |
| System Sync | Automatically synced daily from curated repositories |
Skills can include supporting files (scripts, schemas, templates) beyond the core skill definition, enabling complex multi-file capabilities.
Skill Categories
| Category | Examples |
|---|---|
| Data Analysis | Report generation, trend analysis |
| Communication | Email drafting, meeting summaries |
| Process | Approval workflows, data validation |
| Domain | Industry-specific tasks |
Control & Safety Features
Approval Workflows
Configure which operations require human approval before execution:
- Sensitive data access
- External communications
- Financial transactions
- System modifications
- Sub-agent spawning (optional)
Permission Boundaries
The assistant operates within your defined security boundaries:
- Only accesses data the user is authorized to see
- Cannot exceed the user's permission level
- Respects data classification and sensitivity labels
- Sub-agents inherit parent agent permissions
Audit Trail
Complete visibility into assistant activities:
- What was requested
- What thinking/reasoning occurred
- Which sub-agents were used
- What actions were taken
- What data was accessed
- When and by whom
Use Cases
Executive Support
- Prepare briefing materials with charts and insights
- Summarize lengthy documents
- Track action items and commitments
- Generate status reports automatically
Team Collaboration
- Answer common questions instantly
- Share institutional knowledge
- Coordinate cross-team activities
- Document decisions and rationale
Data Analysis
- Query and visualize data conversationally
- Identify trends and anomalies
- Generate automated reports
- Create interactive dashboards
Operations Management
- Process status inquiries
- Exception handling with intelligent suggestions
- Performance reporting
- Resource coordination
Agent Test Panel
Test your agents live while building them, without needing to save first:
How It Works:
- Open the agent builder and configure your agent (tools, prompts, data sources)
- Click the test panel on the right sidebar
- The panel shows a readiness checklist of required fields
- Chat with your agent using the current form state - no saving required
- Iterate on your configuration and test again instantly
Getting Started
1. Start with Chat
Open the AI Assistant and ask a question naturally:
- "What can you help me with?"
- "Show me my recent data"
- "Help me analyze this file"
2. Explore Capabilities
Ask the assistant to explain what it can do:
- "What tools do you have access to?"
- "Can you generate charts?"
- "How do I create a report?"
3. Try Complex Tasks
Once comfortable, try multi-step requests:
- "Analyze last month's sales, identify top performers, and create a presentation"
- "Find all open support tickets, categorize them, and suggest priorities"
4. Review and Refine
The assistant learns from your feedback:
- Provide corrections when needed
- Confirm successful patterns
- Report issues for improvement
Benefits Summary
| Benefit | Description |
|---|---|
| Time Savings | Eliminate manual data gathering and report generation |
| Consistency | Same quality responses regardless of who's asking |
| Transparency | See thinking, reasoning, and all actions taken |
| Accessibility | Make organizational knowledge available to everyone |
| Scalability | Sub-agents handle complex tasks without bottlenecks |
| Control | You decide what the AI can and cannot do |
The AI Assistant - Intelligent help with human oversight