Data

Alternative data, marked up for credit.

We sell lenders the data their scorecard is missing — collected from other organizations, validated, and turned into signal a credit model can actually use.

app.sylvent.ai
Sylvent — borrower enrichment dashboard
What it is

Beyond the standard sources.

Standard credit data is thin and missing for most small businesses. We step past it — into the data their real operations already generate.

Standard data is thin

Bureau history, declared assets, bank-app usage and basic tax — stale or missing for most small businesses.

Data from real operations

Signals from the organizations a business already deals with: suppliers, telecom, services and reputation.

Supplier-first, verified

Suppliers are large and verifiable, so supplier data is our strongest first signal — cross-checked against several criteria.

The signals

Where the real picture lives.

Hundreds of alternative signals, pulled from the organizations a real business already deals with — then validated and weighted into a score.

Supplier data

Who a business buys from and how much — verified against large, reliable suppliers. Our first and strongest signal.

Inventory & storage

Use of warehousing and stock-level services as a demand signal.

Telecom

Connectivity and usage patterns tied to a real, active business.

Online activity

Web presence and traffic that reflect genuine operations.

Online reputation

Reviews, ratings and sentiment across the web.

Service usage

Other platforms and tools the business relies on day to day.

240+

validated alternative signals per applicant, weighted into one calibrated score.

How it works

From raw data to a usable score.

Collecting data is easy. The hard part — and our moat — is turning it into a feature a credit model can read: normalized, validated and weighted.

Collect

Raw data from suppliers, telecom, web and the services a business uses.

Validate

Schema, range and consistency checks, dedup and freshness decay.

Mark up

Normalize and weight each signal by predictive importance.

Score

Return a calibrated probability and a clear approve / decline.

Integration

One API call turns a thin file into a complete one.

The lender connects over API. When a new application comes in, they call us — we find, collect and mark up everything we have on the borrower, run internal scoring enriched with alternative data, and return it to the lender.

Analyze a few standard fields and the file is incomplete. Analyze hundreds of alternative signals — supplier, telecom, online activity, reputation — and it’s whole. Default risk drops.

enrich.tsTS
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const res = await sylvent.enrich({
  borrower: "MX-RFC-8841",
  amount: 250_000,
})
 
// 38 fields enriched from 240+ signals
res.score     // 0.91
res.risk      // "low"
res.decision  // "approved"
The result

Richer files, lower risk.

How we work
  1. 01

    Connect

    You integrate our API into your origination flow.

  2. 02

    Map & validate

    We map and validate the alternative sources for your segment.

  3. 03

    Live enrichment

    Every application is enriched and scored in real time.

  4. 04

    Monitor & expand

    We track performance and keep adding new signals.

2×+

fewer defaults and delinquencies, by design — sharper, validated signal on every file.

Thicker files

Hundreds of alternative signals turn thin applications into scorable profiles.

One API

No new core — enrich and score every application through a single call.

Fewer false rejections

See the businesses a thin scorecard was blind to — safely, with verified signal.

Decide in minutes

One enriched, scored file instead of a manual chase across separate tools.

Talk to us

Enrich your next application.

Tell us about your lending and we’ll set up a demo — with the data running live on your own applications.

  • One API — no core replacement
  • Hundreds of validated alternative signals
  • Designed to cut default risk 2×+