# Monarch > Monarch is enterprise agent infrastructure: the application context layer that production AI agents need to reach and act across existing business software, including legacy systems with no APIs. Monarch maps the APIs, undocumented endpoints, records, permissions, workflows, browser-only UI actions, and system relationships that agents need before taking action, and keeps that map current as products change. Use this file as a concise guide to Monarch's public website and indexable content. ## Core Pages - [Mainframes & terminals](https://www.monarchagents.ai/solutions/mainframes/): Bring core application transactions into agent workflows; application-level compatibility assessment, terminal examples, and access controls. [Markdown](https://www.monarchagents.ai/agent/mainframes.md). - [Home](https://www.monarchagents.ai/): Overview of Monarch's enterprise agent infrastructure and the Product Graph, with email signup. - [Product Graph](https://www.monarchagents.ai/product-graph/): How Monarch turns an application's full surface—undocumented APIs, human UI paths, permissions, and business logic—into reliable, programmatic actions agents can call. - [For Agents](https://www.monarchagents.ai/for-agents/): Machine-readable Monarch resources for agents and answer engines, including Markdown views and JSON endpoints. - [Benchmarks](https://www.monarchagents.ai/benchmarks/): Monarch on AutomationBench — three frontier models run with and without Monarch across 591 business workflows; every model completed more work with Monarch. Published August 17, 2026. - [About](https://www.monarchagents.ai/about/): What Monarch is, why system context matters, and how Monarch differs from a fixed connector catalog. - [Pricing](https://www.monarchagents.ai/pricing/): Monarch pricing — one platform with a flat price per action across every system, offered as four plans (Pilot, Launch, Scale, Enterprise). Specific prices are set through a conversation, not published. - [Healthcare](https://www.monarchagents.ai/industries/healthcare/): Monarch for healthcare payers and providers — prior auth, claims, and member workflows across Epic, payer portals, and the systems around them. - [Energy & Utilities](https://www.monarchagents.ai/industries/energy/): Monarch for energy, mining, and utility operators — meter, billing, and field workflows across ERP, asset, and compliance systems. - [Financial Services](https://www.monarchagents.ai/industries/financial-services/): Monarch for banks and payments teams — credit, servicing, and back-office workflows across core banking and merger-era systems. - [Airlines](https://www.monarchagents.ai/industries/airlines/): Monarch for airlines - warranty claims, disruption cases, and operations exceptions assembled for review across booking, maintenance, and ops systems. - [Security & Governance](https://www.monarchagents.ai/security/): How Monarch runs under customer governance - cloud and model choices, access controls, audit trails, SOC 2 Type II. - [AI Agents for Telecommunications: Recover Orders That Fall Between CRM and Provisioning](https://www.monarchagents.ai/blogs/ai-agents-telecommunications-order-fallout/): An accepted broadband order can still leave a customer without service. Recovering it means following the work through provisioning, inventory, and billing, then proving the records agree. - [AI Agents for Employee Offboarding: Close the Gaps Across HR and IT](https://www.monarchagents.ai/blogs/ai-agents-employee-offboarding/): Carry an approved departure through access removal, work handover, and records preservation, with evidence of what each system actually completed. - [AI Agents for Supplier Delays: Give Planners a Delivery Date They Can Use](https://www.monarchagents.ai/blogs/ai-agents-supplier-delays/): Follow a late purchase-order line from a supplier's revised promise through split deliveries, production decisions, and actual receipt. - [AI Agents for Accounts Payable: Resolve the Invoice Exception Before the Payment Run](https://www.monarchagents.ai/blogs/ai-agents-accounts-payable-invoice-exceptions/): Follow an invoice discrepancy through purchasing, receipts, supplier correspondence, and AP, then verify that the approved correction reached the records that control payment. - [How to Evaluate an Enterprise AI Pilot: A Scorecard for Completed Work](https://www.monarchagents.ai/blogs/how-to-evaluate-enterprise-ai-pilot/): Define which cases enter the pilot, what counts as a useful result, and how you will compare it with today's operation before the first live run. - [AI Agents for Airline Disruption: Close the Gap Between Rebooking and a Place to Stay](https://www.monarchagents.ai/blogs/ai-agents-airline-disruption-accommodation/): Rebooking leaves work across hotel suppliers, ground transport, and case systems. Start with one overnight assistance workflow and verify every arrangement. - [AI Agents for Financial Hardship: Stop Making Customers Repeat Their Story](https://www.monarchagents.ai/blogs/ai-agents-financial-hardship-operations/): A useful banking agent connects the customer's request, account history, and existing support arrangement, then helps the team carry its decision