Seam by zer07 Labs · Private beta

Coordination, context,
identity, and audit —
at the boundary.

Seam plugs into your existing agent frameworks and enterprise systems. It handles the four operations that determine whether your agent deployments are trustworthy at scale — and gets smarter with every session it runs.

Seam · session lifecycle · admit → seal → learn
What Seam does

Four operations.
One product.

These are the operations agent frameworks don't handle and enterprise systems aren't designed for. Seam handles them — and only them. Each session is a closed loop that feeds the next one.

01
Coordination

Multi-agent decisions in bounded, policy-enforced sessions. Proposals, votes, commitments — explicit, binding, sealed. The session closes with a terminal outcome, not a convention in your code.

02
Context

Structured cognitive state — typed segments, content-addressed, budget-aware — carried across agent boundaries with provenance intact. Agents know what they know. And can prove it.

03
Identity

Challenge-response handshake before any operation. Identity verified, capabilities attested, trust level assigned as a first-class output — not checked as an afterthought.

04
🔒
Audit

Every session sealed as a hash-chained, append-only record, version-locked to the exact policy in effect. Six months later: replay, not reconstruct. Compliance gets proof, not logs.

How a Seam session works

Five stages. Every time.

Every agent interaction that passes through Seam is a session. Each stage is explicit, observable, and policy-enforced. None of it lives in your code.

1 · Admit
2 · Context
3 · Execute
4 · Decide
5 · Seal

Identity verified before anything runs.

The requesting agent declares its identity and capabilities. Seam challenges it — the agent responds with proof. Policy evaluates. A trust level is assigned: untrusted, sandboxed, trusted, or privileged. The precondition for every operation that follows.

// Seam challenges, evaluates, assigns trust level const session = await seam.admit({ agent: agentCert, caps: ['payments', 'read_contracts'], policy: 'financial-v4', }); // trust_level: "trusted" // granted_caps: ["payments", "read_contracts"]
Stage 1 · Identity admission

Context resolved to a budget, with provenance.

Seam resolves the agent's context from the graph — typed segments ranked by priority, compressed to fit the token budget. Each segment content-addressed and traceable to its source. The agent knows what it knows. Months later you can prove it.

// Budget-aware resolution const ctx = await seam.resolveContext({ session_id: session.id, include: ['constraints', 'knowledge', 'state'], budget: { max_tokens: 4096 }, compress: 'adaptive', }); // 3 segments · 2,891 tok · confidence 0.91
Stage 2 · Context resolution

Tasks dispatched. Reliability handled.

Seam dispatches tasks to agents in parallel or sequentially per your workflow. Retries, timeouts, circuit breakers, and heartbeat monitoring are handled by Seam. Your code declares what needs to happen. Seam handles every failure mode.

// Dispatch — Seam handles reliability const result = await seam.dispatch({ session_id: session.id, workflow: [ { agent: 'data-analyst', task: 'query_q3' }, { agent: 'doc-parser', task: 'extract' }, ], mode: 'parallel', timeout: 30_000, });
Stage 3 · Execution

Decisions made explicitly, in a bounded session.

When multiple agents need to agree on an outcome, Seam opens a decision session — declared participants, coordination mode, and policy. Agents propose, evaluate, and vote. The commitment is terminal and enters the audit record immediately. Seam records which policy governed this session — and waits for the outcome.

// Bounded decision session const d = await seam.decide({ mode: 'consensus', participants: [riskAgent, complianceAgent], policy: 'financial-v4', ttl: 30, }); // "APPROVED" · sha256:8f2c... · sealed // → learning loop records this decision
Stage 4 · Decision session

Session sealed. Replayable. The loop closes.

When the session closes, Seam seals it — a hash-chained, append-only record, version-locked to the runtime config and policies in effect. When the outcome arrives — minutes, hours, or days later — the loop closes: Seam's confidence in the governing policy updates, and the next session in the same context class benefits.

