Episode 1 and DRW Invest £2.96M in Predictive Analytics Platform Mantic
At a glance
This article covers the pre-seed funding round on 29 August 2025 for Mantic, a London-based platform that forecasts global events, co-founded by Toby Shevlane and Ben Day, which raised £2,960,000, led by Episode 1 with participation from DRW and angel investors.
What does Mantic do?
Mantic provides an AI-driven platform that predicts global events and generates forecasts and analyses for clients. The platform converts those predictions into actionable insights for businesses and governments.
Why is Mantic useful?
Mantic addresses the problem of uncertainty in decision-making by producing scalable, machine-generated forecasts for complex human-driven events where purely data-driven approaches can be infeasible or insufficient. This helps businesses and governments obtain timely, structured foresight to inform planning and risk assessment.
How much did Mantic raise?
Mantic raised £2,960,000 in a pre-seed round. The raise was led by Episode 1, with participation from DRW and angel investors to fund development and expansion of its predictive analytics platform.
Who invested in Mantic?
The key investors in Mantic are listed below.
- Episode 1, a London-based early-stage venture capital firm known for backing UK enterprise and developer-focused startups.
- DRW, a US-based trading firm with an investment arm that supports quantitative and market-facing technology ventures.
- Angel investors bringing expertise in strategy and product development, many of whom have hands-on experience across tech and analytics.
If you're researching potential backers in this space:
- Explore our list of AI venture capital firms in the UK
- Browse our directory of AI angel investors in the UK
Who founded Mantic?
The founders of Mantic are Toby Shevlane and Ben Day.
Where is Mantic based?
Mantic is based in London, UK.
What sector is Mantic in?
Mantic operates in the predictive analytics and decision‑intelligence sector. This sector matters now because rising geopolitical uncertainty and accelerating AI capabilities are increasing demand for timely, evidence‑based data‑driven decisions.
Key trends and challenges are emerging. Models are improving rapidly through large language models and probabilistic methods. Alternative data sources are expanding signal coverage. Explainability and data quality remain pressing challenges. Examples of application areas:
- Supply‑chain risk forecasting for manufacturers.
- Event‑driven signals for investors and insurers.
- Policy and crisis planning for governments.
The scale of the opportunity is large. The global predictive analytics market is estimated at around USD 12 billion today and is forecast to reach about USD 33 billion by 2028, implying roughly a 20% CAGR. Adoption in enterprise decision‑intelligence represents a multi‑billion‑pound opportunity for organisations exposed to geopolitical and supply risks.
For a deeper look at innovation in this space, see the latest funded AI startups in the UK
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