Aggregate ratings stay hidden until real approved review data is intentionally published.
Customer Stories & Feedback
This page is designed for real buyer feedback only. CheapAI does not publish invented names, invented review text, or public rating claims that cannot be supported by actual approved reviews.
Only approved customer feedback appears on this page.
Filters are already prepared for Cursor, Claude Code, Open WebUI, LangChain, pricing, delivery, setup, reliability, refunds, and more.
Verified purchase badges are shown only when there is real proof behind the feedback.
Search and filter feedback
Search titles, body text, tools, use cases, model families, and tagged topics. The interface is designed to stay calm and readable even when this page grows to 50+ real reviews.
Featured customer stories
Longer, higher-signal buyer stories can sit here once real approved feedback starts to accumulate.
Published feedback
Review cards are built for star ratings, titles, body text, tool tags, model families, source metadata, optional verified-purchase proof, and future pagination at scale.
No approved public reviews yet
The structure is live, but CheapAI is not filling it with fake ratings. Once real feedback is approved, it will appear here with the same search, filtering, and moderation rules shown above.
- Star ratings stay unpublished until there is real approved review data.
- Verified purchase badges appear only when there is real order-backed proof.
- Public review content comes from
data/reviews.json.
What people use CheapAI for
These are the main feedback clusters the page is already prepared to organize cleanly.
IDE coding workflows
Tag future reviews from developers using CheapAI inside Cursor, coding copilots, and day-to-day editor workflows.
Terminal and agent tooling
Separate experiences for Claude Code, repo-level terminal agents, and developer CLI sessions that care about long context and response quality.
Internal chat interfaces
Useful for teams wiring CheapAI into self-hosted chat interfaces, internal assistants, or multi-model workspaces.
SDKs, automation, and pipelines
For SDK integrations, chains, orchestration layers, eval flows, and automation stacks that want a cheaper OpenAI-compatible endpoint.
Trust links beyond star ratings
If you want harder proof than a review feed, these pages are a better starting point.
How real reviews should be added later
The public page reads from data/reviews.json. Add real reviews there, keep moderation_status honest, and do not enable a public aggregate rating until the data actually supports one.
- Add a new item in
data/reviews.jsonwith realrating,title,body,date,tool,model_family,source, andmoderation_status. - Set
verified_purchasetotrueonly when there is real purchase proof behind the feedback. - Use
featuredonly for approved long-form stories worth highlighting at the top of the page. - Leave public aggregate claims off until there are enough approved reviews to publish them truthfully.