Public records, structured for software.
Things is building a platform that turns fragmented public records into clean, continuously updated datasets. We automate collection, normalization, and delivery through APIs for businesses and AI applications.
§ Product brief
Public information is often published across disconnected systems, inconsistent formats, and update schedules that make it difficult to use in software.
The platform automates collection, normalization, maintenance, and delivery so customers can work with stable datasets instead of rebuilding source-specific pipelines. Access is planned through web and mobile applications and documented APIs.
From source to usable record.
A continuous sequence keeps each delivered dataset traceable, consistent, and current.
- 01
Collect
Acquire records from disconnected public sources through repeatable, monitored workflows.
- 02
Normalize
Resolve inconsistent formats and fields into stable, queryable data models.
- 03
Maintain
Recheck sources, track changes, and keep delivered datasets current over time.
- 04
Deliver
Make the resulting data available through web and mobile applications and documented APIs.
§ Designed for
Businesses
Use normalized public information in research, operations, analysis, and customer-facing products without maintaining separate collection systems.
Consumers
Find and use public information through clear web and mobile experiences instead of navigating fragmented source systems.
AI applications
Connect AI and application workflows to structured, maintained datasets through documented APIs.
Cloud infrastructure for a data-intensive product.
The platform is planned to run primarily on AWS. The architecture will support scalable collection, serverless processing, data warehousing, and core AI/ML workloads as source coverage and customer demand grow.
Scalable data architecture
Cloud infrastructure designed to grow with source coverage, update frequency, and customer demand.
Serverless processing
Event-driven collection and transformation workloads that can scale independently as records change.
Data warehousing
Structured storage and query layers for maintained datasets, analytics, and customer delivery.
AI & machine learning
AI/ML capabilities for understanding inconsistent records and making normalized data more useful.
§ Product facts
- Stage
- Ideating and building the initial product
- Planned launch
- October 1, 2026
- Primary customers
- Consumers and businesses
- Access
- Web browser, mobile application, and API
- Planned infrastructure
- Primarily AWS
- AI/ML
- Core AI/ML product
- Funding
- Bootstrapped
- Company
- Things LLC
- Founder
- Will Humphreys, Founder & CEO
- Location
- Orlando, Florida