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Services / Custom Data

If it isn't tracked yet, we build it

If the attribute your workflow needs doesn't exist in any data catalog, Veridion builds it from primary sources. New attributes in weeks, not quarters. Same 642M-company corpus as every standard enrichment output.

Business Importance Tags

Custom tagging classifying companies by their systemic importance to a financial ecosystem. Integrated into credit-risk infrastructure.

Built from
Entity graphFinancial roleCorporate hierarchy
Example outputSystemically important · Tier 1Major German bank engagement
Early warning signals

Pre-distress and pre-growth detection from web changes, news sentiment shifts, headcount deltas, and domain activity.

Built from
Web changesNews sentimentHeadcount delta
Example outputPre-distress score 0.78Acme Logistics
Custom sector classification

Product-level tagging deeper than NAICS. Distinguishes specific certifications, capabilities, and product subtypes within a sector.

Built from
Product dataClient taxonomyML labeling
Example outputClass II contract manufacturerMed-device sector engagement

Failure modes

Where standard enrichment runs out.

Off-the-shelf enrichment stops here. Without a custom dataset, this is what your teams are left working around.

Non-standard taxonomy

What happens when your sector model is not NAICS and off-the-shelf returns the wrong bucket?

Every downstream model inherits the misclassification. Decisions land on the wrong cohort.

Proprietary risk signals

What happens when pre-distress or systemic-importance scoring does not exist in any data catalog?

Either you build it in-house from raw sources, or you accept blind spots in the risk surface.

Regulatory specificity

What happens when classification needs precision no off-the-shelf product supports?

Compliance ships generic; the auditor finds the gap.

Custom universe scope

What happens when companies need filtering by criteria that do not map to standard dimensions?

Generic filters return half the cohort. The other half stays invisible to every downstream workflow.

How a custom dataset gets built

Pilot first. Full scope unlocks only after the pilot accuracy clears.

A typical pilot runs 8 weeks. Every week ships an artifact you can audit. Powered by the Attribute Factory: new attributes in weeks, not the 6 to 12 months typical of fixed-schema vendors.

  1. 1
    W1 · Scoping
    Pick 2 to 3 attributes; lock acceptance criteria; agree the sample universe.Ships: Acceptance criteria doc
  2. 2
    W2–3 · Attribute design
    Architect extraction logic and source strategy per attribute. Validate on sample.Ships: Extraction spec
  3. 3
    W4–6 · Build
    Run pipelines across the representative sample. Tune for accuracy targets.Ships: Validated sample dataset
  4. 4
    W7 · Accuracy review
    Validate against acceptance criteria; investigate edge cases; decide scale-up.Ships: Accuracy report
  5. 5
    W8 · Handoff
    Sample, extraction logic, methodology, refresh schedule. Ready to scale.Ships: Production-ready package

Where Custom Data fits

Six common shapes Custom Data takes.

Bespoke wiring for agentic and analytical workflows. Each one is built from primary sources on the same corpus that powers standard enrichment.

Systemic-risk scoring

Score every company by its systemic importance to a market or supply chain: corporate role, interconnectedness, substitutability. Wired directly into credit and risk infrastructure.

Counterparty exposure mapping

A bank or insurer's full counterparty universe resolved to canonical entities and rolled up to parent groups, so concentration and correlated exposure surface across the whole book.

Regulatory classification datasets

Company populations classified to a specific regime (CSRD scope, UFLPA regions, sanctions-adjacent jurisdictions) with documented boundaries and exclusion rules that land in the audit file.

Pre-distress early-warning scoring

Bespoke leading-indicator scores from web changes, hiring deltas, and news signals, tuned to the portfolio you actually hold.

Industry sub-segment mapping

Break broad NAICS categories into meaningful sub-segments based on business tags and product-level signals. Closer than any standard rollup.

Market Intelligence Command Center

Full agentic workflow: input a company or industry, get competitor discovery, market sizing, gap analysis, country-expansion strategy, and a 200 to 1,000-company lead list.

Strategic Program tier

Custom Data engagements run as a Strategic Program. Multi-month, separately scoped, with Veridion's data science and ML teams involved end-to-end. Output is a delivered dataset or a recurring data feed.

What you get

Deliverables

A proprietary dataset that fits your schema exactly, with documented extraction logic, accuracy benchmarks, and a maintainable refresh framework. Every deliverable ships in the format, cadence, and destination your stack already uses.

Custom attribute definitions

Versioned and replayable on future refreshes, with documented rules for every attribute.

Tailored company datasets

Delivered against your exact schema, in the format your systems already consume.

Coverage and quality benchmarks

Accuracy samples, fill rates, and edge-case documentation, so downstream consumers can apply their own thresholds.

FAQ

Questions worth asking up front.

Custom only

Talk to our data team.

No self-serve for custom. It starts with a conversation about your use case and stack.