AI assistants and search decision
IdeaFast
A competent developer can implement a useful, smaller replacement (data ingestion, clustering, quote evidence, and LLM idea generation) in ~30 hours; nothing on the site claims an unreproducible moat.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Fetch recent posts from a subreddit, extract and cluster recurring complaints, score clusters by frequency/signal, surface representative quotes as evidence, and run an LLM prompt to generate startup ideas from top pain clusters.
What it still won’t have
- Polish UX and interactive demo
- Built-in 'Broad mode' auto-find subreddits
- Tiered validation reports (basic vs full validation)
- Usage-management, billing, and subscriptions UI
- Scale-tested scraping and rate-limit handling
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 9 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a lightweight IdeaFast replacement using Node.js (Express) + React, Postgres for data, and a vector index (pgvector). Core features in scope: 1) fetch posts/comments from Reddit API for a chosen subreddit and time window and store them; 2) compute embeddings (OpenAI or other) and cluster recurring complaints; 3) score clusters by frequency and recency and pick representative quotes with original permalinks; 4) call an LLM to generate 2–5 ideas per top cluster; 5) present results in a simple UI and provide CSV/JSON export. Out of scope: multi-tenant billing, advanced validation reports, broad-mode auto-find, historical trend analytics. Include error handling for API rate limits, retries, and expired tokens, and include unit tests for data ingestion, clustering, and the idea-generation pipeline.
How we checked
How the score was reached
- Build verdict base78
- An open-source build was found+5
- 3 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score93
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productIdeaFast homepage — product and pricing
- open sourceqdrant/qdrant
- open sourcedzhng/deep-research
Integrity checks
What held up, and what did not.