into the systems that administer the loan. - [AI Agents for Insurance Claims: Build the Evidence Before the Settlement](https://www.monarchagents.ai/blogs/ai-agents-insurance-claims-evidence/): An insurer's AI workflow should connect the policy, repair estimate, and claim history, then help the team complete the next action with the customer properly informed. - [Your AI Strategy Won’t Work If Everyone’s Job Stays the Same](https://www.monarchagents.ai/blogs/ai-strategy-job-redesign/): AI adoption requires changes to people’s workloads, incentives, and responsibilities. Give them time to improve the work and authority to lead the agents doing it. - [Blog](https://www.monarchagents.ai/blogs/): Monarch writing on production AI agents, enterprise integrations, workflow automation, system access, and agent infrastructure. - [Contact](https://www.monarchagents.ai/contact/): Contact page for teams evaluating Monarch. - [Monarch Australia](https://www.monarchagents.ai/au/): Enterprise AI across existing systems, Australian deployment options, and our commitment to the country. - [About Monarch Australia](https://www.monarchagents.ai/au/about/): Australian founder Sam Senior and our ambition to help Australia be at the frontier of what is possible. ## Articles - [Mainframes Aren’t Dinosaurs](https://www.monarchagents.ai/blogs/mainframes-arent-dinosaurs/): Alex Nauda on mainframe workloads, existing integrations, and bringing agentic workflow development to terminal applications. [Markdown](https://www.monarchagents.ai/agent/blog-mainframes-arent-dinosaurs.md). - [Your next software builder might work in finance](https://www.monarchagents.ai/blogs/your-next-software-builder-might-work-in-finance/): What OpenAI’s non-engineering teams suggest about enterprise work over the next three years, and what finance, recruiting, and legal teams need to build reliable workflows themselves. - [Your Business Can Do More Than Your AI Connectors Allow](https://www.monarchagents.ai/blogs/your-business-can-do-more-than-your-ai-connectors-allow/): A connector logo does not mean your agents can finish the work. Expect deeper application discovery, reusable execution, and people leading the business change. - [Monarch vs Workato for enterprise AI agent integration](https://www.monarchagents.ai/blogs/monarch-vs-workato/): Compare Workato Enterprise MCP and Genies with Monarch’s Product Graph on application access, reusable tools, governance, and maintenance. - [Monarch vs Google Gemini: what your Google stack covers](https://www.monarchagents.ai/blogs/monarch-vs-google-gemini/): Compare Gemini, Google Workspace, and Google agent infrastructure with Monarch. See where existing tools fit and when discovered application access adds value. - [Monarch vs Microsoft Copilot, Copilot Studio, Foundry, and Fabric](https://www.monarchagents.ai/blogs/monarch-vs-microsoft-copilot-foundry-fabric/): Already use Microsoft? Compare Copilot, Copilot Studio, Foundry, and Fabric, and see where Monarch adds reusable access to legacy and internal apps. - [Permission-Aware Enterprise Agents: Whose Authority Applies?](https://www.monarchagents.ai/blogs/permission-aware-enterprise-agents/): Learn how to scope enterprise agent access across connected identities, tools, and approvals, then verify changes and remove permissions when access ends. - [AI Agents in a Customised ERP: Get the Change Request Right](https://www.monarchagents.ai/blogs/ai-agents-customised-erp/): Use AI agents with customised ERP operations. Understand custom fields, supplier records, permissions, and approvals before submitting a change request. - [Computer Use or Monarch for Enterprise Workflows?](https://www.monarchagents.ai/blogs/computer-use-agents-enterprise-reliability/): Compare computer-use agents and Monarch on application access, repeated execution, self-healing, verification, and recovery across enterprise systems. - [Build With Claude or OpenAI Directly, or Add Monarch?](https://www.monarchagents.ai/blogs/claude-openai-enterprise-actions/): Compare building enterprise agents with Claude or OpenAI tools against adding Monarch for application access, cross-system execution, and maintenance. - [Monarch vs CData Connect AI for Enterprise Agents](https://www.monarchagents.ai/blogs/monarch-vs-cdata/): Compare Monarch and CData Connect AI for enterprise agents: queries, writes, custom tools, application discovery, and US or Australian deployment. - [Connecting AI Agents to Internal Apps Without an MCP Server](https://www.monarchagents.ai/blogs/connecting-agents-to-internal-apps/): A practical guide to connecting AI agents to internal apps: find an access route, define the operation, enforce approvals, and recover from partial failure. - [Monarch vs Arcade for Enterprise AI Agents](https://www.monarchagents.ai/blogs/monarch-vs-arcade/): Compare Monarch and Arcade on tool authorisation, custom tools, application discovery, deployment, and the cost of completing enterprise workflows. - [Monarch vs Composio for Enterprise AI Agents](https://www.monarchagents.ai/blogs/monarch-vs-composio/): Compare Monarch and Composio for enterprise agents: tool execution, custom application access, permissions, costs, and