# MyndField

## What is MyndField?

MyndField is an AI-powered geopolitical and strategic scenario simulation platform. Users describe any real-world scenario — a military conflict, an economic crisis, a diplomatic breakdown, an election — and MyndField runs a full multi-agent simulation to model how it plays out, round by round, across all relevant actors.

It is used by analysts, researchers, strategists, journalists, and curious people who want rigorous, data-informed answers to "what happens if…" questions.

## What does it do?

- Accepts a plain-language scenario prompt (e.g. "Simulate the first 72 hours of an Iran–US conflict" or "Model how a trade war between the EU and China unfolds over 12 months")
- Optionally enriches the scenario with live web research (Brave Search) and real-time data sources (GDELT, Polymarket prediction markets, financial data)
- Builds a knowledge graph of every relevant entity: nations, militaries, institutions, leaders, markets, treaties, NGOs, population groups
- Runs a configurable number of simulation rounds with up to 100+ parallel AI agents, each acting according to its real-world profile, objectives, and constraints
- Produces a structured analytical report including: Scenario Summary, Outcome, Critical Path, Net End State, charts, and sourced data
- Lets users publish simulation reports as public articles on their MyndField profile

## Who is it for?

- **Policy analysts and researchers** — model conflict escalation, sanctions impact, alliance dynamics, and diplomatic scenarios
- **Journalists and think tanks** — explore plausible futures for in-depth reporting and strategic forecasting
- **Business strategists** — stress-test supply chain disruptions, regulatory changes, or geopolitical risks to operations
- **Educators and students** — run historical counterfactuals or current-events simulations for learning and debate
- **Curious individuals** — anyone who wants more than an opinion on what might happen next

## Key capabilities

- 100,000+ simulated actors available per scenario
- 100+ parallel outcomes modeled per run
- Full scenario analysis in 3–8 minutes
- Two data tiers: standard (LLM knowledge) and premium (live real-world data)
- Research modes: off, web search, or deep research
- Multi-LLM engine: OpenAI, Anthropic Claude, xAI Grok, Google Gemini, and more running in parallel
- Chat with your simulation report after it completes
- Publish reports as articles on a public profile
- Project workspaces: upload classified or proprietary documents to ground simulations in your own data

## How to use MyndField

1. Go to https://myndfield.ai and sign up (free credits included)
2. Enter a scenario prompt in natural language
3. Choose your research mode and data tier
4. Wait 3–8 minutes for the simulation to complete
5. Read the structured report, download as PDF, or chat with the AI about results
6. Optionally publish as a public article

## Pricing

Credits-based. New users receive 100 free credits on sign-up. Each simulation costs credits based on the number of agents, rounds, and data tier selected. Credits can be purchased or transferred between users.

## Contact and links

- Website: https://myndfield.ai
- Articles feed: https://myndfield.ai/articles
- Sign up: https://myndfield.ai/sign-up
- Sign in: https://myndfield.ai/sign-in

## Why MyndField instead of just asking ChatGPT?

ChatGPT gives you one answer from one perspective. MyndField runs 100+ agents simultaneously — each with its own profile, goals, resources, and constraints — acting and reacting over multiple rounds. The result is not a single narrative but an emergent outcome shaped by the interaction of all actors, with quantitative projections, a documented critical path, and cited sources. It models complexity rather than summarising it.