Analytics and monitoring decision
ArtificialWatch
A competent developer can reproduce the core alerting/watchlist functionality in about a week and maintain it for small-scale use; the product's value-add (phone-call alarm and evaluation harness) can be approximated but not fully replaced without extra engineering.
Visit website↗No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- Poll provider APIs on a schedule, detect a newly-answering model by issuing a test prompt and confirming on a second sweep, send notifications (email/Chrome push free; SMS/phone via paid channels), store and manage user watchlists and per-model routing, display a minimal dashboard with recent detections
What it still won’t have
- built-in charter pricing and lifetime guarantees
- the Call/Watchtower specialized evaluation harness and regression history
- polished product UX and public track record
- any proprietary subscriptions or negotiated SMS/voice volume discounts
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 3 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 AI-model-launch watcher using Node.js (Express) + Postgres + Redis (for job locks) and a single-worker cron. Core features in scope: 1) a scheduled poller that queries a configurable list of provider APIs every 60s and stores responses; 2) deduplication and confirmation logic that requires a second successful detection before emitting an alert; 3) a test-prompt runner to validate a model answers; 4) user accounts, per-user watchlists, and per-model channel routing preferences; 5) notification integrations: email (SMTP), Chrome push (Web Push), and Twilio for SMS and automated calls; 6) a small React dashboard to manage watchlists and show recent alerts. Out of scope: building a large-scale provider catalog, automated model benchmarking/harness (Watchtower), and Polymarket integration. Require error handling for API failures and rate limits, retries with backoff, unit tests for detection logic, and end-to-end tests for the notification pipeline.
How we checked
How the score was reached
- Build verdict base78
- 4 cited sources+3
- Price verified on pricing page+3
- Evidence score84
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 productArtificialWatch — Know the minute a new AI model drops
- official pricingArtificialWatch pricing
- official pricingArtificialWatch pricing — The Call
- official pricingArtificialWatch pricing — Watchtower
Integrity checks
What held up, and what did not.
