USE CASE
Develop AI Models
Accelerate innovation with synthetic data and live-fire simulations that make your AI models smarter, faster, and more predictive.
SimSpace’s Training Solution gives AI developers access to dynamic, production-grade environments—complete with emulated users, threats, and telemetry—to build and refine models that perform under real-world conditions.
Train Smarter AI, Not Just Faster Models
AI-driven defense only works when algorithms understand how real adversaries behave. Yet most models are trained on narrow, sanitized datasets that fail to capture the complexity of live networks.
SimSpace bridges that gap with synthetic data generated from realistic, full-scale environments. Your models don’t just learn from generic activity—they evolve through exposure to authentic attack patterns, system behaviors, and user interactions that mirror live conditions.
Overcome the Obstacles Slowing AI Progress
ACCELERATE ROI
Problem: AI models take too long to train due to limited real-world data.
Solution: Synthetic data accelerates AI model development, shortening time-to-value and deployment. SimSpace enables developers to generate rich, varied datasets in days, not months.
Optimize Performance
Problem: Models trained on narrow datasets underperform in the wild.
Solution: Exposure to diverse, emulated threats strengthens predictive accuracy and adaptability. Models learn from evolving adversary behaviors to make sharper, faster decisions.
Consolidate Cyber Spend
Problem: Data collection, labeling, and tooling costs spiral quickly.
Solution: Synthetic data reduces reliance on expensive manual pipelines, lowering the total cost of AI training while improving model reliability.
Why AI Builders Trust SimSpace
SimSpace provides the world’s most realistic cyber range for developing and validating AI defense models.
Generate Realistic Data With Real Threat Context
Teams can emulate production-like networks filled with diverse user and attacker activity, producing clean, labeled synthetic datasets that fuel advanced model training. This realism ensures AI agents learn from the same telemetry defenders rely on every day.
Continuously Test, Benchmark, and Adapt
Developers can run evolving attack simulations to continuously test AI performance, benchmark predictive accuracy, and refine training data. Models face live-fire conditions that expose weaknesses early—before deployment ever reaches production.
Validate Resilience Before Real-World Use
Every AI workflow can be validated under novel, unpredictable scenarios to measure how it handles real operational stress. Built-in feedback loops ensure each model adapts over time, keeping pace with the threat landscape and strengthening trust in AI-driven defense.