ARBITR

Where autonomous execution becomes accountable.

The execution-assurance control plane for the moment autonomous systems act. Built for organisations whose AI and agentic automations now execute real changes across payments, records, workflows, and cross-system processes - and need to see, in evidentiary form, exactly what happened. Runtime-agnostic. Vendor-neutral. ARBITR makes delegated execution visible, structured, deterministic, tenant-isolated, portable, and evidentiary. Not identity. Not policy. The layer that records, and proves, what actually ran, under whose authority, at the moment it committed.

For teams deploying autonomous systems where execution authority matters.

ARBITR and system logs are not the same thing.

System logs are produced by the systems doing the work, for the people who run those systems. They tell engineers what happened inside an application, a database, or a piece of infrastructure - exceptions, latencies, errors, throughput. They are written in the language of the system. They are read by the people who keep that system running. Their job is operational diagnosis, not delegation evidence.

ARBITR is produced by the autonomous systems doing things on someone's behalf, for the people who are accountable when those things go wrong. It does not record that a process ran. It records which agent acted, under what delegated authority, on whose behalf, against which target system, with what result, and at the moment it committed. The unit of capture is the act of delegated execution, not the operation of the underlying machine.

The audiences are different. The questions are different. The evidence is structured differently because the questions are structured differently.
A system log answers: did the application work?
ARBITR answers: was this autonomous action authorised, by whom, in what context, and is there a deterministic record I can present to a board, an auditor, or a regulator?
Both are useful. They are not substitutes.

The runtime governance gap.

The boundary between advisory AI and executing AI is where the assumptions holding current governance in place quietly break. Once a system moves from suggesting an action to performing one, making the payment, modifying the record, triggering the workflow, deploying the change, the decision cadence most governance frameworks rely on no longer exists.

"Human in the loop" sounds reassuring because it assumes a human can plausibly review what happened before consequences land. At machine speed, that assumption stops being true. Actions commit faster than any review cycle can reach them. The governance is on paper. The execution has already occurred.

A log is not enough. Traceability shows that something happened. It does not, on its own, show that the action was authorised, by whom, within what scope, under what delegation, and with what consequence. That is the gap ARBITR exists to close.

Built from the same governance-first perspective used in regulated financial services and other high-trust operating environments, where execution, accountability, and consequence cannot be separated.

The primitive: the ARBITR Envelope.

At the core of ARBITR is a single primitive: the Envelope, Structured Execution schema v1. In plain terms, it is a structured, append-only execution record emitted per step. It gives each consequential action a stable, defensible record shape across runtimes, tenants, and environments.

Versioned, tenant-scoped, trace-correlated, capability-bound, secret-safe, signature-ready, and authority-context aware.

Each envelope captures:

  • The initiating actor reference - the human or upstream system that triggered the step
  • The agent reference - the AI or automated component that performed the step
  • The delegation context - the authority chain under which the step was permitted
  • The authority scope - the specific bounds on what the step was allowed to do
  • The target system and action performed
  • The result status
  • Optional checkpoint references and artifact pointers

It is designed to preserve a stable record shape so evidence can be interpreted consistently, exported cleanly, and later sealed cryptographically without changing the underlying execution history.

The envelope is not a policy decision. It is not a compliance certificate. It is a deterministic execution record.

What ARBITR gives the customer.

Three goods, structural and portable.

Visibility.

A real-time view of what autonomous systems are doing at the moment they act. Every consequential step captured in a standardised envelope recording initiator, agent, delegated authority, target system, and outcome.

Accountability.

Every execution step carries its delegation context, traceable back to why something was permitted, not just that it happened. This closes the gap between "the system had permission" and "the system should have acted in this specific way at this specific moment."

Portable evidence.

Structured, exportable evidence bundles that are vendor-neutral and signature-ready. Designed for three levels of review:

  • An executive summary for boards and decision-makers
  • A structured control and exception view for procurement and assurance teams
  • Detailed execution records with checkpoint and artefact references for compliance, audit, and investigation

Not locked into one platform or AI vendor. Built so the evidence can travel, be defended, and be reviewed at the level each audience actually needs.

"In practice, this means ARBITR is not just producing logs. It is producing evidence packages that executives can understand, procurement teams can assess, and compliance teams can work with, in a standards format."

Architecture principles.

ARBITR is SaaS-first and runtime-agnostic. Envelope discipline is absolute because evidence portability depends on a stable record shape across tenants, runtimes, and releases. Storage is append-only. Tenant isolation is enforced at the database layer. No raw secrets are persisted in envelopes. Signature-readiness is built in from v1 so evidence bundles can be cryptographically sealed as the programme matures. The design is extensible across environments and organisational boundaries without changing the underlying execution record.

