Apps & APIs
Pegasus AI Analytics Copilot & SQL-Safe Query Assistant
AI-guided analytics workspace that helps users ask operational questions, routes requests through controlled tools, and returns structured answers through a SQL-safe decision layer.
Copilot decision flow
Pegasus AI Analytics Copilot
Question input, prompt routing, SQL-safe tools, structured response
Guided
Query mode
Curated
Tool layer
Structured
Response format
Mock
Test mode
Question categories
Routed workflow
Question
Router
Tool
Safe SQL
Answer
| Input | Route | Output | Mode |
|---|---|---|---|
| Show slow-moving inventory | Inventory tool | Table + summary | Safe |
| What changed this month? | Trend tool | Cards + chart | Safe |
| Explain reorder alerts | Alert tool | Summary | Safe |
Response outputs
Business problem
Business users needed faster answers to operational questions, but direct SQL access was not the right solution. Raw database querying creates risk, inconsistency, and dependency on technical users for every follow-up question.
The challenge was to create a safer analytics experience that could translate business questions into structured actions, return usable answers, and support operational workflows without turning the reporting layer into an uncontrolled query environment.
System built
Built an AI-assisted analytics copilot with a FastAPI backend, a React frontend, and a curated SQL-safe tool layer. The system accepts natural-language questions, routes prompts through controlled tool logic, executes approved analytics actions, and returns structured outputs such as summaries, tables, cards, and debug detail.
Instead of exposing unrestricted querying, the copilot guides the user through a governed analytics path that is more usable for business teams and safer for operational systems.
Routing signals
Signals reviewed
The assistant works best when it can recognize question type, route requests correctly, and pull from the right governed tool path.
Copilot flow
How it works
Ask
The user enters an operational or analytical question in natural language.
The frontend gives users a guided workspace for asking questions without needing to know SQL, schemas, joins, or backend details.
Route
The system interprets the request and determines which tool, workflow, or analytics path should handle it.
Prompt routing helps separate inventory questions, trend questions, KPI questions, detail lookups, and other domain-specific analytics paths.
Execute Safely
Approved backend logic runs through curated SQL-safe tools instead of unrestricted direct querying.
The backend protects the data layer by using controlled functions and approved tool pathways rather than ad hoc database access.
Structure
Results are organized into usable outputs such as cards, tables, summaries, or diagnostic detail.
The response layer turns backend output into business-friendly views that can be scanned, reviewed, exported, or debugged.
Respond
The frontend returns a guided answer that is easier for business users to act on and easier for developers to troubleshoot.
The final answer balances usability and transparency by supporting summaries, structured data, and debugging context.
System coordination
What the system coordinates
Prompt routing
Routes incoming questions to the most appropriate analytics path, tool, or domain flow.
Tool registry
Defines the approved functions, utilities, and SQL-safe actions the copilot is allowed to use.
Execution layer
Handles backend processing, structured query actions, and controlled analytics responses.
Response layer
Formats outputs into readable summaries, cards, tables, and debugging views for the user.
Impact signals
What the copilot enabled
SQL-safe tool registry
Domain-specific analytics prompts
Structured answers instead of raw query output
FastAPI backend for orchestration
React interface for operator usability
Mock mode for local testing and iteration
Use cases
Use cases supported
Operational analytics Q&A
Supports business questions that need fast answers from structured operational data.
Guided reporting requests
Helps users request analytics without needing to know where every report, table, or calculation lives.
Domain-specific prompts
Routes questions through purpose-built paths instead of forcing every request into one generic chat flow.
Developer-friendly testing
Mock mode and debug views make it easier to validate behavior locally before wiring into production data.
Structured answer delivery
Returns summaries, tables, cards, and detail views instead of unstructured text-only answers.
Safer SQL alternatives
Creates a governed option for analytics exploration without exposing unrestricted query access.
Why this system matters
A safer path between business questions and data answers.
Pegasus AI Analytics Copilot is designed to bridge the gap between business curiosity and technical control. It gives users a guided interface for asking operational questions, while the backend enforces structure, tool governance, and SQL-safe execution.
The result is an analytics experience that feels more modern for users and more responsible for the systems behind it.
Confidentiality note
Visuals and descriptions are sanitized conceptual representations. They do not expose private company data, customer records, credentials, raw exports, internal pricing, operational screenshots, or proprietary source files.