Continuity
Maintains a coherent internal state across time.
The Relational Systems Processor
What does it mean to be an entity?
AI can generate remarkably good responses. Can it make use of what it experiences?
RSP is a patent-pending architecture for persistent internal state, emotional continuity, and coherent behavior across interaction.
Demonstration password: Heart
The Relational Systems Processor creates and maintains an ongoing emotional state from experience, and expresses that state when circumstances and boundaries warrant expression.
Why AI needs internal state
Most AI systems do not fail to understand because they lack intelligence. They fail because they cannot maintain a coherent internal understanding of what is happening as an interaction unfolds.
Ever had your AI caution you against jumping to conclusions — because it jumped to that conclusion?
They process inputs, reconstruct context, and generate outputs. But they do not maintain a continuous internal condition that evolves with experience. That is why systems can miss intent when wording changes, fail to register urgency, or respond correctly at the sentence level while still feeling subtly disconnected from the larger situation.
The words are processed. But the situation often is not.
Someone says, “Fine.”
After a warm, easy interaction, it can mean one thing. After an hour of growing frustration, the same word can mean something totally different.
The words are the same. But what came before changes what they mean.
Understanding the present situation requires the effects of prior experience to carry forward.
RSP is designed to provide that continuity.
Understanding Should Recover Naturally
A healthy human relationship is not defined by the absence of misunderstanding. It is defined by how naturally understanding returns.
When two people are well attuned, they usually understand each other within the context of everything they already know about one another. RSP is designed to provide the same kind of continuity.
But even well-attuned people sometimes misunderstand each other.
One person simply says,
"That's not what I meant."
Little or no further explanation is required.
The other person quickly recovers their understanding because the relationship already provides the necessary context.
Today's AI often requires the user to explain the misunderstanding in detail. The conversation starts over.
RSP proposes something different.
Understanding should recover naturally.
This becomes possible because the architecture continuously reorganizes itself in response to experience. New information changes the system's internal state, so future responses emerge from an understanding that has already incorporated what was learned.
The goal is not to eliminate misunderstanding. The goal is to maintain a high level of understanding over time, and when misunderstanding does occur, to recover as naturally as would happen in a healthy human relationship.
What RSP changes
Humans do not move through the world as a series of disconnected moments. We carry an ongoing internal condition shaped by satisfaction or depletion, safety or threat, and by our relationships with other people.
That condition influences what we notice, how we interpret situations, what feels important, and how we respond across time — even when little or nothing is outwardly expressed.
RSP applies this organizational principle to artificial systems. It is designed to operate alongside modern AI, providing an internal regulatory layer that integrates incoming signals, carries their effects forward, and shapes subsequent interpretation and response.
Understanding
Develops an internal understanding of people, context, and emotion as interactions evolve.
Built-in interpretability
Behavioral changes can be traced to observable changes in structured state.
Alignment
RSP provides alignment through persistent, human-centered internal organization.
Adaptation
Adjusts to new experience while preserving coherent internal organization.
Trustworthy interaction
Behaves consistently enough to earn trust over time.
From perceived signals to a developing entity
Sensor analytics are mapped into three domains of human regulation. Together, these dimensions organize the emotional and motivational pressures that shape how people perceive, interpret, and respond to the world.
S
Sustenance
Needs from hunger and uncertainty to comfort, stability, and satisfaction.
Sustenance
Needs from hunger and uncertainty to comfort, stability, and satisfaction.
P
Self-Protection
Safety, vulnerability, confidence, and fight-or-flight responses to perceived threat.
Self-Protection
Safety, vulnerability, confidence, and fight-or-flight responses to perceived threat.
R
Relatedness
Rejection, loneliness, independence, belonging, closeness, responsibility, and trust.
Relatedness
Rejection, loneliness, independence, belonging, closeness, responsibility, and trust.
The interactive demonstration shows how these dimensions become a persistent internal state whose effects are carried forward, influencing what the system notices, how it interprets what follows, and how it responds.
The objective is not to make machines conscious or emotional in the human sense. It is to create coherent emotional regulation: continuous internal organization across time, with expression governed by context and boundaries.
Explore the project
See the theory in operation.
About Daniel A. Bochner, Ph.D.
I am a clinical psychologist, author, and AI architecture researcher whose work focuses on how intelligent systems maintain coherent internal organization across time.
I developed the Relational Systems Model (RSM) and its computational embodiment, the Relational Systems Processor (RSP) — a patent-pending architecture that introduces persistent internal state, emotional continuity, and behavioral coherence to AI systems.
Foundational work
Recognition for Dr. Bochner's Foundational Theoretical Work
Dr. Bochner's theoretical work has been recognized by leading figures in psychology and psychotherapy for its originality, integrative thinking, and contribution to the field.
“Dr. Bochner has developed a relatively seamless integration of the interpersonal with the intrapsychic... a dazzlingly brilliant book... a comprehensive model that ingeniously synthesizes the best that one-person and two-person psychologies have to offer... This is truly an extraordinary book — at once inspired and inspiring.”
Faculty, Boston Psychoanalytic Institute and Massachusetts Institute for Psychoanalysis
“An ambitious integration of psychoanalysis and family systems theory... an inventive, scholarly, clear, and beautifully constructed invitation to therapists... a much-needed addition to the literature.”
Co-Director, International Institute of Object Relations Therapy
“A significant advance in the movement to integrate psychoanalytic thinking into family therapy.”
Founder of Internal Family Systems (IFS)
Books
The Therapist’s Use of Self in Family Therapy
2001
Introduced the original Relational Systems Model (RSM), demonstrating how integrating psychoanalytic and family systems theories can deepen therapeutic understanding and intervention.
The Emotional Toolbox
2011
A practical self-help guide describing common psychological disorders, relationship challenges, and strategies for improving emotional well-being.
RSP grows directly from the theoretical foundation established in the Relational Systems Model, translating decades of psychological research into a structured computational framework.
I welcome conversations with researchers, AI companies, robotics teams, interface designers, and investors interested in persistent internal state, emotionally intelligent interaction, and human-centered AI.
U.S.
Patent Pending
Patent Pending
Founder
EntityAI LLC
EntityAI LLC
Originator
RSM & RSP
RSM & RSP
Contact
Daniel A. Bochner, Ph.D.
Email: dan@entityai.xyz
Website: entityai.xyz