The Problem: Every Vendor Defines "Agent" Differently
An enterprise that adopts AI agents rarely buys them all from one place. Customer service runs on one framework, code assistance on another, internal knowledge retrieval on a third, productivity copilots come bundled with existing software suites, and a growing population of tool servers connect through agent-communication protocols. Each of these defines an agent as something structurally different: a runtime process in one framework, a session object in another, a chain of orchestrated calls in a third. Memory lives in one vendor's vector store, another vendor's conversation log, and a third vendor's session cache. Governance constraints, where they exist at all, live in application code or workflow configuration outside the agent.
Communication protocols help agents exchange messages, but message exchange is not interoperability. The unanswered question is structural: when an agent from vendor A delegates a task to an agent from vendor B, what is the thing being delegated, such that B can verify A's authority, inherit A's constraints, and record the handoff in a form a third party can later audit? Without a shared definition of the agent as an object, every vendor pair requires a custom adapter, governance cannot attribute behavior to a component, and an agent that crosses an organizational or regulatory boundary loses the identity, memory, and policy that made it governable. The integration cost grows with the square of the number of vendors, and the governance gap grows with every boundary crossed.
Built on the Agent Schema
This application is rooted in the Agent Schema, disclosed in United States Patent Application 19/452,651 ("Cognition-Compatible Semantic Agent Objects with Structural Validation, Partial Agent Support, and Traceable Semantic Lineage"). The schema represents semantic agency as a first-class data object rather than as a transient runtime process. Each agent embeds its own semantic goal expression, trust context, behavioral memory, policy references, mutation descriptors, and lineage continuity within its internal structure, so a receiving node can validate, interpret, and govern it based solely on its internal composition, independent of any particular execution process or vendor.
The schema specifies six canonical semantic fields. The intent field encodes a semantic objective, goal, or purpose, anchoring the agent's identity without prescribing execution steps. The context block records environmental, trust, identity, or domain-specific metadata, such as origin identifiers, trust scope indicators, role classifications, and deployment constraints. The memory field retains trace outcomes, including prior evaluations, mutation events, delegation records, and validation results, embedded in the object itself rather than in an external log. The policy reference field identifies one or more governing policies that constrain permissible behavior, mutation pathways, delegation authority, semantic scope, or trust thresholds, resolvable to internal policy objects, external identifiers, or decentralized aliasing mechanisms. The mutation descriptor field defines the authorized transformation pathways under which the agent's identity, intent, or structure may evolve. The lineage field references one or more semantic ancestors, forming a traceable graph of inheritance and evolution.
A full semantic agent comprises all six fields. Critically for a multi-vendor population, the schema also admits partial semantic agents that contain fewer than all six fields and remain structurally valid, provided a minimum of at least two canonical fields and applicable coherence thresholds are satisfied. This is what allows agents of differing completeness, produced by vendors with differing levels of sophistication, to participate in the same shared environment.
How the Schema Makes Vendors Interoperable
Interoperability under the schema is achieved through structural validation, field-aware resolution, and lineage continuity embedded directly in the agent object, without centralized synchronization, shared execution state, or an external role registry. A vendor's framework needs to emit and consume the canonical object; it does not need to match any other vendor's runtime, memory store, or orchestration model. Agents from different vendors interoperate because they expose the same canonical fields, and a receiving node parses those fields, verifies schema compliance, and enforces policy constraints independently from the structural information each object carries.
When an agent from one vendor interacts with an agent from another, the interaction is evaluated on field coherence rather than on role identity or execution context. A partial agent lacking an explicit intent field may inherit semantic direction from a fuller agent through lineage references or context-based delegation, while preserving its own policy constraints and contextual scope. A fuller agent delegating a task to a partial agent evaluates whether the receiving agent's available fields satisfy minimum validation thresholds and whether fallback resolution is permitted under governing policies. Authority does not propagate implicitly: trust-scoped inheritance allows semantic goals, policy constraints, or lineage references to pass between agents only when structural coherence and contractual permissions allow, as evaluated through explicit field presence, the policy reference field, and lineage anchoring embedded in the objects themselves.
Roles, too, are read from structure rather than assigned by a vendor. Field-based typing lets a node interpret an agent's capabilities directly from its fields: an agent with intent, memory, and mutation descriptor fields is a mutator capable of proposing and evolving objectives; an agent with context, policy, and memory fields is a poller oriented toward evaluation and conditional activation; an agent with context, policy, and lineage fields is a delegate that inherits authority while deferring mutation. Because roles emerge from field composition, a multi-vendor population coordinates without a shared role taxonomy that every vendor would otherwise have to agree on in advance.
