๐ง IntelliHQ โ Your AI-Powered Team Command Center
๐ Inspiration
Startups and fast-paced teams live in tools like Slack, but crucial updates, blockers, and decisions get buried in endless threads. We wanted to build a one-click, AI-powered HQ that summarizes team knowledge and surfaces what matters most โ without making anyone dig for it.
๐ก What it does
IntelliHQ connects to your Slack workspace, ingests recent messages, and uses GPT-4 to generate concise summaries. It identifies key decisions, blockers, and questions, giving your team a clear snapshot of what's happening โ all from a clean web UI.
๐ ๏ธ How we built it
We divided the 12-hour build into focused tracks:
- Slack Ingestion: Used Slack Web API to fetch messages and store them locally in JSON.
- Backend: Built with Node.js to expose
/get_summaryand/ask_questionendpoints. - LLM Integration: Crafted custom prompts and connected to OpenAIโs GPT-4 API to process Slack threads.
- Frontend: Developed a simple React interface to input tokens, trigger summarization, and display results.
- Polish: Added error handling and light styling with TailwindCSS to prepare for demo day.
๐งฑ Challenges we ran into
- Slack API rate limits and workspace permissions delayed testing.
- Prompt engineering was tricky โ we had to iterate to get meaningful summaries.
- React-Flask integration required some debugging due to CORS and token handling.
๐ Accomplishments that we're proud of
- Built a working MVP in under 12 hours.
- Successfully connected Slack โ Node.js โ GPT-4 โ React pipeline.
- Got accurate summaries of real Slack threads โ with GPT identifying blockers we missed!
- Designed a usable UI that non-devs could operate.
๐ What we learned
- Prompt design is as important as code when working with LLMs.
- Real-world APIs (like Slack) bring non-obvious edge cases.
- Clear separation of concerns across frontend, backend, and AI layers helped us iterate fast.
๐ฎ What's next for IntelliHQ
- Support GitHub and Notion ingestion alongside Slack.
- Add automatic daily digests and email/Slack notifications.
- Fine-tune GPT prompts based on feedback.
- Make the product open-source for teams to self-host.
- Train a custom summarization model on company-specific context.
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