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Enterprise Toolkit for Building Domain-Specific AI Agents

Added Jun 2025 3 design docs

Enterprises want AI agents tailored to their own workflows in finance, healthcare, and beyond, but few have the specialist expertise to build each agent from scratch. This project builds the platform that closes the gap, letting organizations assemble, deploy, and manage custom agents without starting over each time.

The intern implements the agent runtime with CrewAI and Langchain, using OpenAI models for reasoning and task execution, and builds a FastAPI backend that manages agent definitions, deployments, and execution. An agent library provides reusable, domain-specific templates that users can customize for their industry's tasks, while user profiles keep each organization's agents, configurations, and history separate. A Streamlit interface, with everything written in Python, makes building and operating agents accessible to technical and semi-technical users alike.

The project teaches platform thinking applied to AI, including designing abstractions for agents in general rather than one hardcoded workflow, managing multi-tenant state, and exposing complex orchestration through a clean API and UI. Completing it demonstrates the intern can engineer the infrastructure layer of the emerging agent economy.

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