This is the discipline that makes the evidence defensible later, not just convenient now.

Competitive positioning.

The agent market is splitting into layers, not converging into one crowded category. ARBITR's lane is the neutral execution evidence and interpretation layer across agents, runtimes, enterprise systems, and commit surfaces.

Player Market layer Control point What it is selling ARBITR relationship
ARBITR Neutral execution evidence and interpretation layer Cross-runtime execution records, topology, and evidence bundles Canonical execution envelopes, deterministic trace topology, tenant-isolated evidence, and executive-ready execution assurance ARBITR adds the connective interpretation layer across the market. It records, reconstructs, and packages execution evidence without replacing agents, identity, policy engines, payment rails, or enforcement systems.
OpenClaw Open-source AIOS and local-first agent runtime layer Local Gateway, messaging channels, agent sessions, skills, tools, cron jobs, browser actions, files, shell access, and app nodes Personal and team AI assistants that run on user-controlled devices and execute real work through chat, tools, and connected systems ARBITR adds enterprise-grade execution evidence to OpenClaw deployments. It captures Gateway and session events, channel-originated instructions, skill and tool calls, file and shell activity, cron jobs, approvals, checkpoints, and outcomes, then generates deterministic topology, authority trails, evidence bundles, and executive-readable outputs for secure OpenClaw operations.
OpenAI Frontier / ChatGPT Workspace Agents Agent platform and workspace automation layer Shared agents, long-running work, tool orchestration, and business-system access Agent teams that carry out delegated work across business systems inside OpenAI and ChatGPT workspaces Important evidence source and connector target. ARBITR captures run metadata, tool calls, handoffs, authority context, and outcomes where customer-accessible telemetry allows, then generates topology views, evidence bundles, and executive-readable execution outputs.
AWS Bedrock Managed Agents / OpenAI on AWS Cloud agent runtime and managed infrastructure layer AWS-hosted agent build, deployment, logging, and operational governance Production agent deployment inside AWS with enterprise cloud controls and model access Strong cloud-runtime connector target. ARBITR ingests Bedrock, CloudWatch, EventBridge, and state-lineage events under customer approval, then adds cross-runtime interpretation beyond the AWS estate.
Microsoft Copilot / Agent 365 Enterprise productivity and agent governance layer Microsoft 365 context, enterprise work graph, agent lifecycle, and admin controls Delegated work inside Word, Excel, PowerPoint, Outlook, Teams, and Copilot Chat Complementary. Microsoft governs agents inside its estate. ARBITR evidences Microsoft and non-Microsoft execution together so delegated work remains visible across boundaries.
Salesforce Agentforce 360 / Headless 360 CRM and enterprise workflow agent layer Salesforce records, flows, APIs, MCP tools, business logic, and customer operations Agent-ready access to CRM, service, sales, and operational workflows Strong integration target. ARBITR evidences agent-driven changes to records, opportunities, cases, flows, and other production CRM actions, then turns those changes into traceable execution journeys.
Agent Script Agent behaviour definition layer Structured agent logic, transitions, guardrails, and sub-agent flow design A more inspectable way to define expected agent behaviour inside supported ecosystems Declared-behaviour evidence artifact. ARBITR references expected agent behaviour, compares it with observed execution, and produces variance, topology, and evidence outputs without becoming the behaviour engine itself.
Anthropic Claude Code / Claude agent workflows Agentic coding and delegated work layer Codebase access, file changes, tests, shell actions, and multi-step task execution Agentic execution for software engineering and knowledge work Important evidence source. ARBITR captures code, file, shell, PR, and deployment activity and connects it to authority context, approval state, and downstream production impact.
OpenAI Codex Agentic coding layer Parallel coding agents, worktrees, cloud environments, and code review flows Software engineering acceleration through delegated coding and review ARBITR evidences what changed, which tests ran, what was approved, what was committed, and what reached production, then packages the software-execution trail for review and audit.
Cursor / Windsurf AI development environment layer IDE-level agent actions across source code, terminals, repositories, and local tooling Developer productivity through agent-assisted and agent-led coding workflows ARBITR adds downstream execution evidence from Git, CI/CD, shell, database migration, and deployment adapters while the IDE remains the developer execution surface.
Perplexity Computer / Comet workflows Research and computer-use agent layer Research tasks, browser actions, source gathering, file creation, and deliverable assembly Agentic research and analysis workflows with browser and computer-use capability ARBITR evidences source trails, tool use, generated artifacts, and decision-support workflows when those outputs influence business action or operational decisions.
