Coordination & Relationship Infrastructure

The Missing Layer
Below Agent Systems

Your agents can reason, plan, and call tools. But coordination state — trust, conflict, delegation, recovery — is invisible. RelationshipOS is the infrastructure stack to observe, resolve, and trace it.

See Agent Demo How It Works

Built for

AI Infrastructure Builders Agent Framework Teams Multi-Agent Architects Technical Founders Infrastructure Investors
Modern AI Systems Can
✓ Capabilities today
🧠

Reason across long contexts

🗺️

Plan multi-step workflows

🔧

Call tools and external APIs

⚡

Execute autonomous tasks

But They Still Lack
✗ No standard model for
🔗

Coordination Statewho delegates to whom, and how that changes

🛡️

Trust Evolutionconfidence scores, reliability history, earned authority

📡

Response Availabilityis this agent reachable, overloaded, or offline

⚔️

Conflict & Repairwhen agents disagree — or break — and how they recover

📈

Relationship Trajectorieshow coordination patterns shift over the lifetime of a system

What is RelationshipOS

Infrastructure, not a framework

RelationshipOS sits beneath your agent orchestration layer. It provides a standardized data model and resolution engine for coordination state — just as OpenTelemetry provides a standard for observability signals.

Analogous Layers
OpenTelemetry
→ signals for →
RelationshipOS
distributed traces
→ equivalent →
coordination traces
spans + metrics
→ equivalent →
observations + trust
service health
→ equivalent →
relationship health
Agent Framework (LangGraph, CrewAI, AutoGen…) your framework
Task Orchestration Layer your orchestrator
RelationshipOS · Coordination State Layer we are here
RelationshipOS · Evidence & Truth Resolution we are here
LLM Inference / Compute provider
Network / Storage / OS infra
Proof Case: Agent-to-Agent Coordination

What breaks when agents coordinate

Watch the same pipeline — once without RelationshipOS, once with it. Coordination state becomes observable, recoverable, and traceable.

without_relationship_os.log
Coordination Failure
🧭
Planner Agent
task_id: research_q4_strategy
delegated_to: research_agent
delegation_sent ↓
🔬
Research Agent
status: OFFLINE (overloaded)
queue_depth: 47
⏱ response_timeout: 30s
🏗️
Builder Agent
input: null (never received)
context: missing
✕ task_failed: null_input
🔍
Reviewer Agent
invoked: false
reason: upstream_failure
✕ pipeline_aborted

ERROR: No coordination state recorded.
No trust signal updated.
No recovery path identified.
Failure cause: unknown to operator.

with_relationship_os.trace
Resolved + Traced
🧭
Planner Agent
coord_id: crd_8f2a91
trust_basis: historical_success(0.94)
coordination_state: ACTIVE
⚡
Research Agent — Overloaded
availability: DEGRADED
ros.escalation: fallback_to_research_b
⚠ responsiveness_event logged
🔁
Research Agent B — Recovery
ros.repair_cycle: initiated
trust_trajectory: recovering
✓ recovery_cycle: complete
🏗️
Builder Agent
input: research_b_output
coord_state: DELEGATED
✓ task_in_progress
🔍
Reviewer Agent
conflict_check: passed
trajectory: positive_drift
✓ pipeline_complete · fully_traced

coordination_trace: crd_8f2a91 → exported
trust_deltas: recorded for 4 agents
repair_cycle: logged + attributed
Full trajectory available in ROS Dashboard.

How RelationshipOS Works

From raw signals to trusted state

A four-stage pipeline converts agent interactions into structured, traceable coordination state.

