Analytics and monitoring decision

Treendly

A technical user can build a useful trend-finding replacement for core search and charts, but Treendly’s proprietary curated dataset, editorial curation, and enterprise features make a full parity commercial replacement impractical.

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You pay

$8.25/mo

$99/yr

Read off the official pricing page.

You’d pay instead

$50one-off24 h to build

$0/mo3 h/mo upkeep

On cash alone, building overtakes the subscription at 1 seat.

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 Treendly alternatives, with the arithmetic →

What a replacement has to do

  • User enters a term → system fetches time-series signals → compute growth/pace/peaks → store results → surface trends in a web UI and simple API

What it still won’t have

  • Treendly proprietary curated dataset and historical coverage
  • Premium curated newsletter and editorial curation
  • Enterprise features (unlimited monitors, enterprise API UID/passwords)
  • Integrations and Chrome/Notion/WordPress extensions
  • Any proprietary forecasting/insights models behind Treendly

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

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

Not run yet
Build a minimal trend-discovery service using Node.js (Express) + Postgres (or TimescaleDB) + React. Core features in scope: (1) a data ingestor that pulls Google Trends and other public signals on a schedule and normalizes them; (2) background jobs to compute pace, peaks, simple 6-month forecast and opportunity score; (3) a REST API endpoint /quick-get mirroring Treendly's basic response fields; (4) a React UI to search terms, show time-series charts (use Chart.js), and filter by pace/opportunity; (5) simple auth and a 1-seat free/pro toggle (no payments integration required). Out of scope: proprietary datasets, enterprise multi-seat billing, Chrome/Notion/WordPress integrations, advanced ML forecasting. Include error handling, retry/backoff for external calls, logging, and unit tests for ingest and metric computation. Provide Dockerfiles and a docker-compose for local dev and a short README with deployment steps to a single t3.small-equivalent VM and managed Postgres.
How we checked5 sources · 2/3 runs agreed · evidence score 63

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.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded