Data Product Development
We build data products — the datasets, APIs, pipelines, licensing frameworks, and quality systems that turn raw data into something customers pay for. The founding team shipped a 300B+ token legal dataset to 25+ Fortune 500 companies and open-sourced the largest copyright-clean AI training corpus in existence.
Your organization has valuable data, but it is trapped in operational systems, inconsistent formats, and unclear licensing terms. Most consulting firms will help you think about your data strategy. We build the actual product: the pipeline, the quality systems, the licensing framework, the API, and the documentation. We have done it before, at scale.
Starting at $15K | 2-24 weeks
Services
Dataset Development & Curation
Production-quality datasets: sourced, cleaned, normalized, documented, and versioned. Ingestion pipelines, schema design, metadata enrichment, quality validation, and provenance tracking. We built KL3M (132M+ documents, 1.35T tokens from 16 sources) and the Kelvin Legal DataPack (300B+ tokens from ~100TB).
8-20 weeks
Data API & Delivery Infrastructure
REST and GraphQL APIs that serve your dataset to internal or external consumers. Authentication, rate limiting, usage metering, billing integration, SDK development, and OpenAPI documentation.
6-12 weeks
Data Pipeline & Processing Infrastructure
Automated ingestion, transformation, and serving infrastructure. Source connectors, ETL/ELT pipelines, data quality and observability systems, scheduling, orchestration, and infrastructure-as-code deployment.
4-12 weeks
Data Licensing & Rights Framework
Source data rights audit, output licensing structure design, copyright and IP compliance review, provenance documentation, and Fairly Trained certification support. We track 70+ active AI training data copyright lawsuits.
2-6 weeks
Data Product Monetization & Go-to-Market
Pricing model design, customer segmentation, distribution strategy, data contract and SLA definition, and revenue forecasting. We have shipped enterprise licensing, subscription, consumption, and marketplace models.
2-4 weeks
Data Marketplace Development
Platform architecture for listing, discovering, and delivering data products, whether internal (data mesh) or external (commercial marketplace). Catalog, access control, entitlements, usage tracking, and billing integration.
12-24 weeks
Why us
We have shipped data products at scale
Kelvin Legal DataPack: 300B+ tokens from ~100TB of legal content, sold to 25+ Fortune 500 companies. KL3M: 132M+ copyright-clean documents, first Fairly Trained certified dataset. OpenEDGAR: open-source SEC data pipeline. Most firms offering this service have never shipped a data product themselves.
We solve the licensing problem most teams ignore
Most data product efforts die on the licensing question. We have navigated copyright, licensing, and provenance for datasets spanning thousands of sources. CPA + dual CIPP + Certified AI Auditor credentials. We know which data you can use, how to document your rights, and how to license your output.
We build the whole stack, not just the pipeline
Pipeline is necessary but not sufficient. A data product needs schema design, quality systems, documentation, versioning, delivery infrastructure, licensing, and customer support tooling. We have built all of these for our own data products.
Why licens.io?
| Big 4 | licens.io | |
|---|---|---|
| Data product experience | Advise from theory | Shipped 300B+ token dataset to Fortune 500 |
| Licensing expertise | General IP awareness | Track 70+ AI copyright lawsuits; built Fairly Trained dataset |
| Pipeline depth | Recommend tools | Built pipelines processing 100TB+ |
| AI training data | Emerging practice | Wrote the paper; built the first certified corpus |
| Integration | Separate data eng + legal teams | One team builds, licenses, and governs |
| Pricing | Hourly, $200-400/hr | Fixed-fee, $15K-$300K |
Data product experience
Big 4
Advise from theory
licens.io
Shipped 300B+ token dataset to Fortune 500
Licensing expertise
Big 4
General IP awareness
licens.io
Track 70+ AI copyright lawsuits; built Fairly Trained dataset
Pipeline depth
Big 4
Recommend tools
licens.io
Built pipelines processing 100TB+
AI training data
Big 4
Emerging practice
licens.io
Wrote the paper; built the first certified corpus
Integration
Big 4
Separate data eng + legal teams
licens.io
One team builds, licenses, and governs
Pricing
Big 4
Hourly, $200-400/hr
licens.io
Fixed-fee, $15K-$300K
Who this is for
- ✓ Data-rich companies with monetization ambitions that want to turn internal data into a revenue-generating product
- ✓ AI companies building training datasets that need large-scale, copyright-clean corpora with clear provenance and quality systems
- ✓ PE/VC portfolio companies with data assets where data is an undermonetized asset and the operating partner wants recurring revenue from data licensing
- ✓ Legal, financial, and professional services firms sitting on decades of proprietary content that could become a data product if properly structured, licensed, and delivered
- ✓ Organizations building internal data products using data mesh or similar approaches to improve cross-team data access and quality
- ✓ Companies entering data marketplaces that need the infrastructure, quality systems, and licensing to list and sell data commercially
Frequently asked questions
What is a data product?
A data product is a curated, documented, and governed dataset, API, or data service designed for repeated use by specific consumers. It applies product management discipline to data: defined quality SLAs, versioning, documentation, support, and a delivery mechanism. Examples range from commercial datasets like the Kelvin Legal DataPack to internal data APIs serving analytics and ML teams.
How is data product development different from data strategy consulting?
Data strategy consulting produces recommendations: governance frameworks, maturity assessments, roadmaps. Data product development produces a working product. We build the dataset, the API, the pipeline, and the licensing framework. You get production code, deployed infrastructure, and a data product your customers can actually use. We offer data strategy advisory separately.
How do you handle licensing and copyright for data products?
We audit source data rights, design output licensing structures, document provenance, and build compliance into the pipeline. We built the first Fairly Trained certified dataset and track active AI training data copyright litigation. The licensing question kills more data product efforts than the engineering does. We know how to solve it.
How long does it take to build a data product?
A data licensing framework takes 2-6 weeks. A data pipeline takes 4-12 weeks. A full-stack data product, from sourcing through API delivery, typically takes 12-24 weeks. We scope based on your sources, complexity, and quality requirements. All engagements are fixed-fee.
What data product monetization models work?
The main models are enterprise licensing (fixed annual fee per customer), subscription tiers (volume or feature-based), consumption pricing (per-query API access), bulk data licensing, and marketplace listing fees. The right model depends on your data, your customers, and your competitive position. We have used enterprise licensing for the Kelvin Legal DataPack and open distribution for KL3M.
Can you build a data product from public or government data?
Yes. KL3M was built entirely from public and properly licensed sources: government filings, public records, and open-license content. OpenEDGAR is an open-source pipeline built on SEC EDGAR public data. Public data still requires significant engineering. The data is free; the product is not.
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Read moreReady to build a data product?
We'll scope the pipeline, the quality systems, the licensing, and the delivery infrastructure, then build it. Fixed price, defined timeline.