RAG-based Tutoring Chatbot
Quiet signalA library in your pocket. A tutor by your side.
Launched 4d ago
Signal
18
Velocity
21
What this means
+151%Launching in a 151% WoW growing category.
GitHub had 236 launches this week vs 94 last.
16Founder Conviction Index: 16 — low signal.
Few of the conviction sub-signals (reputation, velocity, buyer-intent, tagline clarity) are firing yet.
Prediction
Top-5 finish probability
12%
today
Projected end-of-day votes
2range 2–3
Trajectory
stable
Not enough snapshots yet to detect trajectory.
Speed vs peers
0.7×
87 comparable launches
About
The RAG-based Tutoring Chatbot is made using Python, LangChain and FAISS. The system retrieves relevant context from a knowledge base before generating answers with Gemini Flash, grounding responses instead of relying on the model's raw knowledge.I evaluated it with the RAGAS framework, achieving ~0.87 faithfulness and ~0.83 answer relevancy, and deployed it live on Streamlit Community Cloud.I built this project from scratch with no prior coding experience, learning Git and GitHub along the way.
Attention & discussion velocity
Not enough snapshots yet. Run the snapshot worker every 15 min to build the time-series.
Performance
Pace needs two or more snapshots. This launch has 1, so velocity and momentum read as unmeasured rather than zero.
Velocity—
not measured
Momentum—
not measured
Virality—
not measured
Engagement—
not measured
Signal sources
1 of 6 active- Launch tracking1 reading since we picked it up
- AI analysisnot yet enriched
- Comment intelligencethread not yet analysed
- Outside discussionnot checked — domain is a storefront or shared
- Revenue signalsno match on this domain
- Editorial scoringbelow the signal threshold for this pass
A source that found nothing is a measurement. A source that has not run is a gap. Neither means the launch lacks the thing.