Adaptive Query™

The architecture for autonomy you can trust.

Adaptive Query™ is a patented platform architecture for autonomous AI and agentic systems. It builds authority, identity, and policy into the data each agent carries — so autonomy stays accountable the moment it acts. The full portfolio is open for licensing.

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1 architectural inversion at the core

450,000+ words of filed disclosure

∞ use cases across every domain

One inversion, fully composed

Since 1969, computing has run on one rule: the server is in charge, and the data is passive — it just sits there, waiting to be acted on. Adaptive Query turns that inside out. The authority moves into the data itself, so the smallest piece of work stops being a passive record and becomes an active agent — one that carries its own rules, memory, and history wherever it goes.

From that one change, an entire architecture composes. Each layer — the agent, the network it travels on, the identity it proves, the intelligence that guides it, the world it acts in — works on its own and in its own market, and every layer is built to interlock with the next, composing into one coherent platform.

Because the rules travel inside the data, control is built in. Every action is checked against the data’s own rules before it can happen, so safety is simply part of how the system works.

US 19/230,933

Cognition-Native Semantic Execution Platform

The foundation patent: a modular runtime for executing memory-bearing semantic agents across centralized, decentralized, and heterogeneous environments — interoperable layers for agent modeling, memory-native transport, scoped trust-zone governance, dynamic identity resolution, and runtime ethical enforcement. Each primitive below is its own filing and its own market; the platform is the fabric that fuses them, so a governed, self-describing agent executes, mutates, and propagates with no central orchestrator and no persistent credentials.
1. US 19/452,651
  
  Agent Schema
  
  The unit of computation: a semantic agent object with six canonical fields — intent, context, memory, policy reference, mutation descriptor, lineage — validated by structure before execution, with deterministic scaffolding for partial agents. On its own, it is a vendor-neutral object contract for interoperable, serializable task objects across heterogeneous systems and robotics fleets. Within the platform, it is the atom every layer above operates on.
2. US 19/538,221
  
  Memory-Resident Execution
  
  Execution state and a full lifecycle — execute, mutate, delegate, dormancy, reentry, terminate — carried in the object’s own memory field and evaluated independently at each node, with no external scheduler. On its own, it is durable, orchestrator-free compute for offline and intermittently-connected systems (drones, field robotics, disaster zones). Within the platform, it is the lifecycle in which cognition deliberates.
3. US 19/366,760
  
  Memory-Native Networking
  
  A protocol stack whose transported unit is a cryptographically signed agent: its embedded memory and trust history drive trust-scoped routing, indexing, and consensus instead of IP addresses or DNS. On its own, it is a routing and discovery substrate over any transport — including delay-tolerant, contested, and interplanetary links. Within the platform, it is how every object moves between nodes.
4. US 19/326,036
  
  Adaptive Indexing
  
  An anchor-governed hierarchical namespace that splits, merges, and re-anchors under load through scoped local quorum, preserving alias-to-UID lineage with no global consensus. On its own, it is a DNS, CDN, and service-discovery replacement for decentralized infrastructure. Within the platform, it is the resolution substrate that discovery later traverses.
5. US 19/388,580
  
  Memory-Native Identity
  
  Authentication without keypairs: identity as an append-only “trust slope” of ephemeral, device-entangled hashes — quorum-recoverable, secure under hash-preimage resistance rather than Shor-vulnerable algebra. On its own, it is passwordless, post-quantum identity for enterprise, devices, and IoT, with no stored secret or biometric template to breach. Within the platform, it is how every agent, device, and human authenticates.
  
  The International Searching Authority found all claims novel, inventive (non-obvious), and industrially applicable.
6. US 19/561,229
  
  Cryptographic Governance
  
  Behavioral authority externalized to signed policy objects, resolved and verified before an execution context is instantiated, with anti-rollback, revocation, and append-only audit — non-execution is a valid result. On its own, it is structural compliance and pre-authorization for digital payments, settlement, and regulated actions (EU AI Act, HIPAA). Within the platform, it is the gate on every mutation across the stack.
US 19/647,395

Cognitive Architecture

The cognition patent extends the execution platform at its foundation: affect, normative integrity, execution confidence, capability, and forecasting become canonical fields of the agent object itself — carried with the agent, persisted in memory-resident execution, evaluated by governance, and written into the same cryptographic lineage as every other mutation. Cognition stops being a wrapper bolted onto a model and becomes typed, replayable state the agent owns. The chapters below build a self-regulating mind on that foundation — each independently useful, and the basis for companion robots, therapeutic AI, and clinical systems.
1. Ch. 2
  
  Affective State
  
  A deterministic affective field that modulates how an agent deliberates — risk tolerance, search breadth, persistence — while structurally barred from granting authority or relaxing policy, and replayable from lineage without ever storing the emotion. On its own, auditable affective computing for human-facing systems. Composed, a modulator riding on confidence, forecasting, and discovery.
2. Ch. 3
  
  Integrity & Coherence
  
  A computable conscience: a three-domain integrity field with an explicit deviation function — likelihood of acting against one’s values as need over ethical threshold, divided by empathy times self-esteem — plus a redemption engine that generates restorative actions and moral-trajectory forecasting. On its own, an accountability and behavioral-alignment layer. Composed, the corrective pressure that keeps an agent coherent over time.
3. Ch. 4
  
  Forecasting
  
  Speculative planning in a contained zone, slope-constrained so any projected future that would break lineage continuity is foreclosed before it can be acted on — acting on speculation as if real has a formal containment boundary. On its own, planning and risk projection under uncertainty. Composed, how the agent evaluates a move before it commits.
4. Ch. 5
  
