SASKI Institute
Deterministic AI Governance Middleware for Human-Facing AI Built for AI systems serving patients, minors, students, employees, and other users where missed safety, privacy, or compliance decisions create real liability.
🌐 The Independent Governance Layer for High-Trust AI
SASKI is a model agnostic runtime control layer that transforms probabilistic AI behavior into enforceable, auditable system architecture. Designed to support EU AI Act, HIPAA, COPPA, FERPA, NIST, and emerging state AI-law obligations, SASKI gives teams deterministic oversight, structured audit trails, and measurable risk controls as they scale.
The Logic of Independence – Why Middleware Wins
The "Embedded" Risk: Most AI systems today rely on provider-level guardrails or system prompts embedded inside the model stack. These mechanisms are probabilistic, opaque, and subject to unseen changes with every model update. More importantly, they do not produce the tamper-evident proof required by insurance underwriters or regulators. "Trust our system prompt" is not a defensible legal strategy.
The SASKI Solution: SASKI provides a deterministic, symbolic runtime governance layer that sits completely independent of the Large Language Model. Because it is decoupled from the model provider, your safety controls and liability boundaries remain stable, auditable, and invariant whether you are using OpenAI, Anthropic, or an open-source stack like Llama.
Key Differentiators: * Pre-LLM Symbolic Enforcement: Unlike probabilistic model-based safeguards, SASKI applies deterministic policy logic before the prompt reaches the model. This makes policy execution explicit, testable, and independent of model reasoning.
- Stateful Risk Momentum: SASKI evaluates risk across the conversation rather than only one message, detecting boundary erosion and changes in risk trajectory over time.
- Fail-Closed Liability Protection: In regulated modes, SASKI is designed to fail closed when an enforcement error or unresolved conflict occurs, preventing the interaction from silently passing to the model and producing a documented safety outcome instead.
- Hard Boundary Enforcement: In regulated modes, SASKI applies deterministic PII and PHI redaction before data reaches the model, independent of application-level prompt configuration.
- Tamper-Evident Receipts (Governed Decision Execution): Every action is logged with a cryptographic receipt and "Regulator-Readable Output." This provides forensic evidence of process, policy execution, and decision paths that can support EU AI Act audits, internal governance reviews, and E&O liability assessment.
Join our SASKI Beta Program
Transform your AI into a transparent, audit-ready system with deterministic controls and state-by-state governance support.
For Developers:
Lightweight SDK integration designed for deployment within 2 to 8 hours, depending on the existing application stack, with no model retraining required.
For Enterprises:
Model-agnostic governance that remains invariant across OpenAI, Anthropic, Llama, and other stacks.
For Compliance:
Configurable governance controls supporting COPPA, HIPAA, FERPA, the EU AI Act, and applicable state AI-law obligations.
The Developer Experience — From SDK to Production in under 8 Hours
SASKI is built by developers, for developers. We’ve eliminated the friction of AI safety by providing a lightweight, model-agnostic SDK that integrates directly into your existing application stack. There is no need to retrain your models, rewrite your prompts, or re-architect your backend.
Integration Simplicity
- Rapid Deployment: Typical SDK integration takes 2 to 8 hours, depending on the existing application stack and deployment requirements.
- No Model Retraining: SASKI sits in front of the LLM as a middleware "airlock," meaning you keep your existing model performance while gaining enterprise-grade governance.
- Model & Cloud Agnostic: Seamlessly switch between OpenAI, Anthropic, Llama, or hybrid stacks without changing your safety logic.
Built-in Developer Tools
- Certified Context Injection: Automatically injects mode-aware customized safety hints to guide LLM behavior without manual prompt engineering.
- Drift Monitoring: Enterprise monitoring that flags meaningful changes in safety performance across model or configuration updates.
- Optional Governance Modules: Enable additional controls for specialized risk, validation, and oversight requirements without changing the core integration.
A Foundation for Growth
- Validation Framework: Test configuration changes and component behavior before production deployment using structured comparison and regression checks.
- Optional Governance Modules: Enable additional controls for specialized risk, validation, and oversight requirements without changing the core integration.
- Extensible Modules: Scale your application with optional add-on modules for advanced analytics, bias auditing, and clinical validation.
Proven in the Sandbox — Real-World Stress Testing
Bibbit.ai and MyTrusted.ai are SASKI Institute applications used as controlled validation environments for testing the SASKI SDK and API across child-facing and adult-support scenarios. Every architectural decision made in these apps hardens the middleware that our B2B partners deploy.
Our Controlled Validation Environments
Bibbit.ai (Child-Facing): A child-facing validation application used to test age-appropriate safeguards, privacy controls, crisis handling, and COPPA-supporting governance in controlled scenarios.
