Don't Query.
Quest
For Truth.
State a goal. A squad of specialized AI agents autonomously explores, cleans, analyzes, and visualizes your data. Your senior analyst in a box.
Foundational
Architecture
Three pillars that transform passive dashboards into an autonomous analytics engine. Connect anything. Ask naturally. Get alerted automatically.
Universal Data Connectors
Seeyon Quest fragments data silos by connecting to SQL, NoSQL, CSVs, and live APIs. The Scout agent scans schemas, identifies relevant tables, and maps relationships automatically.
Natural Language Interface
Context-aware prompts that reference previous queries. Ambiguity resolution built-in. Ask for 'Sales' and the system asks: 'Gross Revenue or Net Sales?'
Auto-Insight Engine
Even when not queried, background agents surface anomalies and trends. Real-time alerts for KPI drift. Your data talks before you ask.
Six Specialized
Agents
Quest Giver
The project manager. Parses user intent, decomposes it into sub-tasks, assigns the right agents, and compiles the final executive brief with supporting evidence.
The Scout
ConnectorData ingestion specialist. Scans schemas across PostgreSQL, Snowflake, Google Sheets, and APIs. Identifies relevant tables and maps metadata relationships.
The Alchemist
Data PrepDetects nulls, outliers, and formatting inconsistencies. Auto-generates Python/Pandas cleaning scripts. Fixes mismatched SKUs, date formats, and encoding issues.
The Oracle
AnalystStatistical powerhouse. Runs regressions, clustering, trend analysis, and anomaly detection. Builds forecasting models and surfaces correlations humans miss.
The Bard
VisualizerSelects the optimal chart type based on data shape — heatmaps, bar charts, scatter plots. Generates interactive React/D3 components with drill-down capability.
The Guardian
SecurityGovernance layer. PII masking via regex, query cost estimation before execution, SQL injection prevention. Read-only by default. DELETE requires human approval.
From Intent
To Insight
No SQL. No dashboards. Just state your goal and let the agent guild handle the rest — from data wrangling to executive briefing.
Initiation
User states a high-level goal in natural language: 'Optimize our inventory for the upcoming holiday season.' The Quest Giver parses intent and generates a multi-step plan.
Planning
The Quest Giver breaks the goal into ordered sub-tasks: 1. Analyze historical holiday sales. 2. Check current stock levels. 3. Forecast demand. Agents are assigned.
Execution
Agents work in parallel. The Scout queries Snowflake and Shopify. The Oracle runs a forecasting model. The Alchemist fixes mismatched SKUs. The Guardian masks customer emails.
Delivery
The Bard renders an interactive dashboard with drill-down support. The Quest Giver compiles a narrative executive brief with supporting evidence and confidence scores.
API-First
Platform
RESTful endpoints via FastAPI. Webhooks for async delivery. A plugin ecosystem where developers write custom Python agents that inherit from BaseAgent.
// Initiate a new Quest
const response = await fetch("/api/quests", {
method: "POST",
body: JSON.stringify({
goal: "Find out why churn increased in Q3",
connectors: ["postgres_crm", "shopify_api"],
options: {
pii_masking: true,
max_query_cost: "$0.50",
output_format: "dashboard + brief"
}
})
});
const { quest_id, status } = await response.json();
// status: "planning" → agents being assignedProject-Based
Workspace Agents
Organize and analyze your data using AI-powered agents that work directly within your project environment. Dedicated workspaces for every initiative.
Create Projects
Organize your work into separate projects for different teams, departments, or analysis initiatives.
AI Agent Sessions
Launch dedicated AI agent sessions within each project to perform data analysis tasks autonomously.
Real-Time Collaboration
Watch as the AI agent reads files, creates scripts, processes data, and generates insights in real time.
How It Works
Benefits
Keep different analyses and datasets isolated in their own projects
Agents handle repetitive data processing tasks automatically
All file operations stay within the project environment
Intelligent Workspace
File Management
Projects now have built-in file system capabilities with Paperboy integration. The AI agent manages your project files intelligently — from upload to analysis to export.
Upload Files
Add CSV, Excel, JSON, text, and other data files to your project workspace.
Browse File Tree
Explore the complete structure of files in your project with a visual file explorer.
AI-Powered Operations
The agent reads, creates, and edits files with precise changes for advanced analysis workflows.
Download Results
Export analysis results, generated reports, and processed data files with full format support.
AI Agent Tools
Sophisticated file operations with full reasoning display to track agent logic.
| Tool | Mode | Description |
|---|---|---|
| Write Tool | Create | Create new files with AI understanding of data structures and formats |
| Edit Tool | Modify | Make precise modifications to existing files without data loss |
| Read Tool | Analyze | Analyze file contents intelligently with context-aware parsing |
| Skill Tool | Execute | Execute specialized analysis skills like statistical modeling and visualization |
Supported Files
CSV, JSON, Excel
Python, SQL, JS
PNG, JPG, PDF
Real-World
Applications
From sales analysis to data cleaning to multi-source integration — see how workspace agents transform your data workflows.
Sales Data Analysis
Upload monthly CSV files to a Q1 2026 project and let the AI agent analyze trends, create visualizations, and generate actionable insights.
Data Cleaning & Transformation
Upload raw data files and use an agent to identify quality issues, create cleaning scripts, and transform data into analysis-ready formats.
Multi-Source Integration
Combine data from multiple systems. Upload files from different sources and let the agent merge, normalize, and prepare standardized datasets.
Getting
Started
Quick tips to help you make the most of your workspace agents from day one.
Create a project with just a few data files to explore the capabilities
The more specific your analysis request, the better results you'll get
Watch the agent's file operations to understand what it's doing
Export analysis results and generated files for use in other tools
Try both read-only and editable modes to suit your needs
Traditional BI vs. Seeyon Quest
Why an autonomous agent squad fundamentally changes the analytics equation — from passive dashboards to proactive intelligence.
| Feature | Traditional | Seeyon Quest |
|---|---|---|
| Query Construction | Manual SQL / drag-and-drop builder | Natural language intent → auto-generated queries |
| Data Cleaning | Manual scripts, ad-hoc notebooks | Alchemist agent auto-detects & fixes issues |
| Insight Discovery | Passive dashboards — shows what happened | Active agents explain why + suggest what to do |
| Security | Depends on team discipline | Guardian agent: PII masking, cost limits, audit trail |
| Time to Insight | Hours to days (analyst bottleneck) | Seconds to minutes (autonomous agents) |
Tech Stack
Start Your
First
Quest.
Join the waitlist for early access. Be among the first to deploy autonomous agent squads on your data. No SQL required.