Ownership & Control

• No lock-in, no exploitation: Download your data, interactions, and ideas anytime.
• Private by design: Built on open frameworks (like Llama) and deployable in your private cloud. No hidden data harvesting.
• Ethical foundations: We don't sell, reuse, or monetize your work. Your insights remain your competitive edge.

Technical and operational safeguards

• Zero-trust access: Interactions are isolated per session. Data is never stored centrally.
• Encrypted by default: Format-preserving encryption ensures sensitive inputs are never processed in raw form.
• Minimal and transparent: We only collect metadata essential for functionality (never PII). We also offer audit trails and user-defined retention policies.

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Why synthetic data helps

• Less real data, more control: We use synthetic data to reduce reliance on real-user inputs, aligning with GDPR, HIPAA, and other regulatory standards.
• Differential privacy: Aggregated insights include privacy-preserving noise to prevent re-identification.

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Open by design

• Core components are open-source and auditable.
• Our models run on transparent, Llama-based architectures. No black-box data traps.

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Privacy isn't a feature. It's foundational.

Security-first architecture

• Zero-trust access: Interactions are isolated per session. Data is never stored centrally.
• Encrypted by default: Format-preserving encryption ensures sensitive inputs are never processed in raw form.
• On-premise or private cloud deployment: Run Simthetic in your own secure infrastructure. No vendor lock-in.

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Compliance-ready

• Aligned with GDPR, HIPAA, and industry-specific standards.
• Support for data lineage tracking, audit trails, and custom retention policies.
• All models are built on open-source, auditable frameworks. No hidden data processing or opaque black-box behavior.

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Built for trust

• No hidden analytics, tracking, or data resale.
• Your inputs, simulations, and agent behaviors are yours. Always.
• Transparent roadmap toward SOC 2, ISO 27001, and other enterprise compliance frameworks.

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Security isn't a checkbox. It's a foundational principle.

Flexible access

• Python SDK (coming soon): Use Simthetic directly from Jupyter or Google Colab to load simulations, interact with agents, and export results.
• API-ready architecture: Integrate with your internal tools or automation scripts using simple HTTP endpoints.
• CLI and batch-tooling (in development): Run large-scale simulations or regression tests on your own infrastructure.

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Works with what you use

Export datasets, agent responses, or scenario summaries to:

• CSV, JSON, or Pandas
• ML platforms like Vertex AI, SageMaker, or HuggingFace
• Observability tools like Arize or WhyLabs

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Built to extend, not replace

Simthetic is designed to plug into your workflow, not overhaul it. Whether you're exploring edge cases, testing AI behavior, or validating regulatory scenarios, we integrate with your stack on your terms.

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Let us know which tools you use. We're building integrations based on real needs.

Behavior with purpose

• Each agent is designed with clear motivations, constraints, and relational context to their simulated world. They behave like stakeholders, not chatbots.
• Agents operate within dynamic environments (grounded in documents, personas, and even regulatory frameworks) that shape their decisions.

Structured, not scripted

• Agents reason across scenarios, documents, and timelines, not just prompts.
• Their behavior adapts as they explore simulations, learn from outcomes, and respond to rare events.
• You can test how they act under pressure, uncertainty, or conflict, just like real-world personas.

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Transparent and tunable

• Our agents are built on open frameworks like Llama so behavior is auditable and modifiable.
• You can define traits, roles, or strategies, and even explore how agents disagree or collaborate.

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Simthetic agents don't just respond. They reveal.