Every agentic orchestration vendor claims to provide hundreds of “integrations.” Most of them are lying.
Though not on purpose. In recent years, conceptions of what constitutes an integration capable of powering reliable AI agents—to say nothing of autonomous agents—have become… muddy.
Ask many agent providers what autonomous agents require, and they’ll tell you: “connection.”
And this is what they’re selling, in the way of integrations: connectors: thin pipes between systems that can authenticate, sync a field, and trigger an event—but that don’t give you or your AI agents anywhere close to what’s required of doing real enterprise work.
And the gap between what vendors are promising and what they're shipping? It’s about to become very expensive for the enterprises that bought the pitch. Certainly it pays to know the difference.
Enterprise work is never as simple as vendors make it sound. It’s actually very difficult to facilitate any kind of work “end-to-end.”
Of course, that’s a big part of what makes the agentic era so exciting: the very real potential of agentic technology to finally do just that. But the solution to this “Last Mile Problem” is necessarily sophisticated and specific, dependent at once on technology advances hard-won over decades and applications of that technology implemented strategically, at the process level.
This is why the state of the agentic orchestration market is a problem. There have emerged a number of agentic products promising buyers that they have the solution to the LMP but that in fact offer very little that’s actually new.
Nowhere do you see this more clearly than the way agent vendors are dressing up their “integration” offerings.
Deep, reliable integrations are infrastructural to agentic work, perhaps the number one enabler for the agentic workforce.
But most of the “integrations” that vendors are promoting aren’t what they seem. They’re connections facilitated through third parties. iPaaS technology is one example. MCP and AI-powered CLI tools are another.
What’s the matter with this?
Well, iPaaS, CLI tools, the MCP…these means of connection are concerned only with access. This is not a bug; these tools were not designed to provide anything other than that. Rather, they were designed to be used by human developers under the assumption that those developers would apply best practices in using them—and, moreover, that they’d use them effectively at their own risk. This makes them useful as tools for developers—but insufficient for the task of instrumenting AI agents for sensitive, enterprise-grade work.
Why, exactly? Because instrumenting AI agents for sensitive, enterprise-grade work requires something more than simple connection.
AI agents are not mere tools; they are intelligent entities, like humans in many of the ways that matter for knowledge work. To equip them to conduct complex work, they need more than mere access to systems. They need structure, policy, approval matrices, org charts, access controls, context, instructions, goals, and more.
What’s dangerous about the way orchestration vendors have begun marketing their “integrations” is that it suggests connection is all you need in order to set AI agents up for autonomous work. Consider for a moment how crazy that is. It’s the technical equivalent of giving a contractor you’ve never met the master keys, a corporate Amex, admin-status inside your ERP, telling them to get to work, and simply trusting that things will go well because you’ve (and they’ve) been told they’re competent.
So what is an enterprise-grade integration, actually? What do integrations need to provide AI agents in order for them to be able to complete work autonomously?
To start: the type of structure and support that human employees require.
Not mere plumbing—but process-level governance.
Not mere connection—but context.
A connector of the sort provided by an iPaaS tool or MCP is just a way for two systems to talk to each other, and usually exposes basic access to an API, event, or object. It can authenticate, share a field, trigger an event, or sync a record. That was table stakes 10 years ago.
What vendors don’t want you to ask is:
An integration is something much more substantial. An integration interprets the underlying schema or data model, understands user permissions and object relationships, operates within complex business logic, and maintains state inside connected systems.
In enterprise environments, systems rarely use clean, out-of-the-box schemas. They have custom objects, conditional fields, nested records, line-item structures, and bespoke, business-specific metadata. A connector may be able to pass a field value from one system to another, but AI agents need means of understanding how those fields relate to the underlying business object, what combinations are valid, and what additional context is required for the transaction to be successful.
But how, then, can you provide agents with integrations so capable?
The orchestration layer is, in the most basic sense, a system that sits above your organization—in its own operational layer, effectively above your tech stack, org-chart, policies and data systems. It gives enterprise teams a bird’s eye view into their operations, and provides a means of coordinating work across all of these enterprise components.
An orchestration layer doesn’t simply connect these systems. It helps enterprise ops teams govern and facilitate work across systems, at the process level, in accordance with policy. It guarantees agents access while guaranteeing humans control.
Let’s see how this applies in a specific vertical, such as procurement.
Let’s say a business stakeholder submits a request for a new software vendor in Slack. A connector can move that request into a queue. That’s a simple transaction.
A real integration, facilitated through an orchestration layer, does much more. In accordance with every internal policy relevant to the process in question, it allows an agent or automation to:
And that’s to say nothing of proactivity. AI agents instrumented via MCP/CLI/iPaas will be able to ascertain, for example, when a purchase request exists. The latter will know in real-time not only when a purchase request has been submitted but whether the supplier is already onboarded, whether budget is available, whether the contract is missing a required clause, and whether the request needs finance and legal review in a specific order.
And all the while, because this is happening in real-time through an orchestration layer, it’s producing context—or, insight into how decisions get made internally and why work happens the way it does—which AI agents use to do things like autonomously navigate exceptions, edge-cases, and other Last Mile complications.
Integrations provided through a dedicated, enterprise-grade orchestration platform are stateful. They can help an agent track where a request sits across multiple systems, detect data changes, reconcile sometimes conflicting updates, and resume execution when something fails or stalls.
These are the type of integrations Tonkean provides. Rather than relying on third-party workflow or integration layers for core operational connectivity, Tonkean provides native integrations with every piece of technology in your tech stack, from major ERP platforms—oncluding SAP S/4HANA, SAP ECC, SAP Ariba, Oracle ERP Cloud, and Workday—to communication apps and everything in between. These are direct, no-code integrations built into Tonkean's integration library. They’re not reliant on middleware.
"Here's the question to ask your next agentic orchestration demo: Show me your agent updating a custom field in our SAP instance, routing the request through our approval matrix, and writing the result back without a human touching it.
If the vendor's answer involves their iPaaS partner, an MCP server, or a list of CLI tools, they're selling you a connector. If they can do it on their own platform, governed by your policies, with state preserved across the systems involved — that's an integration.
The difference will define which agentic platforms survive contact with enterprise reality, and which ones quietly disappear from RFPs in 18 months.
Want to learn more? Dive into Tonkean Agentic Orchestration here.