// Replay any session, months later await seam.replay('ses_f4a1', { seamVersion: '1.4.2', policyVersion: 'financial-v4', }); // ✓ Identical state transitions // ✓ Export for regulatory submission // ✓ Outcome feeds the learning loop
Stage 5 · Sealed · outcome feeds learning loop
How Seam gets smarter

Every decision teaches
the next one.

A closed learning loop runs underneath every session. The runtime that executes your agent workflows is the same runtime that learns from their outcomes — improving coordination quality, context calibration, and routing decisions continuously. Not in a training run. Not after a model deployment. After every outcome.

Policy selection improves with every outcome
Seam learns which coordination approach works best for each type of decision in your environment. High-performing policies accumulate confidence over time. Where Seam is certain, it applies what it knows. Where it is not, it explores — automatically, without configuration. The more decisions it runs, the better the policy selection gets.
🧠
Novel situations are handled — not stalled
When Seam encounters a decision type it hasn't seen before, it doesn't fall back to random selection. It reasons from context and similar past outcomes to make an informed initial choice, then learns from real results. When no existing policy handles a context class well, Seam flags the gap and proposes a new one for human review — it goes live only when approved.
The loop closes continuously — no training runs
Every session outcome feeds back into Seam's decision model immediately. There is no monthly retraining cycle, no model deployment, no human trigger required. Outcomes that take days to confirm — a fraud chargeback, a compliance ruling, a clinical result — are handled natively. The system holds the decision in context until the outcome arrives, then updates.
New customers start ahead, not from zero
Customers who opt in contribute anonymised learning — what worked, what didn't — to a shared vertical knowledge base. New customers in the same industry inherit that accumulated knowledge as their starting point. Where a customer starting from scratch might take weeks to converge, a new Seam customer in an established vertical is calibrated from day one.
The compound value story

Most enterprise infrastructure is static. The same rules that governed the first decision govern the ten-thousandth. Seam is different: coordination gets smarter, context resolution gets better-calibrated, and trust policies self-tune — all from session outcomes, in your environment, specific to your workflows.

After 12 months: a system calibrated across tens of thousands of confirmed outcomes in your specific environment. Unavailable to any competitor. Impossible to replicate without running the same decisions through the same feedback loop for the same duration.

Full learning architecture →
Seam learning · outcomes feed the next decision
Policy selection · confidence builds with every confirmed outcome
Open protocols

We open-sourced the specs
Seam is built on.

Seam's coordination, context, and identity layers are built on three protocols we designed and released under Apache 2.0 — our contribution back to the agent ecosystem. The specs are open. Anyone can implement them. Seam is our production implementation.

MACP
Multi-Agent Coordination Protocol
GitHub →
CTXP
Context Transfer Protocol
GitHub →
AITP
Agent Identity & Trust Protocol
GitHub →
Integrations

Seam plugs in.
Your stack stays.

Works alongside LangChain, LangGraph, CrewAI, AutoGen, Temporal, MCP, A2A, and ACP. Integrates with Snowflake, Databricks, Okta, AWS IAM, Postgres, Kubernetes, and OpenTelemetry.

Seam · integration layer
Enterprise

For organisations where agent decisions have
real consequences.

We scope, integrate, and operate Seam directly with your engineering, security, and compliance teams. Your infrastructure. Your policies. Your data plane.

Talk to us →
🏗
Your infrastructure
Single-tenant in your cloud or on-prem. No shared inference. No data egress. Ever.
📋
Compliance-ready
SOC 2 Type II, HIPAA BAA, ISO 27001. Custom DPA signed before deployment.
🧠
Learning stays in your VPC
Decision outcomes, learning state, and session records never leave your infrastructure. Opt-in shared learning contributions are fully anonymised.
🤝
Dedicated team from day one
Solutions architect and implementation engineer included. 24/7 SLA-backed support.

Your agents handle reasoning.
Seam handles the rest.

One product. One integration. Gets smarter with every session it runs.

Talk to us → See use cases

Seam · zer07 Labs · Private beta 2025