FutureSearch builds AI-powered forecasting infrastructure that goes beyond raw probability estimates to produce transparent, reason-backed predictions. Founded in 2023 by Dan Schwarz (ex-Google, ex-Waymo, former CTO of Metaculus) and Lawrence Phillips (former head of Metaculus' AI team), the company runs autonomous AI researchers and forecasters over tabular data to deliver ranking, classification, research, deduplication, and forecasting at scale. Their platform emphasizes legible facts, adversarial reasoning, and quantitative models rather than opaque numerical outputs, and serves enterprise clients including Amazon, OpenAI, Google, xAI, and Anthropic.
Funding Details
- Annual Budget
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- Monthly Burn Rate
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- Current Runway
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- Funding Goal
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- Funding Raised to Date
- $6,175,000
- Fiscal Sponsor
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Theory of Change
FutureSearch believes that improving the quality and transparency of forecasting about AI and other consequential events is a direct lever for better decision-making by policymakers, researchers, and funders. By building AI systems that produce not just numerical probability estimates but structured, inspectable reasoning — including cited facts, adversarial argument resolution, and quantitative models — they aim to raise the epistemic quality of forecasts on high-stakes questions like AI timelines and existential risks. Their theory holds that accurate, legible forecasts reduce uncertainty for decision-makers, improve resource allocation in AI safety and policy, and create a public epistemic infrastructure that benefits the broader field. Demonstrating that AI forecasters can outperform humans on important questions also advances the case for using AI as a tool to navigate transformative AI development.
Grants Received
from Open Philanthropy
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Details
- Last Updated
- Apr 2, 2026, 9:52 PM UTC
- Created
- Mar 20, 2026, 2:34 AM UTC