Open source · Self-hosted · Works fully offline

Hackathon judging you can defend.

Juryza runs your whole hackathon — registration, teams, submissions, judging, community voting and published results — and makes the ranking statistically fair. A harsh judge can't sink a project, and every score is on the record.

No cloud account One-command install MIT licensed

juryza.local/e/sample-hack-2026/leaderboard

Judged leaderboard

41 projects · 30 judges · 123 reviews

Raw meanNormalized
  1. 1

    Issue Radar

    Night Owls

    +1.62▲3
  2. 2

    Carbon Ledger

    Greenfield

    +1.31—
  3. 3

    Loop Assist

    Pair of Docs

    +0.94▲2
  4. 4

    Quiet Hours

    Deep Work

    +0.52▼3

Impact

30%

Execution

35%

Innovation

20%

Demo

15%

Live on this instance

Events hosted
0
Projects submitted
0
Participants
0
Judges on panels
0
Scores recorded
0
Community votes
0

Everything in the box

From first sign-up to signed certificate

One self-hosted app covers the whole event. No plugins to buy, no spreadsheet glue, no per-seat pricing.

Run

Events & tracks

Dates, tracks, prizes and rules in one place. The lifecycle follows the calendar — no manual phase flipping.

Run

Teams by invite link

Create a team, share one link. Max team size and deadlines are enforced by the backend, not the button.

Run

Notion-style write-ups

A block editor with slash commands for project pages — headings, checklists, code, embeds. Drafts until submit.

Judge

Weighted rubric

Organizer-defined criteria and weights. Judges score what matters; weights normalize to 100% automatically.

Judge

Backend role isolation

A judge can't read another judge's scores — not in the UI, not with a raw curl. Enforced on every request.

Judge

Z-score normalization

Each judge's scores are standardized against their own mean and spread, so harsh and lenient judges count equally.

Judge

Pairwise Bradley–Terry

Prefer comparisons to absolute scores? Judges pick A vs B and a Bradley–Terry model turns that into a ranking.

Judge

Quadratic community voting

Voters spread a credit budget; n votes cost n². Enthusiasm counts, but a single fan club can't buy the prize.

Judge

Similarity & comparison

Duplicate and near-duplicate submissions are flagged automatically, with side-by-side project comparison.

Run

Readable audit trail

Every submission, score, publish and permission change is logged with actor and time — in plain language.

Integrate

REST API, webhooks, OpenAPI

Every UI action is an API call. Bearer tokens, signed webhooks and an OpenAPI 3.1 spec for your own tooling.

Integrate

Verifiable certificates

Signed certificates for winners and judges. Anyone can check a serial — tampered records fail verification.

Integrate

Embeddable gallery

Drop the public project gallery into your event site. Search and track filters come with it.

Integrate

CSV / JSON import-export

Bulk-import projects, export scores and results. Your data leaves in open formats whenever you want.

Built to be read by machines, too

Browse the full API reference, or pull the spec straight into your client generator.

How it works

Five steps, one timeline

Every event moves through the same lifecycle. Phases follow your dates, so nobody forgets to close submissions at midnight.

  1. 1

    Create

    Set dates, tracks, prizes and a weighted rubric. Publish when ready.

  2. 2

    Submit

    Teams form by link and write their project up. The deadline is enforced server-side.

  3. 3

    Judge

    Assignments are balanced across the panel. Judges score blind to each other.

  4. 4

    Vote

    The community spends quadratic credits on a randomized ballot.

  5. 5

    Publish

    Normalized results stay hidden until you publish. Certificates are signed.

Judging integrity

Luck of the draw shouldn't decide the winner

With 40 projects and 30 judges, no one sees everything. If your project lands with the toughest judge, a raw average quietly punishes you. Juryza compares each score to that judge's own habits first.

Per-judge standardization

z = (x − μjudge) / σjudge

Then the weighted rubric is applied and z-scores are averaged per project. Ties and single-review projects are handled explicitly — the method is documented, with a worked proof.

  • Judges only ever see their own assignments and scores — enforced by the API.
  • Pairwise Bradley–Terry mode for events that prefer comparisons to scales.
  • Every score change lands in the audit trail, with who and when.

Judge A

lenient

μ 4.3 · σ 0.3

Judge B

harsh

μ 2.5 · σ 0.6

ProjectRawRankzFair rank

Quiet Hours

reviewed by Judge A

4.5#1+0.83#3 ▼

Carbon Ledger

reviewed by Judge A

4.5#2+0.50#4 ▼

Issue Radar

reviewed by Judge B

3.4#3+1.73#1 ▲

Loop Assist

reviewed by Judge B

3.1#4+1.18#2 ▲

Illustrative: Judge B's 6.8 is exceptional for Judge B. Raw averages hide that; normalization surfaces it.

FAQ

Questions organizers ask

Something else? The API reference documents every rule the backend enforces.

Your next hackathon, judged fairly — running in one command.

Self-host it on a laptop for a weekend event or a server for a season. Seeded with sample data so you can click through everything first.

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