Our Business Model

• Scope: 25+ production‑ready packs spanning markets, macro, company fundamentals, filings/KPIs, logistics, and web intelligence.
• Format: CSV/Parquet, direct‑query connectors, and secure presigned downloads. All packs include a data dictionary, schema version, and change log.
• Model‑ready: Clean joins, consistent keys, UTC timestamps, and train/test splits where applicable; optional labeling for supervised tasks.
• Provenance: Source URLs, extraction tags, validation logs, and license mapping included in every release.

• Domain Pro bundles (by function, e.g., Finance, Supply Chain) combine multiple packs with unified schemas and cross‑pack joins.
• EMPIRE bundle offers organization‑wide access to the full library with priority SLAs and roadmap influence.

• Source feasibility, parser build‑out, historical backfills, and one‑off research pulls.
• Data normalization to client ontologies (entity resolution, ticker/ISIN/LEI, location canonicalization, etc.).

• Integration support, schema mapping, and MLOps handoff.
• Priority support, training sessions, and implementation playbooks.

• AI/ML teams at startups and large enterprises training models on real‑world data.
• Quant funds & prop desks needing clean alternative + fundamentals signals.
• FinTech & analytics vendors embedding structured data in their products.
• Consultancies & systems integrators delivering data‑led programs.

• Quality: All packs pass automated validation (schema, ranges, nulls) and include provenance.
• Freshness: Clear update cadences (daily/weekly/monthly by pack) with published SLAs.
• Interoperability: Consistent IDs, time standards, and join keys across packs.
• Transparency: Full lineage, versioned schemas, and deprecation notices.
• Speed to Value: Evaluation samples, quickstarts, and battle‑tested joins reduce time‑to‑production.

• Per‑Pack Plans: Tiered by refresh frequency, history depth, and support level.
• Bundle Plans: Domain Pro bundles for functional teams; EMPIRE bundle for org‑wide access.
• Terms: Annual subscriptions with optional quarterly billing; multi‑year discounts available.

• Bursting: Temporary overage buckets for peak research periods.

• Company‑wide Rights: Unlimited internal users and environments under one license.
• Redistribution Add‑On: For vendors embedding QuantLens data in commercial products (rev‑share or fixed royalty).

• Fixed‑scope integrations, ontology mapping, and historical backfills.
• Training workshops and model‑readiness audits.

Pricing Philosophy

Transparent tiers aligned to value (freshness, history, scope). We avoid hidden fees and publish clear rights per tier.

• Permitted Uses: Internal analytics, AI/ML training, backtesting, and derived features.
• Restrictions: No raw data redistribution without a redistribution add‑on. No use in violating laws or third‑party rights.
• Attribution: Not required for internal use; required for public research if quoting QuantLens figures.
• Model Training: Allowed under standard commercial license; model weights may be distributed if they do not expose underlying rows.

• Standard Commercial: Team‑level access, internal use.
• Enterprise Unlimited: Org‑wide internal use, multiple environments.
• Redistribution License: Rights to embed/share downstream with controls.

• Direct via our website catalog (samples, docs, and instant trials for select packs).
• Partner Channels with data marketplaces and SIs (co‑selling and solution packaging).
• All deliveries via secure presigned URLs, direct‑query connectors, or client‑preferred storage handoff.

1. Discover: Browse packs, read data dictionaries, view coverage and freshness.
2. Evaluate: Download sample slices (anonymized/limited), test joins with your data.
3. Scope: Choose packs/bundles, define history depth and refresh cadence.
4. Contract: Sign subscription & license; optional redistribution add‑on.
5. Integrate: Receive credentials or presigned links; map to your IDs.
6. Operate: Scheduled refreshes, release notes, and SLA monitoring.
7. Expand: Add packs or custom sourcing as needs grow.

CTAs we use: Request Sample, Get Access, Talk to Data Engineer.

• Freshness SLAs: Pack‑specific (e.g., daily by 10:00 UTC; weekly every Monday 12:00 UTC).
• Quality Gates: Schema checks, statistical drift, range/regex rules, and null budgets per column.
• Versioning: Semantic versions for schema; content versions for each release; deprecation policy with 60‑day notice.
• Lineage & Audit: Source URLs, extraction tags/regex, validation summaries, and changelogs shipped with each drop.
• Support: Standard (business hours) or Priority (24×5) with defined response/restore targets.

• Gross Margin: 70–85% depending on delivery mode and compute needs.
• COGS: Storage, egress, pipeline compute, QA labor.
• Levers: Columnar compression, incremental refresh, query pushdown, and cache hits.

• Start with Request Sample → we provide a slice and data dictionary.
• We align on scope, SLAs, and rights. You get a clear delivery plan, not surprises.
• Ongoing: predictable refreshes, release notes, and a named engineer for support.

QuantLens delivers curated, model‑ready data for AI and analytics teams. We provide validated datasets with clear lineage, consistent schemas, and enterprise‑grade SLAs — available by pack, bundle, or enterprise license, with optional services for fast integration.