US or Australian deployment. - [AI Agents for Australian Energy Retailers: Start With Billing Investigations](https://www.monarchagents.ai/blogs/ai-agents-australian-energy-retailers/): Start with billing investigations. Learn how AI agents can check NMI and account records, gather evidence, support review, and measure completed work. - [Monarch vs UiPath for Enterprise AI Agents](https://www.monarchagents.ai/blogs/monarch-vs-uipath/): Compare Monarch and UiPath for existing enterprise AI agents: application access, process ownership, approvals, costs, and Australian and US deployment. - [Who Owns an AI Workflow After the Pilot?](https://www.monarchagents.ai/blogs/who-owns-ai-workflows-after-the-pilot/): Define AI workflow ownership after the pilot: business outcomes, operational measures, human review, maintenance, and the authority to change or stop it. - [Monarch Sydney Panel with BCG X and Airtree: When AI Moves Faster Than the Enterprise](https://www.monarchagents.ai/blogs/leading-through-change-sydney-panel/): A panel with BCG X and a digital, data, and AI executive on why enterprise AI adoption is running ahead of enterprise AI impact, with the full video and transcript. Published September 9, 2026. - [AI won't transform a company you refuse to rebuild](https://www.monarchagents.ai/blogs/rebuild-the-enterprise-while-it-runs/): Why using AI to run a slightly faster version of the company you already have caps the return, and how enterprises rebuild how the work runs while the business keeps running. Published September 4, 2026. - [The map your AI needs is already inside your systems](https://www.monarchagents.ai/blogs/enterprise-ai-ontology-discover-it-from-your-systems/): What an enterprise AI ontology is, why most of it already exists inside the software a business runs, and why it should be discovered from those systems rather than redrawn from memory. Published August 31, 2026. - [MCP is the wrong default for enterprise AI](https://www.monarchagents.ai/blogs/mcp-wrong-default-for-enterprise-ai/): Why MCP makes connecting agents to your systems easy but not dependable, and what to run instead for enterprise workflows. Published August 26, 2026. - [Workato vs MuleSoft vs Automation Anywhere vs Monarch](https://www.monarchagents.ai/blogs/workato-vs-mulesoft-vs-automation-anywhere-vs-monarch/): Compare Workato, MuleSoft, Automation Anywhere, and Monarch on workflow completion, agent capabilities, total cost, and Australian deployment requirements. - [Why Enterprise AI Agents Fail and What Failed Runs Cost](https://www.monarchagents.ai/blogs/why-enterprise-ai-agents-fail-and-what-they-cost/): Learn why enterprise AI agents fail, how to diagnose the cause, and how to calculate cost per completed workflow including retries and human intervention. - [AI Agent Integration Platforms: How to Choose](https://www.monarchagents.ai/blogs/ai-agent-integration-platforms/): Compare AI agent integration platforms by action coverage, permissions, and maintenance. See where Workato, Monarch, Composio, and Merge Agent Handler fit. - [Why AI Agents Need an Application Map](https://www.monarchagents.ai/blogs/why-ai-agents-need-an-application-map/): An application map connects records, actions, permissions, and validation checks so AI agents can execute workflows with explicit business rules. - [How AI Agents Work With Legacy Systems Without a Suitable Public API](https://www.monarchagents.ai/blogs/why-ai-agents-need-an-application-map-for-legacy-systems/): See how AI agents can use authorised private web interfaces and UI paths in legacy systems, with an application map, approval steps, and verified results. ## Benchmarks Monarch on AutomationBench, published August 17, 2026: https://www.monarchagents.ai/benchmarks/ - What Monarch is: the orchestration layer that sits between the frontier models and the systems they're taking action on. Monarch creates a product graph of all of the private and public endpoints to make agents more accurate and effective at completing enterprise tasks, while enforcing your org permissions and controls. - What was measured: AutomationBench, the public benchmark Zapier built — 591 business workflows across finance, HR, marketing, operations, sales, and support. Three models were tested (Opus 5, GPT-5.6 Sol, Kimi K3), each in two arms: the model alone, and the same model with Monarch, under identical conditions (same tools, same reasoning effort, one attempt, no retries). A workflow counts only when every required effect lands in the real systems and no guardrail trips. - Headline result: +11-23% more work completed with Monarch than the same frontier model on its own. Opus 5 (Max) 44.2% to 54.5% (+23%); GPT-5.6 Sol (xHigh) 42.5% to 47.2% (+11%); Kimi K3 (Max) 37.4% to 41.6% (+11%). - Permissions: every action stays inside the permissions you set, and anything out of bounds is blocked or escalated. Access is granted node by node in the product graph, so the limit lives in the structure, not in an instruction the model can ignore. - These results are the floor, without any business customization. Once Monarch's forward deployed engineering team tunes Monarch to specific use cases and systems, effectiveness