Project and task management decision

Rize

A basic automatic tracker with a desktop agent, simple categorization, and a team dashboard is feasible to build and self-host, but reproducing Rize's cross-platform polish, proprietary AI tuning, integrations catalogue, and enterprise features would require significantly more time and resources.

Visit website
You pay

$12.99/mo

$156/yr

Read off the official pricing page.

You’d pay instead

$100one-off80 h to build

$50/mo12 h/mo upkeep

On cash alone, building overtakes the subscription at 5 seats.

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

  • Capture focused-window events on desktops, map them to projects/clients (AI or heuristics), send events to a backend that aggregates per-user and per-team, provide a web dashboard for utilization/profitability and exports.

What it still won’t have

  • Polished cross-platform native app and installers
  • Proprietary AI model tuning and AI-credit system
  • Enterprise features (SOC2, SSO/SCIM, dedicated SLAs)
  • Mature integrations catalogue and connector polish
  • Polished client-ready PDF reports and priority support

What remains hard

  • Brand trustTrusted by teams worldwide
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 5 seats.

Paid seatsseats

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

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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 automatic time-tracking stack: create a native desktop agent for macOS (or Windows) that emits focused-window events (app name, window title, URL) every 15s; implement a simple classifier service (Python) that maps metadata to project/client using configurable rules and a small ML fallback; build a backend (Node/Express + Postgres) to ingest events, deduplicate, store per-user times, and compute per-project, per-user, and utilization aggregates; create a React web dashboard that shows live team utilization, hours by project/client, project profitability (revenue/hour inputs), and CSV/PDF exports; include OAuth sign-in, an admin panel to create projects/clients and mapping rules, and webhooks for integrations. Out of scope: advanced AI training, SOC2, SSO/SCIM, mobile clients. Provide error handling, retries for agent-to-backend uploads, automated tests for backend APIs, and basic end-to-end tests for the dashboard.
How we checked3 sources · 3/3 runs agreed · evidence score 62

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Evidence score62

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 →

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat quoted from the page