Google Gemini Enterprise agent stack Enterprise agent platform layer Google Cloud and Workspace agent lifecycle, orchestration, security, and governance Build, deploy, govern, and optimise enterprise agents inside the Google ecosystem Complementary. Google governs agents inside Google Cloud and Workspace. ARBITR ingests Google Cloud and Workspace execution evidence and correlates it with activity from other vendor estates.
Kimi K2.6 / Qwen Code Open-weight and self-hosted agent layer Local or self-hosted coding agents, long-horizon tasks, and agent swarms Lower-cost or more controllable agentic execution outside closed hyperscaler runtimes ARBITR supports local-first Python, Node, and MCP adapters so self-hosted agents emit SE envelopes cleanly and receive the same topology, evidence, and export outputs as managed runtimes.
MCP Tool access protocol and connector surface How agents discover, connect to, and call external tools A common integration pattern for agent-to-tool execution Strategic observation surface. ARBITR captures MCP tool calls across many runtimes, normalises them into SE envelopes, and turns agent-to-tool activity into evidence-ready execution topology.
On-prem AIOS agent solution Private agent operating-system layer Customer-controlled agent runtime, private tools, internal systems, local models, network egress rules, and restricted evidence streaming Secure internal agent execution inside the customer estate with tightly controlled outbound-only connectivity ARBITR adds the same execution assurance outputs to private AIOS deployments as managed runtime deployments. The ARBITR SDK emits a tightly scoped outbound-only encrypted stream from your approved IP and port, producing canonical SE envelopes, live topology views, tenant-isolated evidence bundles, executive reports, and forensic exports without opening inbound access to the customer estate.
NVIDIA NemoClaw Enterprise AIOS runtime and deployment layer Enterprise OpenClaw deployment, GPU-backed execution, packaging, hardening, privacy, and network guardrails Secure packaged OpenClaw-style AIOS infrastructure for organisations running persistent agents across enterprise systems ARBITR turns a NemoClaw AIOS estate into an accountable execution environment. It captures agent steps, tool calls, boundary crossings, authority context, outcomes, checkpoints, and artifacts from NemoClaw and connected systems, then generates cross-runtime topology, tenant-isolated evidence bundles, executive reporting, and forensic trace exports beyond the NemoClaw runtime itself.
Tunic Pay Payment context and fraud-decision infrastructure layer Payment context, fraud signals, authorised payment risk, and decision support Infrastructure to help banks and payment providers understand payment intent and scam risk Complementary payment-context layer. Tunic Pay strengthens payment decision context. ARBITR records what an agent or system executed after that context was used and packages the resulting authority trail.
MATTR Trust, identity, and credential infrastructure layer Digital trust, verifiable credentials, delegation, and authorisation signals Trust infrastructure for agentic commerce, identity, and delegated authority Complementary trust layer. MATTR strengthens identity, credential, and delegation signals before action. ARBITR records and interprets the execution trail after action occurs.
Zortrex Execution authority enforcement layer Commit-time authority boundary Runtime authority control and bounded execution Adjacent authority-control layer. Zortrex constrains execution at the commit boundary. ARBITR evidences and interprets execution across systems, including flows inside and outside Zortrex-governed boundaries.
Genesis50 Compliance enforcement layer Mandatory compliance choke-point Reg-to-code enforcement plus immutable audit log Adjacent compliance-control layer. Genesis50 blocks regulated actions through compliance logic. ARBITR provides neutral evidence, topology, and executive-ready outputs without presenting itself as a compliance guarantee.

The market is not becoming one agent platform. It is becoming a network of execution surfaces. ARBITR helps organisations evidence, interpret, and defend what autonomous systems actually executed across those surfaces.

Status.

ARBITR is in active development. The core primitive is stable, the V1 product scope is defined, and ten pilot organisations are being selected. The product is not available for general sale at this stage. The pilot programme is the only commercial path today.

ARBITR is best suited, today, to organisations deploying or planning autonomous systems where execution authority matters across payments, record modification, agent-triggered workflows, or other compliance-sensitive operations.

Express interest in the ARBITR Pilot.

Ten organisations will help shape ARBITR while structural feedback can still influence the product. Each pilot partner pays a single fixed entry fee and receives lifetime access thereafter. This is not a discount scheme. It is a partnership.

Submit an Expression of Interest and, if the fit is strong, you will be invited to a qualification call. Shortlisted organisations receive the Prospectus and, under mutual non-disclosure, the Architecture Brief and Envelope schema.

Not ready for either? For advisory, integration, or partnership enquiries that sit outside the pilot route, email contact@magentix.ai.