Every company needs data. We built the infrastructure to get it.
Brickroad is the infrastructure layer for data procurement. Source, evaluate, and license data — at the speed of compute.
Trusted by 8,000+ researchers and developers
n × m. Bilateral negotiations. Months.
- 3–6 months per deal, $50k+ in transaction overhead
- Legal review alone consumes 4–8 weeks
- Utility unknown until after acquisition
- Long-tail data sources locked behind friction barriers
- No visibility into what the market actually needs
n + m. One adapter. Seconds.
- Full procurement lifecycle in 7 autonomous tool-use turns
- Per-deal transaction cost: ~$0.07
- Utility estimated before acquisition via sandbox evaluation
- Long-tail datasets become economically viable
- Demand signals visible across the entire network
Source, evaluate, and license data — at the speed of compute
Launch pipelines that autonomously discover, negotiate, and deliver data. One request creates many deals across many providers.
Enterprise integrations to optimize your data and compute spend
Purpose-built for AI labs, agent teams, and data providers. Each engagement is hands-on, scoped to your stack, and designed to deliver measurable outcomes.
Data value estimation
Estimate the marginal utility of data across your existing catalog and the Brickroad network. Know what's worth buying before you spend on compute.
Now Onboarding →Runtime data access
Procure data at runtime across your existing vendors, internal catalogs, and 1.5M+ datasets on the Brickroad network. One integration, every source.
Now Onboarding →Market intelligence
Benchmark pricing, deal comparables, and demand signals across the Brickroad network. Know what data is worth before you negotiate.
Now Onboarding →Building the data frontier
The multiplexer protocol and agent infrastructure are formalized in our published peer-reviewed research.
The Data Multiplexer for the Agent EconomyThesis
Formalizes the structural problem in data markets — n × m bilateral integrations — and introduces the multiplexer as a universal adapter that collapses integrations to n + m while optimizing min(Cd + Ct) subject to utility thresholds.
A Sustainable AI Economy Needs Data Deals That Work for GeneratorsNeurIPS 2025
Ruoxi Jia, Luis Oala, Wenjie Xiong, Suqin Ge, Jiachen T. Wang, Feiyang Kang, Dawn Song — formalizes the structural barriers preventing data generators from capturing fair value in the AI economy.
Stop sourcing. Start shipping.
The infrastructure layer for AI data procurement.