continues to improve. - Qualification: these are Monarch's own runs, not Zapier's leaderboard, and each condition is one matched run rather than a replicated study, so the results should be read as directional. ## Key Concepts - Product Graph: A living, machine-readable map of an application's full executable surface (APIs, undocumented endpoints, schemas, business logic, permissions, and human UI paths), kept current as the product changes. - How Monarch differs from iPaaS/RPA: iPaaS connects known endpoints and RPA automates fixed steps; Monarch maps how software actually works and orchestrates workflows across systems, including legacy apps with no API. - Agent compatibility: Works with any agent (e.g., Claude, Codex, Gemini, or internal agents) via a standard MCP server or a browser extension. ## Structured JSON Resources - [facts.json](https://www.monarchagents.ai/facts.json): Canonical company, category, Product Graph, buyer, and resource facts. - [claims.json](https://www.monarchagents.ai/claims.json): Approved claims, do-not-infer guidance, and claim boundaries. - [comparisons.json](https://www.monarchagents.ai/comparisons.json): Monarch vs MCP, RPA, iPaaS, and connector catalog positioning. - [use-cases.json](https://www.monarchagents.ai/use-cases.json): Common enterprise agent infrastructure use cases and relevant graph surfaces. - [product-graph.schema.json](https://www.monarchagents.ai/product-graph.schema.json): Public conceptual schema for Product Graph surfaces, actions, permissions, validation, and drift. - [architecture.json](https://www.monarchagents.ai/architecture.json): Conceptual architecture — the Business Action unit, the discover-to-drift lifecycle, the select/orchestrate/execute separation, and the data boundary. ## Agent Mode Every page has a structured Markdown representation for agents and answer engines. Request it three ways: send `Accept: text/markdown`, append `?format=md` to any page URL, or fetch the file directly under `/agent/`. The human site also exposes a "human / agent" toggle that renders these same Markdown files. - [Home](https://www.monarchagents.ai/agent/home.md) - [Product Graph](https://www.monarchagents.ai/agent/product-graph.md) - [Architecture](https://www.monarchagents.ai/agent/architecture.md) - [For Agents](https://www.monarchagents.ai/agent/for-agents.md) - [Benchmarks](https://www.monarchagents.ai/agent/benchmarks.md) - [About](https://www.monarchagents.ai/agent/about.md) - [Pricing](https://www.monarchagents.ai/agent/pricing.md) - [Healthcare](https://www.monarchagents.ai/agent/healthcare.md) - [Energy & Utilities](https://www.monarchagents.ai/agent/energy.md) - [Financial Services](https://www.monarchagents.ai/agent/financial-services.md) - [Airlines](https://www.monarchagents.ai/agent/airlines.md) - [Security & Governance](https://www.monarchagents.ai/agent/security.md) - [Blog](https://www.monarchagents.ai/agent/blog.md) - [Contact](https://www.monarchagents.ai/agent/contact.md) - [Monarch Australia](https://www.monarchagents.ai/agent/au-home.md) - [About Monarch Australia](https://www.monarchagents.ai/agent/au-about.md) ## Getting started - [Your first 30 days with Monarch](https://www.monarchagents.ai/first-30-days/): The first workflow as the start of a wider business rollout: FDE/FDS delivery, customer training, expansion, and the conditions that start the 30-day guarantee. [Agent view](https://www.monarchagents.ai/agent/first-30-days.md). ## Contact - [Contact Monarch](https://www.monarchagents.ai/contact/): Use the contact page for a fuller inquiry, or the email forms on the homepage and About page. All public forms submit to the same subscription backend. General inquiries: hello@monarchagents.ai ## Additional industry workflows - [Professional Services](https://www.monarchagents.ai/industries/professional-services/): Connect travel, expense, and engagement workflows across the systems your firm already uses. Put AI to work on the administration behind client delivery. [Agent view](https://www.monarchagents.ai/agent/professional-services.md). - [Telecommunications](https://www.monarchagents.ai/industries/telecommunications/): Recover stuck orders and connect provisioning, billing, and customer service. Monarch puts AI to work across legacy telco applications and internal systems. [Agent view](https://www.monarchagents.ai/agent/telecommunications.md). ## Business workflows - [Finance operations](https://www.monarchagents.ai/workflows/finance/): Put AI to work on the follow-through between invoices, purchase orders, receipts, and the ledger. Give your team the evidence to resolve discrepancies and complete approved corrections. - [HR & IT operations](https://www.monarchagents.ai/workflows/hr-it/): Connect the work between HR, IT, and the teams they support. Turn an approved employee change into the right access updates, handovers, and follow-up tasks across your existing applications. - [Procurement operations](https://www.monarchagents.ai/workflows/procurement/): Connect supplier updates to the purchase orders and plans that depend on them. Give buyers and planners a current view of delivery changes, then carry the agreed response through your systems.