AI assistants and search decision
Google AI Pro
A competent developer can build a useful assistant plus storage and simple Drive/Gmail integrations, but cannot replicate Google’s proprietary Gemini models, first‑party Google app integrations, or bundled ecosystem perks — so building replaces only part of the paid product.
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
- Provide a chat/assistant UI that accepts user prompts, sends them to a hosted LLM API, and returns results combined with user files stored in cloud storage.
What it still won’t have
- Access to Google’s proprietary Gemini Pro/Flash models
- Deep, built-in integrations across Google apps with first-party privileges
- YouTube Premium Lite and Google Home/Health bundled perks
- High usage limits and scale-backed features (expanded token/context windows, agentic capabilities)
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 6 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 self-hosted Google-One-like assistant: use Next.js + React for frontend, Node.js + Express for backend, Postgres for metadata, S3-compatible storage for files, and Stripe for billing. In scope: user sign-up/login, file upload/download, a chat UI that forwards prompts to an LLM API (configurable API key), Drive import/export via Google Drive API (OAuth), usage tracking, and admin pages for usage/billing. Out of scope: training models, reproducing Gemini, YouTube/Google Home/Health perks, and large-scale multi-tenant optimizations. Provide error handling, input validation, basic automated tests for backend endpoints, and deployment instructions (Docker + managed Postgres + S3).
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 4 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 · 4
Every page the run actually retrieved.
- official productGoogle One overview
- official pricingGoogle One plans & pricing
- open sourceChatGPTNextWeb/NextChat
- open sourceleon-ai/leon
Integrity checks
What held up, and what did not.