01
Evidence Collection
Raw behavioral signals from agents — messages sent, latencies, errors, delegation requests — captured and typed.
evidence {
  source: "planner_agent"
  target: "research_agent"
  type: DELEGATION_REQUEST
  ts: "2025-06-12T08:14:22Z"
}
02
Observations
Interpreted patterns over evidence — availability states, trust signals, conflict indicators — with confidence weights.
observation {
  pattern: RESPONSE_UNAVAILABLE
  confidence: 0.91
  evidence_refs: ["ev_44f", "ev_91c"]
}
03
Truth Resolution
Conflicting observations are reconciled into canonical coordination state — the authoritative record of the relationship at a given moment.
truth {
  coord_state: DEGRADED_ACTIVE
  trust_score: 0.63
  repair_eligible: true
}
04
Traceability
Every state change is attributed, timestamped, and exportable. Full audit trail from cause to resolution — queryable like distributed traces.
trace.export("crd_8f2a91")
→ coordination_trace.json
→ trust_timeline.json
→ repair_attribution.json
Evidence T+00:00.000
planner_agent → research_agent
DELEGATION_REQUEST · task_id: q4_strategy
timeout_budget: 30s
Evidence T+00:30.421
research_agent → no response
TIMEOUT · queue_depth: 47
availability_signal: DEGRADED
Observation T+00:30.500
pattern: RESPONSE_UNAVAILABLE
confidence: 0.91
escalation_eligible: true
Truth T+00:30.512
coord_state: DEGRADED_ACTIVE
repair_path: research_agent_b
trust_delta: −0.12 (research_agent)
Trace T+02:14.881
trace_id: crd_8f2a91
repair_complete: true
trajectory_shift: RECOVERY → STABLE
Core Primitives

A typed model for coordination state

Six foundational primitives. Composable. Versioned. Exportable. Schema-compatible with existing observability pipelines.

🔗
CoordinationState
The current relationship posture between two agents — ACTIVE, DELEGATED, DEGRADED, SUSPENDED, REPAIRING.
state: CoordStateEnum
since: Timestamp
initiator: AgentRef
🛡️
TrustVector
A multi-dimensional trust score with historical delta tracking. Earned through observable behavior, not declared.
reliability: Float[0..1]
authority: Float[0..1]
delta_30d: Float
📡
ResponsivenessSignal
Availability posture of an agent at any moment — latency, queue depth, error rate, degradation reason.
availability: AvailEnum
latency_p99: Duration
queue_depth: Int
⚔️
ConflictRecord
A structured account of disagreement or collision between agents — typed by cause, severity, and resolution status.
type: ConflictTypeEnum
severity: SeverityLevel
resolution: ResolutionRef?
🔁
RepairCycle
The structured sequence of actions taken to restore a degraded coordination — with attribution and outcome.
trigger: ConflictRef
steps: RepairStep[]
outcome: RepairOutcome
📈
RelationshipTrajectory
The long-run arc of a coordination pair — drift detection, inflection points, lifecycle stage classification.
trend: TrendEnum
inflections: Event[]
stage: LifecycleStage
Where It Applies

Infrastructure beneath every coordination pattern

Agent coordination is the proof case. The category is much larger.

Use Case 01
Multi-Agent Pipeline Observability
Instrument LangGraph, CrewAI, AutoGen, or custom orchestrators with RelationshipOS to emit coordination traces alongside your existing spans and metrics. Understand not just task completion — but why a delegation succeeded or failed.
LangGraph CrewAI AutoGen custom orchestrators
Use Case 02
Delegation Failure Diagnosis
When a pipeline silently fails, coordination traces show which agent was unavailable, what trust signals preceded it, and whether a repair path was available — giving you a root cause instead of a timeout error.
failure attribution timeout diagnosis repair tracing
Use Case 03
Trust-Aware Routing
Use live TrustVector scores to route delegation decisions at runtime. High-trust paths get first priority. Degraded agents are bypassed automatically. Trust is earned, observed, and actionable — not declared in config files.
dynamic routing trust scoring availability gating
Use Case 04
Human-Agent Coordination Audit
Model the relationship between human principals and agent systems using the same primitives. Track delegation, conflict, override, and repair events across human-AI boundaries with full attribution.
human-in-the-loop override tracking audit trails
Category Positioning

Larger than the use case

We are not
An agent framework or SDK
An autonomous agent platform
An AI workflow automation tool
A replacement for your orchestrator
We are
Infrastructure beneath agent systems
A standard data model for coordination state
An evidence → truth resolution engine
A coordination traceability layer
"OpenTelemetry for coordination."
OpenTelemetry didn't replace your application. It gave distributed systems a shared language for observability. RelationshipOS gives agent systems a shared language for coordination state.

The category is Relationship and Coordination Infrastructure — a layer every sufficiently complex agentic system will eventually need.
Early Access Open

Build on the infrastructure,
not around the gap

RelationshipOS is in private preview. We're working with AI infrastructure teams, framework builders, and technical founders who are hitting the walls of coordination state today.

Request Early Access Read the Spec Draft

For: AI infrastructure teams · Agent framework builders · Multi-agent architects · Infrastructure investors