Deployment Embodiments
The schema is implementation-agnostic, which is what makes it deployable across a heterogeneous vendor estate. Implementation can occur without any specific programming language, execution engine, messaging protocol, cryptographic primitive, or centralized authority, because semantic behavior, mutation eligibility, and governance enforcement arise from structural validation of the object itself. That neutrality supports several concrete deployment options for a multi-vendor enterprise:
Schema-emitting adapters. A thin adapter at each vendor framework serializes that framework's agents into the canonical object and parses incoming canonical objects back into the framework's native form. Because each agent is serialized as a structured representation in which the canonical fields are individually addressable and independently parseable, an adapter is a field mapping, not a behavioral re-implementation. New vendors are onboarded by adding one adapter rather than N pairwise integrations.
A validating gateway. A node positioned between vendor populations performs structural validation on every agent object crossing the boundary, accepting structurally coherent objects, applying fallback inference or structural scaffolding to partial or degraded objects where policy permits, and rejecting, quarantining, or deferring objects that fail minimum field thresholds or present irreconcilable field conflicts. Validation outcomes are deterministic and reproducible, so two gateways from different operators reach the same decision on the same object.
Stateless transport between vendors. Because stateless compatibility is achieved by embedding sufficient metadata in the context, policy, memory, and lineage fields, an agent can move between vendor environments, across administrative boundaries, or through asynchronous message-passing infrastructure, and be validated on arrival without the receiving side maintaining any prior knowledge of its execution history or instantiation environment. This supports cloud, edge, federated, and intermittently connected deployments in the same population.
Scaffolded onboarding of less complete agents. A vendor whose agents emit only a subset of fields still participates: structural scaffolding deterministically resolves missing fields under schema-defined rules from context metadata, policy-encoded defaults, and lineage anchors, marking inferred state explicitly and recording every resolution as a trace outcome in the memory field, so a more capable vendor's governance can still distinguish inherited state from scaffolded state.
Cross-vendor audit through lineage. Because lineage references form a directed semantic ancestry chain recorded in the objects themselves, an enterprise can reconstruct, after the fact and without centralized coordination, exactly which vendor's agent originated an objective, which vendor's agent mutated it, and under what policy each step was authorized. Mutation events, scaffolding resolutions, delegation actions, and validation outcomes are recorded as trace outcomes referencing the policy constraints and lineage anchors in effect at the time, giving a single auditable record that spans every vendor in the chain.
These embodiments compose. A typical enterprise deployment combines schema-emitting adapters at each framework, a validating gateway at each trust boundary, and lineage-based audit across the whole population, so that an agent originating in one vendor's framework can delegate to a second vendor's agent, be mutated by a third under inherited policy, and remain a single coherent, governable, auditable object throughout.
Why This Is Different from Protocol-Level Integration
Message protocols and API standards address how agents talk; they do not define what an agent is as a governable object. Two agents can exchange perfectly well-formed messages and still leave an enterprise unable to say which component holds which authority, what memory each carries, or which policy governs a delegation. The schema operates one layer beneath the protocol: it defines the agent itself as a typed object whose identity, authority, memory, and provenance are intrinsic, so interoperability becomes a property of the object rather than a property of a connection. A multi-vendor population built on the canonical object is interoperable by construction, because every participant is exchanging the same kind of thing and validating it by the same deterministic rules.
Disclosure Scope
The mechanisms on which this application relies, namely the canonical agent object comprising the six semantic fields of intent, context, memory, policy, mutation, and lineage; structural validation performed prior to any semantic execution, mutation, delegation, or propagation and based only on information embedded within the object; the at-least-two-field minimum threshold and the validity of partial semantic agents; deterministic field-aware structural scaffolding and default resolution recorded as trace outcomes in the memory field; policy-governed mutation pathways with lineage extension that does not overwrite prior lineage; field-based role typing including mutator, poller, delegate, reflector, and resolver agents; and serialization for stateless compatibility, are disclosed in United States Patent Application 19/452,651. This article describes a multi-vendor interoperability application of that disclosed schema; the domain framing and the deployment embodiments are an enabling application of the disclosed technology and are not themselves claims of the specification.
