COMPLIANCE / DDQ-READY
No personal data · aggregated to counts, medians & indices · identifiers removed upstream Point-in-time · observation_date vs knowledge_date · append-only · never restated No look-ahead · no survivorship bias · reproducible backtests No MNPI · public, factual, aggregated data only Licensed & redistributable · factual data, not copyrighted content DDQ-ready · FISD-style questionnaires · data dictionary + methodology with every dataset No personal data · aggregated to counts, medians & indices · identifiers removed upstream Point-in-time · observation_date vs knowledge_date · append-only · never restated No MNPI · public, factual, aggregated data only
Compliance & Due Diligence

Built for institutional due diligence.

Acumix data is engineered from day one to clear a compliance officer's desk. Every panel is aggregated, point-in-time, and sourced from public information — no personal identifiers, no material non-public information, and full rights to license and redistribute. We complete standard alternative-data DDQs and ship a data dictionary, methodology and coverage report with every dataset.

acumix_data_attestation Verified
No personal dataAggregated to counts / medians / indices. Identifiers stripped upstream.
Point-in-time integrityobservation_date + knowledge_date. Append-only, never restated.
No MNPIPublic, factual, aggregated data only. Represented & warranted.
Licensed & redistributableFactual data (prices, counts, dates) — not copyrighted content.
DDQ-readyStandard alternative-data / FISD-style questionnaires completed on request.
Compliance Framework

Five commitments that make
the data usable.

Alternative data only helps if it survives your diligence process. Each Acumix dataset is designed around the questions an institutional buyer's compliance, legal and data-science teams actually ask — before a single row is delivered.

No personal data

Aggregated, never individual

Every delivered field is an aggregate — counts, medians, means, ratios and indices computed across many observations. We never sell row-level records tied to an identifiable person.

  • Personal identifiers (review-author names, contact details, account handles) are removed upstream, before aggregation
  • GDPR-aware design: no processing of identifiable EU data subjects in the delivered product
  • Public and aggregated sources only — no logins, no private accounts, no customer-side data
No MNPI

Public, factual, aggregated

We collect only information that is publicly observable to any ordinary user of a public source — published prices, listing counts, ratings, catalog attributes and dates. Nothing confidential, nothing insider-sourced.

  • No material non-public information is collected, held, or delivered — represented and warranted in every agreement
  • No access to a company's internal systems, no confidential feeds, no expert-network content
  • Signals are derived facts and aggregates, not selective disclosures
Sourcing & rights

We hold the right to license

The datasets are proprietary and continuously collected. We warrant the right to license and redistribute them to you, and the deliverable consists of factual data points — not copyrighted expressive content.

  • Delivered data is factual (prices, counts, dates, attributes) — facts are not protected by copyright
  • No wholesale reproduction of protected creative content; we extract structured facts, not media
  • License terms grant you the right to use the aggregated signals for investment research
Provenance & governance

Documented, auditable lineage

Every panel ships with a data dictionary, a written methodology, and coverage statistics. You can trace each aggregate back to its source category, geography and collection window — and reproduce it.

  • Per-field data dictionary: definition, units, aggregation rule, refresh cadence
  • Methodology note: what is measured, how signals are constructed, known limitations
  • Coverage report: geographies, platforms, entity counts and history depth per dataset
Point-in-Time Integrity

Two dates on every row.
Never restated.

The single most important property for a backtest is knowing what you would have known, when. Every Acumix observation carries both the date the fact was true in the world and the date it entered our knowledge base. Records are append-only and never restated — so history you download today is identical to history you downloaded a year ago.

# one row from a point-in-time panel
{
  "entity_id":        "DHER.DE",
  "signal":           "delivery_venue_count_idx",
  "geo":              "DE",
  "value":            104.7,          # index, base=100
  "observation_date": "2025-11-30",   # when the fact was true
  "knowledge_date":   "2025-12-02",   # when we knew it
  "vintage":           "append_only",
  "restated":          false
}

# backtest as-of any historical knowledge_date:
# SELECT * WHERE knowledge_date <= as_of_date
# → returns exactly what was knowable then.
No look-ahead bias

Because knowledge_date reflects real collection latency (not the observation date), an as-of query never leaks information that wasn't yet available. Your backtest sees the data on the day a live strategy would have.

No survivorship bias

Entities that later delisted, merged, or stopped trading remain in the panel with their full history. We do not prune the universe to today's survivors, so cross-sectional studies stay unbiased.

Reproducible backtests

Append-only, never-restated storage means a given (observation_date, knowledge_date) pair always returns the same value. Re-run last quarter's research and get byte-identical inputs.

Due-Diligence Ready

Your DDQ is
already answered.

We routinely complete standard alternative-data due-diligence questionnaires — including FISD-style data-sourcing questionnaires — and provide the supporting documentation your data-governance and compliance teams need to onboard a new provider. Everything below ships with every dataset, at no extra cost.

Completed DDQ

We fill out your alternative-data / FISD-style questionnaire covering sourcing, PII handling, MNPI, licensing, retention and change management.

Data dictionary

Every field defined — name, meaning, units, aggregation rule, valid range and refresh cadence — so your analysts can model against it without guesswork.

Written methodology

How each signal is constructed and aggregated, the collection window, known gaps and limitations, and the mapping from raw facts to delivered indices.

Coverage statistics

Geographies, platforms, entity counts, history depth and cadence per dataset — plus a security master mapping each entity to its ticker.

Compliance representations

Written representations and warranties: no PII in the deliverable, no MNPI, public sources only, and the right to license and redistribute.

Evaluation sample

A representative point-in-time sample so your team can validate schema, coverage and integrity before committing — reviewed under NDA on request.

Request our compliance pack.

Tell us the coverage you need and we'll return a completed DDQ, the data dictionary and methodology, coverage statistics, and a point-in-time evaluation sample — under NDA if you prefer.

Request Compliance Pack & Sample