SAN FRANCISCO, Feb. 2, 2026 /PRNewswire/ — Principle, a Strategic Foresight AI platform that enables companies to simulate competitive futures before committingSAN FRANCISCO, Feb. 2, 2026 /PRNewswire/ — Principle, a Strategic Foresight AI platform that enables companies to simulate competitive futures before committing

Principle Raises $2M to Bring Pentagon Wargaming to Corporate Boardroom Strategy Planning

2026/02/03 00:32
5 min read

SAN FRANCISCO, Feb. 2, 2026 /PRNewswire/ — Principle, a Strategic Foresight AI platform that enables companies to simulate competitive futures before committing resources, today announced $2 million in pre-seed funding. The round was led by SMRK VC and SMOK VC, with participation from RideHome AI Fund, a16z Scout Fund, Bain Capital Scout Fund, and Unpopular Ventures.

Strategic decisions at most companies are made with outdated information, gut instinct, and static planning documents that become obsolete the moment market conditions shift. While oil majors like Shell pioneered sophisticated scenario planning decades ago, this capability has remained locked inside organizations with deep pockets and long time horizons.

“Every Fortune 500 company we talk to has the same pattern,” said Artur Kiulian, co-founder and CEO of Principle. “They misread market signals, they react too slowly to structural shifts, and by the time something obvious in hindsight becomes clear, it’s already too late.”

From Static Strategy to Living Simulations

Principle creates digital twins of companies, competitors, regulators, and market forces, then runs adversarial simulations across hundreds of strategic directions. Unlike generic AI tools that provide stateless answers to one-off questions, Principle maintains persistent models that continuously update as new market intelligence arrives – competitor moves, regulatory changes, pricing shifts, M&A activity.

The platform is already in pilots with multiple Fortune 500 companies, governments, leaders in the energy market, and established technology companies exploring M&A pathways.

“Principle helps us build that muscle: turning strategy into an iterative process where we explore scenarios, learn quickly, and decide based on evidence, not intuition alone.” said Oleksandr Kosovan, CEO & Founder of MacPaw.

Origin: From National AI Models to Strategic Foresight

Principle emerged from work with governments navigating AI adoption. In 2025, the founding team signed an MOU with Ukraine’s Ministry of Digital Transformation to develop national AI capabilities – work that produced collaborative research on sovereign models recognized in the best data journalism picks of 2025. That engagement expanded to the Middle East: benchmarking AI models with Doha Graduate Studies University as part of Qatar’s sovereign AI initiative, and collaborating with Dubai Health Authority on population health strategy.

A consistent gap emerged: organizations could deploy powerful AI models, but struggled to translate them into strategic decisions.

“Governments and enterprises would invest heavily in AI infrastructure, then face a utilization problem,” said Kiulian. “That’s when we realized the real opportunity wasn’t building more AI — it was building the decision layer on top of it.”

Working alongside Dubai Centre for Artificial Intelligence (DCAI) and Dubai Future Foundation, Principle developed scenario modeling for health system resilience.

“The future belongs to those who ask the most important questions,” said Khalfan Juma Belhoul, CEO of Dubai Future Foundation.

LLMs as World Models

Recent advances in large language models have unlocked a new capability: the ability to simulate not just environments, but the logic of how markets, competitors, and organizations actually behave. Principle’s founding team – with backgrounds spanning Google’s behavioral simulation research, physics modeling at CERN, and strategic technology work for the White House – recognized that LLMs could finally make strategic foresight scalable.

“Every major platform shift creates new primitives for human interaction,” said Chris Messina, General Partner at Ride Home AI Fund and inventor of the hashtag. “The common objection we hear is ‘I can just use ChatGPT for this,'” said Kiulian. “But a generic LLM is stateless — no memory of your company, no persistent model of your competitors. We’re running continuous simulation engines that learn from outcomes.”

Principle has already begun building on this foundation, training a custom model on AWS’s Nova architecture to improve plausibility classification of future market events – joining early adopters like Reddit, Sony, and Booking.com in building domain-specific “Nova” models that embed deep vertical expertise.

Built for the Enterprise Blindspot

The company is initially targeting mid-market and Fortune 500 corporate strategy teams – organizations large enough to face complex competitive dynamics but lacking the resources to build in-house foresight capabilities. 

“Enterprise AI has optimized individual productivity — coding assistants, document drafting. Palantir helps companies make their internal data work again. What’s missing is the layer that shapes where the business actually goes. We adopted military wargaming techniques and applied them to corporate strategy,” said Yurii Filipchuk, co-founder of Principle.

Use of Funds

The funding will accelerate Principle’s transition from high-touch pilot delivery to a productized platform, with investment in the simulation core, real-time market intelligence integration, and an interface that allows strategy operators to interact with scenarios directly. The company is also expanding its enterprise pilot program, targeting additional Fortune 500 customers across industrial, technology, and financial services verticals.

About Principle

Principle is the Strategic Foresight Simulation platform that helps companies model competitive futures before committing resources. Founded in 2024 and headquartered in San Francisco. Users can learn more at futureprinciple.com

Contact
Yurii Filipchuk
Principle
yf@openbabylon.com

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SOURCE Principle

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