Guilded AI is an expert data foundry that builds custom data pipelines connecting credentialed specialists with AI developers seeking high-quality training data and recurring evaluations. The company designs production processes grounded in social science and institutional design, giving expert contributors long-term equity incentives tied to company growth. Its data products treat provenance and attestation as first-class concerns, enabling transparent, verifiable claims about data origin and permitted use.
Funding
Funding not disclosed
Founders
Product
Problem
AI developers face a persistent challenge in sourcing reliable, high-quality training and evaluation data from genuine subject-matter experts. Conventional data labeling approaches rely on anonymous taskers who lack domain credentials, producing data with unclear provenance and questionable quality. Existing market structures provide weak incentives for experts to contribute their specialized knowledge, limiting the depth of expertise available for AI training.
Solution
Guilded AI operates as an expert data foundry that builds pipelines connecting credentialed specialists with AI builders who need verified, high-quality data. The company scopes data needs, identifies qualified contributors, and designs production processes around each use case using expertise in social science, computing, and institutional design. Contributors receive long-term incentives tied to company growth, aligning their interests with downstream data quality and fostering sustained engagement. The platform treats provenance and attestation as first-class concerns, documenting data origin, contributor claims, and permitted use for every asset.
Target Audience
Primary customers are AI labs, enterprise AI teams, research organizations, and product teams requiring expert-built training datasets and recurring evaluations for domain-specific model development.
Features
- Expert network composed of researchers, clinicians, attorneys, engineers, scholars, and practitioners with verifiable credentials
- Custom production process design informed by social science methodology and institutional design principles
- Recurring evaluation programs that move beyond one-off data snapshots, maintaining continuity of context and standards over time
- Long-term incentive structures that provide contributors with equity tied to company value growth, promoting sustained engagement and data stewardship
- Documented provenance and explicit contributor claims regarding data origin, quality, and permitted use
- Personalized intake and review processes without AI-led interviews, ensuring human judgment in contributor selection