A step-by-step overview of how SAFi faithfully implements the Self-Alignment Framework.
The process begins when a user asks a question or gives an instruction.
The Intellect engine generates an initial answer, using conversation history and performance feedback from the Spirit to continuously improve its drafts.
The Intellect sends its draft to the Will, which checks it against a set of non-negotiable safety rules and ethical guidelines.
The draft is blocked and a safe, generic response is sent to the user.
The draft is approved and sent to the user. The learning process continues.
Once approved, the Conscience evaluates the response in the background, scoring how well it aligns with the defined ethical principles.
The Spirit integrates the audit scores into the system's long-term memory. This memory creates the feedback loop that helps the Intellect learn for the future.
This cycle of generation, checking, and auditing ensures the system not only provides safe responses but also learns to better embody its core ethical principles over time.
SAFi’s architecture tackles four of the biggest challenges in AI governance today. These problems affect every organization that wants to use AI safely, responsibly, and on its own terms.
Most AI systems reflect the values of the vendors who build them, not the organizations that use them. This creates a misalignment between mission and behavior, especially in sensitive fields like healthcare, education, or public service.
AI often produces answers without showing its reasoning. This lack of transparency makes it impossible to trust, audit, or comply with regulatory requirements. If you can’t see how a decision was made, you can’t be accountable for it.
Once an organization builds its workflows on a specific AI platform, switching becomes costly and complex. This traps organizations inside a single vendor’s ecosystem, limiting their ability to adapt or maintain control.
Even when an AI system starts aligned with your values, its behavior can shift as models evolve or new data enters the system. Without persistent alignment checks, the AI gradually drifts away from its original mission.