Research project
Grant Lab Automation — AI Workflow Platform
An internal AI workflow platform with a visual builder for composing repeatable multi-step automations. It supports multiple model providers, real-time execution tracking, file processing, and administrative controls in one system.
- My role
- Lead Developer
- Duration
- 1 month
- Discipline
- Research project
- Year
- 2025
01 / The problem
Researchers needed a way to compose repeatable AI-assisted workflows without rebuilding prompts, file handling, execution tracking, and provider integrations each time.
02 / The work
Built the full-stack platform: workflow designer, provider abstraction layer, WebSocket execution tracking, file processing, admin tooling, and deployment.
03 / The outcome
Turned experimental AI-assisted tasks into a controllable internal platform instead of a scattered collection of one-off scripts.
This is an internal workflow system. The case study focuses on platform design, provider abstraction, and execution control rather than private workflow definitions.
At a glance
- Visual workflow designer for multi-step AI runs
- Supports Claude, OpenAI, and Gemini behind a unified execution layer
- WebSocket execution tracking, file handling, admin controls, and audit logging
Project Overview
A full-stack AI workflow orchestration platform built to automate research tasks at the Grant Lab. Provides a visual interface for designing multi-step AI workflows, executing them in real-time, and managing results — all with enterprise-grade authentication and audit logging.
Project Details
Technologies Used
- Next.js 14 (frontend with Tailwind CSS)
- FastAPI (Python backend)
- PostgreSQL 15 (database)
- Zustand (state management)
- WebSocket (real-time execution updates)
- JWT + bcrypt (authentication)
- Docker Compose (deployment)
Key Features
- Visual Workflow Designer: Drag-and-drop interface for composing multi-step AI workflows
- Multi-AI Provider Support: Integrates Claude (Anthropic), OpenAI, and Google Gemini
- Real-Time Execution: WebSocket-based live progress tracking during workflow runs
- File Processing: Upload and process files through AI-powered pipelines
- Admin Panel: User management, API key configuration, system settings, and audit logs
- Security: JWT authentication with bcrypt password hashing
Technical Highlights
- Full-Stack Architecture: Decoupled Next.js frontend and FastAPI backend communicating via REST + WebSocket
- Multi-Provider Abstraction: Unified interface across Claude, OpenAI, and Gemini APIs
- Production-Ready: Dockerised deployment with PostgreSQL persistence and environment-based configuration