Writing and content decision
Frase
A capable developer can build a narrow 'Answers' widget + indexed retrieval + draft generator and CMS publisher in about a week and modest monthly hosting/LLM costs, but reproducing Frase’s full loop (multi-engine AI visibility, Content Guard automation, enterprise polish and scale) is substantially larger and justifies staying on the paid product for teams needing that scope.
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. All Frase alternatives, with the arithmetic →
What a replacement has to do
- Capture visitor questions from a site, index site content, generate a cited answer/draft with an LLM, and publish or export the draft to a CMS while storing the question as a content signal.
What it still won’t have
- Multi-engine 'AI Visibility' monitoring across ChatGPT, Perplexity, Claude, Gemini, and Google AI
- Content Guard’s automated detect-draft-republish workflow and earned autonomy controls
- Industry-wide cohort insights and anonymized trending questions across other teams
- Enterprise features (white-label portals, SSO/SAML, SLA, dedicated account manager)
- Polished product UX, built-in team/workspace management, and turnkey hosting on FraseCMS
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 4 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 minimal Frase Answers replacement using Next.js for the frontend widget, Node.js + Express for the backend, PostgreSQL for storage, Elasticsearch (or vector DB like Milvus/Weaviate) for content indexing, and OpenAI (or compatible) LLM for generation. In scope: (1) a JS widget embeddable on any site that posts visitor questions to the backend, (2) a crawler that fetches and indexes the site's public pages and stores embeddings, (3) a retrieval+LLM pipeline that returns a cited short answer and a full article draft from retrieved passages, (4) a simple clustering mechanism to group repeated questions into content signals, (5) an integration to push drafts to WordPress via REST API, and (6) a basic scheduler that runs weekly SERP checks for a small list of tracked queries and creates alerts. Out of scope: multi-engine AI-citation tracking (ChatGPT/Perplexity/Claude/Gemini full integration), enterprise SSO/SAML, a white-label portal, and advanced agent autonomy (auto-publish based on learned trust). Include authentication for the CMS push, robust error handling, retries for network failures, and unit/integration tests for the crawler, indexer, LLM call wrapper, and CMS publisher.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 5 cited sources+3
- Price verified on pricing page+3
- Evidence score63
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 · 5
Every page the run actually retrieved.
- official productFrase homepage
- official pricingFrase pricing
- official productFrase Answers feature page
- open sourcestrapi/strapi
- open sourcepayloadcms/payload
Integrity checks
What held up, and what did not.