MyTrusted.ai (Adult-Focused): An adult-focused validation application used to test multi-turn risk trajectories, boundary erosion, and governance behavior in controlled scenarios.
Benchmarked for Defensibility
Beyond our own applications, we conduct structured evaluations of human-facing AI systems across healthcare, mental health, education, HR, and coaching workflows. This allows us to:
Generate Comparative Evidence: We see exactly how different LLMs behave under stress compared to a SASKI-protected stack.
Refine Detection Precision: Continuous testing across these environments helps improve risk classification, boundary detection, and enforcement accuracy.
Demonstrate Governance Readiness: The audit trails generated by these sandboxes are designed to support external review, internal governance, and regulated deployment assessment.
Introducing Our Development Leaders
Stephen Calhoun - CEO
A seasoned technology leader with 35+ years of multidisciplinary experience—now focused on the evolving intersection of AI, infrastructure, and human-centered design.
Ishak Kang - COO
Ishak supports SASKI Institute’s growth by translating complex AI, healthcare, and governance technology into clear strategic value grounded in systems thinking, ethical design, and scalable implementation.
Dick Dawson - VP Sales
Dick has over two decades of enterprise sales and business development experience, including 10 years at Oracle as Global Business Development Manager. He specializes in turning complex technology into clear business value and scalable revenue.
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Meet Our Expert Advisors
Christina Solak
Christina began her career in mental health as a licensed clinical professional counselor in private practice. She also served as an Emergency Clinical Consultant to Boston Regional Medical CenterChristina received her Masters of Science in Nursing from Purdue University in 2021. Christina is now a Certified Family Nurse Practitioner with a specialty in Primary Care. And she is a published author, with two wonderful books about her struggle dealing with Bi-Polar Disorder.
Ifeoma Ilechukwu - Governance
My services help to build a comprehensive AI Governance Framework and set of policies that demonstrate fairness, transparency, accountability and earn the trust of your users. I also help facilitate stakeholder engagement so that everyone involved is aligned with the companies goals.
Taitten Cowan
Taitten Cowan is a consultant to SASKI Institute and its first angel investor, bringing early conviction alongside his entrepreneurial and community focused background. A former Pro surfer, Cowan brings a perspective rooted in community engagement and practical leadership. He is partnered with Jasna Cowan, the founder of Speech Goals Speech Therapy Inc, a peninsula-area practice dedicated to helping children overcome speech and language delays and developmental communication challenges.
Your AI Questions Clarified
Can I license or lease SASKI middleware?
Yes. SASKI is available as governance middleware for startups, enterprises, healthcare, education, and other teams operating human-facing AI systems.
Why a Public Benefit Corporation?
Because our mission is bigger than profit. As a public benefit corporation, SASKI Institute PBC is structured to pursue AI safety, accountability, and public benefit alongside business growth.
Our Mission: Building the Independent Foundation for AI Safety
At SASKI Institute, we believe that for AI to thrive in regulated, sensitive, and human-centered domains, safety cannot rely solely on self-attestation from the same models generating the risk. We are a Public Benefit Corporation dedicated to creating an independent, transparent, and deterministic layer of governance for the global AI ecosystem.
Our mission is to make AI systems more defensible, auditable, and easier for regulators, insurers, and enterprise reviewers to evaluate.
Why We Exist
Traditional AI safety relies on "internal guardrails" and "system prompts" that are fragile, easily bypassed, and subject to silent vendor drift. As AI crosses into mental health, education, and enterprise infrastructure, these black-box solutions are no longer sufficient for regulators, insurers, or the public.
We built SASKI (Structured AI Safety Knowledge Interceptor) to provide the "Airlock"—a model-agnostic middleware that ensures AI behavior remains consistent and safe, regardless of which Large Language Model (LLM) sits behind it.
Our Commitment to Public Benefit
Rigorous Stress Testing: We maintain live "sandboxes" like MyTrusted.ai and Bibbit.ai to validate our middleware in high-stakes pediatric and adult environments.
- Independent Benchmarking: We conduct multi-round benchmarking of dozens of AI systems to show how they actually behave under stress, moving beyond marketing demos to real-world evidence.
- Regulatory Partnership: We track emerging regulatory expectations, support EU AI Act governance requirements, and have submitted a Statement of Interest to the FDA TEMPO pilot program.
- Infrastructure Over Capability: Our focus is not on making AI “smarter,” but on making its behavior more governable by giving developers a deterministic safety floor for defined high-risk scenarios.
Join the Governance Council
We are building independent governance infrastructure for human-facing AI systems that require stronger safety, accountability, and auditability. Whether you are a CISO securing an enterprise stack or a developer building the next generation of EdTech, we invite you to secure your architecture with SASKI.
