@uvrn/core

UVRN Delta Engine core — deterministic multi-source comparison and verification. Runs the Delta formula on bundles, produces canonical receipts with SHA-256 hashes, and validates or verifies bundles and receipts. Release: 1.5.1.

Disclaimer: UVRN is in Alpha testing. The engine measures whether your sources agree with each other — not whether they’re correct. Final trust of output rests with the user. Use at your own discretion. Have fun.

UVRN makes no claims to "truth", the "verification" is the output of math — it is up to any user to decide if claim is actually "true" — Research and testing are absolutely recommended per use case and individual system!!

Install

npm install @uvrn/core

Or with pnpm:

pnpm add @uvrn/core

Usage

1. Define a bundle: a claim, a threshold, and at least two data specs with metrics.
2. Call runDeltaEngine(bundle) to get a receipt (outcome, delta, hash).
3. Use validateBundle and verifyReceipt for validation and integrity checks.

import { runDeltaEngine, validateBundle, verifyReceipt } from '@uvrn/core';

const bundle = {
  bundleId: 'example-001',
  claim: 'Metrics from source-a and source-b should agree within 10%.',
  thresholdPct: 0.10,
  dataSpecs: [
    {
      id: 'source-a',
      label: 'Source A',
      sourceKind: 'report',
      originDocIds: ['doc-a-1'],
      metrics: [{ key: 'count', value: 100 }],
    },
    {
      id: 'source-b',
      label: 'Source B',
      sourceKind: 'report',
      originDocIds: ['doc-b-1'],
      metrics: [{ key: 'count', value: 105 }],
    },
  ],
};

const receipt = runDeltaEngine(bundle);
console.log(receipt.outcome);   // 'consensus' | 'indeterminate'
console.log(receipt.deltaFinal); // max delta across metrics
console.log(receipt.hash);      // SHA-256 of canonical receipt

Use cases

• Compare two or more data sources — Run the Delta formula on metrics (e.g. report A vs report B) and get a deterministic consensus or indeterminate outcome. Note: consensus means the sources agree with each other within the threshold — not that either source is correct.
• Produce verifiable receipts — Every receipt has a canonical hash; use verifyReceipt(receipt) to recompute and check integrity.
• Validate before running — Use validateBundle(bundle) to check structure and threshold without executing the engine.
• Integrate into pipelines — Use as a library in CI, ETL, or any service that needs deterministic comparison and proof.

Use case: Product / content research

Your audience and market data often live in multiple places: platform analytics (e.g. YouTube, Spotify), surveys, CRM exports, or APIs. When one source says +41%, another +35%, and a third +38%, it’s hard to know if you can safely pivot or ship — who do you trust?

UVRN helps content creators, product teams, and designers reconcile that split. You feed 2 to 100+ data sources into the Delta Engine (each with comparable metrics). The engine:

1. Canonically serializes the inputs, runs a deterministic delta comparison, and checks whether the spread is within your threshold (e.g. 8%).
2. Produces a verifiable receipt with a clear outcome: consensus (sources agree within threshold — e.g. “Both signals agree. Pivot with proof.”) or indeterminate (outside threshold — time to investigate).
3. The receipt is hash-verified and reproducible; you can share it with partners or your team so anyone can verify the same result.

Example: Three sources — YouTube Analytics (+41% how-to views), a subscriber survey (+35% demand), and a platform API (+38% engagement). The engine returns consensus with a 4.83% delta (within an 8% threshold), so the designer or creator can confidently decide to pivot or ship, backed by a receipt — not just a hunch.

Links

Open source: Source code and issues: GitHub (uvrn-packages). Project landing: UVRN.

• Repository — monorepo (this package: uvrn-core)
• @uvrn/sdk — programmatic client (CLI/HTTP/local) built on this core
• @uvrn/cli — run the engine from the command line