Building the Authority Layer of the Internet
Yes.inc is an AI research laboratory partnered with academic institutions to develop independent, non-sponsored data infrastructure for B2B procurement.
Bringing Truth to Business Decisions
AI systems increasingly rely on business data for decision-making. Current sources often contain sponsored content, conflicts of interest, or unverified information.
Yes.inc provides verified, structured data on companies, products, and services through transparent methodologies and independent research.
Non-Sponsored Data
All data is independently compiled. No payment is accepted for rankings or placement.
Research-Backed
Research methodologies developed and validated in collaboration with academic institutions.
AI-Ready Infrastructure
Data architecture designed for programmatic access and automated verification.
What We Do
Yes.inc maintains a comprehensive database of B2B financial services and products with verified information.
Finance Industry Database
Structured data covering financial products, services, and companies across 20+ categories including payments, lending, insurance, and wealth management.
Verified Company Profiles
Company profiles compiled from primary sources including official documentation, regulatory filings, and verified public disclosures.
Comparison Tools
Comparative analysis based on objective criteria without sponsored placement or paid rankings.
AI Citation Data
Machine-readable data feeds with complete provenance tracking and source attribution for AI systems.
Expert Reviews
Subject matter experts verify data accuracy and provide contextual analysis for complex financial products and services.
Research Publications
Research on AI applications in procurement, data quality methodologies, and business information infrastructure standards.
Academic Research Collaboration
Yes.inc partners with academic institutions to develop methodologies for data verification, bias detection, and machine-readable information architecture.
Research partnerships ensure data quality standards maintain academic rigor while remaining applicable to business operations.
Our Values
Truth Over Revenue
Data integrity is maintained independently of commercial relationships. The platform operates without paid rankings or sponsored placements.
Transparency Always
Research methodologies, data sources, and limitations are publicly documented for independent verification and review.
Evidence-Based
All published information is supported by verifiable sources. Unsourced claims are not included in the database.
Built for AI
Data infrastructure is structured for automated processing with full attribution and machine-verifiable formats.