bhupathiraju-likhitha/growthpilot-ai — explained in plain English
Analysis updated 2026-05-18
Chat with a locally running AI model about business growth questions.
Store and recall business context across conversations using the Hindsight memory service.
View a dashboard and timeline of business information through the FastAPI backend.
Run the whole stack locally on Windows for private, offline-friendly experimentation.
| bhupathiraju-likhitha/growthpilot-ai | 0xhassaan/nn-from-scratch | 3ks/embedoc | |
|---|---|---|---|
| Stars | 0 | 0 | — |
| Language | Python | Python | Python |
| Last pushed | — | — | 2023-06-08 |
| Maintenance | — | — | Dormant |
| Setup difficulty | moderate | moderate | hard |
| Complexity | 3/5 | 4/5 | 1/5 |
| Audience | pm founder | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Ollama running locally with a downloaded model, plus separate backend and frontend dependency installs and a Hindsight API key.
GrowthPilot AI is a full stack application meant to help startup founders think through business growth questions with help from AI, while keeping track of context about their business over time. It combines a FastAPI backend written in Python, a React frontend built with Vite, a locally running AI model through a tool called Ollama, and a separate service called Hindsight that stores memories of past business context and conversation insights so answers can be grounded in what has already been discussed. The backend exposes endpoints for handling business information, a dashboard, chat conversations, and a timeline. The frontend is described as a modern, animated interface using a glassmorphism visual style, meaning translucent, frosted-glass looking panels. To run the project, a person needs Python 3.10 or newer, Node.js 18 or newer, and Ollama installed locally with a working model such as llama3 downloaded ahead of time. The backend reads its configuration, including the Ollama connection details and the Hindsight API key and settings, from an environment file. The README's setup instructions are written specifically for Windows Command Prompt, walking through creating a Python virtual environment, installing backend dependencies, installing frontend dependencies with npm, and then starting the backend and frontend in separate terminal windows. Once both are running, the frontend is available at a local address on port 5173 and the backend API on port 8000. The README also mentions a backend smoke test script for a quick check that things are working, and a command to build the frontend for production. It notes that if the local Ollama model is not responding, the person should confirm it is running and that the model has been downloaded, and that if the Hindsight memory service is unreachable, the app is designed to keep working locally through a fallback behavior built into the backend, though the README does not describe exactly what that fallback does.
A local AI-powered business growth assistant combining a FastAPI backend, a React frontend, a local Ollama model, and memory storage via Hindsight.
Mainly Python. The stack also includes Python, FastAPI, React.
No license information is provided in the README.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly pm founder.
This repo across BitVibe Labs
Verify against the repo before relying on details.