AI Agent for Electrical Project Estimation

An established electrical company in the Seattle area needed a better way to manage project requests, customer input, documents, and estimation workflows. The goal of this project is to create an AI-powered internal platform that helps the team move from scattered project details to structured estimates faster and more consistently.

The core of the platform is an AI agent built with LangChain and LangGraph, with a model-agnostic architecture that can work with different LLM providers depending on business needs. The agent is designed to collect user input, understand project requirements, ask follow-up questions when needed, and generate an initial estimate that can be reviewed and adjusted by the team.

The platform also manages project documents and connects them to the estimation process. This allows the company to keep customer details, uploaded files, project requirements, and generated estimates in one centralized place instead of relying on disconnected tools or manual tracking.

A key part of the system is storing estimation history for future processes. Previous estimates and project details can be reused for planning, proposal preparation, internal review, and future workflow automation.

The infrastructure is being designed to support secure document handling, reliable AI processing, and future expansion into broader internal automation, including customer communication, proposal generation, and project management support.