We avoid evaluating irrelevant factors that don't relate to a tenant's ability to pay rent, reducing discrimination risks in our automated process.

We're developing a tool that identifies common patterns in conversations without human input, allowing us to analyze these clusters.

We do not change prices based on individual customers; instead, we cluster customers to apply different pricing strategies.

We utilize proprietary models and APIs to generate insights, allowing us to scale our services and provide timely information to clients during meetings.

We need to be very clear and upfront about anything we do regarding user interactions and data.

To verify user ages, we primarily rely on age gating during sign-up and also check the age against the content they post, while balancing privacy concerns.

We are localizing data in a way that no other company has done, ensuring American data is stored securely and overseen by American personnel.

It's crucial to analyze quantitative data, like user logs and retention curves, to understand how your product is actually being used, rather than relying solely on user feedback.

We focus on delivering a strong financial model and rigorous analysis to ensure our customer acquisition costs and lifetime values are accurate.