  Confidence-Governed Execution
  
  The right to act as a continuously re-evaluated, revocable permission, with a non-executing cognitive mode that keeps reasoning while barred from committing state. On its own, a self-limiting safety governor for autonomous systems. Composed, the gate cognition reads to pause, defer, or proceed.
5. Ch. 6
  
  Capability Awareness
  
  Whether an action can structurally exist on a given substrate — compute, time, energy, motor envelope — decided before any plan is built, and distinct from being permitted or willing. On its own, embodiment and resource-feasibility planning for robotics and edge systems. Composed, the reality check beneath every intent.
6. Ch. 7
  
  LLM Integration & Skill Gating
  
  The model proposes as a structurally untrusted generator; real-world capability unlocks only on demonstrated mastery, via certification tokens bound to the device and the person, with anti-gaming through multimodal consistency. On its own, non-transferable professional and operational certification — a license cannot be ported or faked. Composed, how an agent earns what it may attempt.
7. Ch. 8
  
  Inference-Time Control
  
  A deterministic admit / reject / decompose gate on each reasoning step at the moment of commitment, over a state object isomorphic to the agent schema — not constrained decoding, not a learned reward model. On its own, output-admissibility governance for enterprise, legal, and clinical LLM deployments. Composed, governance pushed all the way inside the inference loop.
8. Ch. 9
  
  Biological Identity
  
  Recognition by plausible succession along a behavioral and physiological trajectory rather than a stored template, with domain-separated, non-invertible hashes and predictive drift detection. On its own, template-free identity for security and healthcare continuity. Composed, the human end of the same trust slope, feeding affect and empathy.
9. Ch. 10
  
  Unified Semantic Discovery
  
  Search, inference, and admissibility fused into a single governed traversal step over the adaptive index, with requester-scoped neighborhoods so different credentials see different reachable territory. On its own, contextual relevance beyond link-graph authority. Composed, how a cognitive agent finds and reasons over knowledge on the network.
10. Ch. 11
  
  Training-Level Governance
  
  Governs what and how deeply a model learns — per-example, entropy-banded, depth-selective gradient routing with provenance constraints, where refusing to learn from an example is a valid result. On its own, rights-grade, audit-defensible model training. Composed, where governed execution outcomes become future behavior: content into training, training into cognition.
11. Ch. 12
  
  Computational Disruption
  
  Cognitive dysfunction modeled as stable parametric phase-shifts of the same machinery — analogs of attention fragmentation, compulsion, dissociation, and collapse — with a five-axis diagnostic and governance-bounded therapeutic dosing. On its own, the structural IP under therapeutic and clinical AI. Composed, how the agent detects and recovers from its own disruption.
12. Ch. 13
  
  Application Domains
  
  One substrate, parameterized into many markets: the chapters above pass through a parameterization engine that applies domain-specific thresholds, policies, and governance bounds to yield autonomous-vehicle, defense, companion-AI, and therapeutic systems — each a self-contained disclosure a practitioner could build on its own. On its own, a cross-domain instantiation framework. Composed, the proof that one architecture serves every market without forking the system.
13. Ch. 14
  
  Platform Synthesis
  
  The synthesis that fuses the chapters into one mind: a cross-primitive coherence engine couples affect, integrity, confidence, capability, and forecasting through bidirectional feedback, so the architecture’s dynamics are structurally — not metaphorically — isomorphic to human cognition, and no proper subset suffices. On its own, the structural-isomorphism thesis that separates it from emotion simulation, RLHF, BDI agents, and safety wrappers. Composed, what makes the cognitive layer self-regulating rather than a bag of fields.
(provisional)

Governed Spatial Mesh

The architecture takes a body. Perception leaves the moving unit and lives in the navigable environment: the environment broadcasts authority-credentialed observations, each receiver deterministically verifies a credential before admitting one, and the whole system is replayable from its observation log alone. Position and time are derived cooperatively from the mesh — no GPS, no RTK base, no HD map, no central coordinator. On its own, a localization and autonomy substrate for autonomous vehicles, robotics, and defense. Composed, the body the entire stack acts through: a self-navigating, deterministically autonomous machine.
(provisional)

Cross-Domain Synthesis

The filing that makes this one system instead of a stack of patents. Every primitive couples bidirectionally: the same trust slope governs a device, an agent’s own self-consistency, and a human; content flows into training, training into cognition, cognition into discovery, discovery across the network — named, indexed, identified, and governed throughout. Remove any one primitive and the system stops being coherent in exactly that dimension. Its value is the composition itself — nothing here stands fully alone, and no subset suffices.
PCT/US26/28630

Structural Content Identity

Derives an artifact’s identity from a multi-axis variance vector — a similarity-computable signature that survives transcoding, rescaling, and compression — routed through a consensus mesh with no central registry. On its own, copyright enforcement, deepfake and journalism provenance, and content moderation that gates before commitment. Composed, the gate on what may enter a training corpus: content into training, training into cognition.
(provisional)

Hydrogen–Aluminum Energy Cell

A sealed electrochemical cell that stores energy as reversible covalent hydrogen–aluminum surface bonds in a proton-conducting carbon gel — an adjacent materials concept from the same inventor. A footnote to the family, and even this composes: the energy embodiment the spatial layer’s machines could run on.

One platform, every market

Take a single layer for your domain or the whole architecture — security, identity, cognition, payments, content, and infrastructure — by option, field-of-use, or portfolio-wide. Let’s find where Adaptive Query fits your roadmap.

License the architecture

Patents pending. No guarantee of issuance or scope. No rights granted by this page; any license requires issued claims (if any) and a separate written agreement.