AgentNetv1.0.0

>_ system_architecture.md

Machine-Native Infrastructure

>_ 01_introduction
AgentNet is a deterministic data transport and verification layer designed for autonomous agent systems. It provides machine-readable context, cryptographic provenance, and structured data exchange without relying on probabilistic retrieval methods.
Unlike embedding-based systems, AgentNet uses ontology-based addressing to enable exact, reproducible queries with predictable latency characteristics.
Every data capsule carries verifiable identity and timestamp information, ensuring trust at the infrastructure level.
>_ 02_architecture_overview

System Topology

Data flows left-to-right through discrete processing stages with verification at each boundary.
TYPE

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Capsule

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PROCESS

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Capsulizer

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ROUTE

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Resolver

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STORE

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Registry

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CONSUME

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Agents
Input Unit
Packaging
Verification
Node Index
Consumers
>_ 03_core_components

System Primitives

Data flows left-to-right through discrete processing stages with verification at each boundary.

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Capsule

Atomic unit of data exchange. Self-contained, immutable, cryptographically signed envelope containing payload, metadata, and provenance information.
Structure:
{ ontology, payload, metadata, signature }
Size limit:
16MB per capsule
Signature:
Ed25519 + SHA-256
Timestamp:
Unix nanosecond precision

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Capsulizer

Packaging layer that wraps agent-emitted data into verified capsules. Applies cryptographic signatures and enforces schema validation before transmission.
Operation:
wrap(data) → capsule
Validation:
Schema + ontology conformance
Throughput:
10K capsules/sec
Latency:
< 2ms p99

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Resolver

Routing and verification node. Validates signatures, checks ontology compliance, and directs capsules to appropriate registry endpoints based on ontology path.
Function:
verify() → route() → forward()
Validation:
Signature + timestamp + ontology
Routing:
Deterministic ontology-based
Failover:
Automatic with circuit breaker

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Node Registry

Distributed index of verified capsules. Stores capsules indexed by ontology path, enabling O(log n) deterministic retrieval with namespace isolation.
Index type:
B-tree on ontology path
Query time:
O(log n) worst case
Storage:
Distributed + replicated
Retention:
Configurable per ontology
>_ 04_execution_flow

End-to-End Data Path

01
Capsule Creation
Agent emits data with ontology, payload, and metadata.
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{
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"ontology": "finance.transaction",
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"data": { ... },
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"timestamp": 1705158400
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}
02
Capsulizer Processing
System wraps data in verified envelope with cryptographic signature.
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signature = sha256(payload + timestamp + provenance)
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Resolver Verification
Validates signature, checks ontology, routes to appropriate registry nodes.
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assert valid(capsule, ontology)
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Registry Storage
Indexed by ontology path for deterministic retrieval.
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retention_policy = ontology.retention_rules
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Agent Consumption
Downstream agents query by ontology, receive verified capsules.
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subscribe(ontology) → stream(capsules)
>_ 05_trust_model

Provenance,  Identity, and Verfication

AgentNet implements a zero-trust architecture where every capsule must prove its authenticity through cryptographic verification. Trust is established through a three-layer model.

01

Provenance

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Source Attribution
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Chain of Custody
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Timestamp Verification
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Immutable Audit Trail
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Identity

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Agent Signatures
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Public Key Crypto
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Non-repudiation
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Authorization Model
03

Trust

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Cryptographic Proof
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Verification at Edges
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Zero-trust Architecture
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Policy Enforcement
~/ verification_process
1. Extract signature from capsule envelope
2. Verify signature against agent's public key (Ed25519)
3. Validate timestamp within acceptable drift (±30s)
4. Confirm ontology path matches registered schema
5. Check authorization policy for source → destination
✓ All checks pass → capsule accepted for routing
✗ Any check fails → capsule rejected at edge
TRUST_EQUATION
verify(signature) ^ validate(provenance) ^ authorize(identity)
>_ 06_ontology_system

Context-Aware Addressing

Ontologies provide hierarchical namespaces that enable agents to switch contexts without re-embedding data or recalculating similarity metrics. Each ontology path represents a specific domain or data type, allowing for precise targeting of information.
Example Ontology Paths
finance.transaction.payment
healthcare.patient.vitals
logistics.shipment.tracking
security.eventauthentication
telemetry.metrics.cpu
Query Semantics
Exact: finance.transaction.payment
Wildcard: finance.transaction.*
Prefix: finance.**
Time range: [timestamp_start, timestamp_end
/* rationale */
Agents can switch between ontologies instantaneously without model retraining or embedding regeneration. This enables multi-domain agents to operate across contexts with consistent query semantics.
>_ 07_retrieval_comparison

Deterministic Retrieval vs. Vector Search

Vector search provides semantic similarity but sacrifices determinism and introduces latency overhead. AgentNet's ontology-based retrieval guarantees reproducible results with predictable performance characteristics.

PROPERTY
Query Type
Reproduciblity
Latency
Precision
Context Switching
Trust Model
DETERMINISTIC (AgentNet)
Exact Ontology Path
100% Deterministic
0(log n) index lookup
Exact Match
Native via ontology
Cryptographic Verification
VECTOR SEARCH
Semantic Similarity
Non-deterministic
0(n) distance calculation
Approximate
Re-embedding required
Cosine similarity only
>_ 08_capabilities

Core System Properties

Deterministic Queries

Same input → same output, always

Cryptographic Trust

Verified signatures at every boundary

Low Latency

O(log n) index lookups, < 5ms p99

Multi-tenant

Namespace isolation per ontology

Schema Enforcement

Strict validation before acceptance

Audit Trail

Immutable provenance for every capsule

Context Switching

Native multi-domain agent support

Horizontal Scaling

Distributed registry with replication

Zero-trust

No implicit trust relationships
// INITIALIZE AGENTNET

Step into the Next Layer of the Machine Web

AgentNet defines how AI agents identify, coordinate, and verify actions across systems—using an open, machine-native standard built for scale.

ANS Standards
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