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§ Private Profile · Auckland, New Zealand
PredictHQ is a technology company.
PredictHQ transforms the complexity of global events into accurate demand intelligence your models are missing. Making AI smarter, forecasts sharper, and operations more dynamic.
PredictHQ has raised $32.0M across 2 funding rounds.
PredictHQ has raised $32.0M in total across 2 funding rounds.
PredictHQ has raised $32.0M across 2 funding rounds. Most recently, it raised $22.0M Series B in February 2020.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Feb 1, 2020 | $22M Series B | Brian Blond | Acrew Capital, Sequoia Capital, AddVenture, Theresia Gouw, Lightspeed Venture Partners, Rampersand | Announced |
| Nov 1, 2018 | $10M Series A | Theresia Gouw | Acrew Capital, Sequoia Capital, Jason Wang, AddVenture, Arif Janmohamed, Rampersand | Announced |
PredictHQ has raised $32.0M in total across 2 funding rounds.
PredictHQ's investors include Brian Blond, Acrew Capital, Sequoia Capital, AddVenture, Theresia Gouw, Lightspeed Venture Partners, Rampersand, Jason Wang, Arif Janmohamed.
PredictHQ is a technology company that builds a global demand intelligence platform powered by AI to forecast how real-world events impact business demand.[1][2][5] It serves industries including retail, hospitality, transportation, aviation, accommodation, consumer packaged goods, leisure, travel & tourism, parking, quick service restaurants, and delivery, helping them solve demand volatility caused by events like sports, concerts, holidays, weather, and politics.[2][3][5] The platform provides enriched event data—covering 19 categories with predictions on attendance, spend, geographic impact, and rankings—via APIs for use cases like demand forecasting, dynamic pricing, inventory management, staffing, marketing, and supply chain optimization, delivering at least 10% improvements in forecast accuracy.[3][5][7]
Founded in 2015 and headquartered in Auckland, New Zealand, PredictHQ pioneered predictive demand intelligence by addressing the blind spot of event-driven demand fluctuations.[2][5] While specific founders are not detailed in available sources, the company emerged from recognizing that traditional demand planning ignored external events, leading to billions in losses from supply chain issues and inefficiencies.[1][5] Early traction came from aggregating data from hundreds of public and proprietary sources, building 8+ years of historical data plus 2 years forward-looking, and developing over 1,000 machine learning models for precise predictions.[5][7] Pivotal moments include launching tools like the Events API, Features API, and Beam relevancy engine, which correlates user demand data with events for customized insights.[3][6]
PredictHQ stands out through its unique event data enrichment and AI-driven predictions, enabling businesses to go beyond event listings to quantify "why" events matter:
PredictHQ rides the AI-powered demand planning trend, integrating real-world event data as a critical input for next-generation ML models amid rising demand volatility from climate events, geopolitical shifts, and post-pandemic recovery.[1][5] Timing is ideal as businesses face supply chain disruptions costing billions, with PredictHQ's 1,000+ models and forward-looking data enabling predictive analytics in a market shifting toward event-aware forecasting.[5][7] Favorable forces include growth in sectors like travel, retail, and delivery—boosted by e-commerce and experiential leisure—plus API ecosystems for seamless BI and SCM integration.[2][3] It influences the ecosystem by partnering with platforms like Kinaxis for inventory optimization and Snowflake for scalable data processing, empowering data science teams to build more accurate, context-rich AI while reducing blind spots in traditional models.[1][8]
PredictHQ is positioned for expansion as event intelligence becomes table stakes for AI-driven operations, with potential to deepen enterprise adoption through advanced features like multi-location Beam analysis and custom ML feature building.[5][6] Trends like real-time weather integration, privacy-safe marketing data, and generative AI for scenario planning will shape its trajectory, amplifying impact in high-volatility sectors.[3][5] Its influence may evolve toward becoming the de facto event layer in global supply chains, unlocking billions in efficiency as businesses master predictability in an unpredictable world—echoing its core mission to turn event chaos into actionable foresight.[1][5]