Interactive Docent Agent

A context-aware AI guide that helps you navigate, interpret, and learn from complex synthetic environments.

Tracks your position and actions within the simulation, offering proactive support and suggestions based on what's unfolding.

Transforms complex agent interactions and system behaviors into digestible summaries, so you understand not just what happened, but why.

Allows you to ask "what if?" questions and receive dynamic feedback, enabling structured exploration of edge cases, counterfactuals, or unintended consequences.

How it works

The docent observes agent behaviors, system state, and your interactions in real time. It applies contextual reasoning and memory to surface insights, suggest next steps, and help you extract value from high-dimensional simulations.

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Setting up this feature

Your docent is your first step, helping you create the requirements that bound your simulation space. It will begin collaborating immediately, offering guidance, surfacing questions, or stepping back as you explore independently.

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Scaling with this feature

As your simulations grow in complexity, the docent evolves too. It learns from past runs, adapts to new domains, and becomes a personalized research partner. Whether you're prototyping or stress testing enterprise-grade systems, the docent scales its guidance to match your needs.

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Interactive Docent Agent

Scenario-Aware Guidance

Interpretability & Insight Surfacing

Hypothesis Testing & Exploration Support

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High-fidelity simulations

Create risk-free, realistic environments that mirror complex real-world systems without exposing sensitive data

Answers

to your top questions

What do you do with my data?

At Simthetic, we're built on the principle that your data and IP are always yours.

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.

Is this secure for enterprise use?

Yes. Simthetic is designed from the ground up for enterprise-grade security, privacy, and compliance.

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.

Can I integrate Simthetic into my current workflow?

Yes. Simthetic is designed to be integration-friendly and developer-accessible, whether you're running experiments in notebooks or deploying in enterprise pipelines.

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.

How are Simthetic's agents different?

Simthetic's agents aren't just text generators: they're contextual, goal-driven, and grounded in structured environments.

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.