Agentic Orchestration: Enterprise AI's Deployment Problem: How SaaS Teams Should Respond
The latest VentureBeat Pulse Research brings critical insights for anyone operating in the software automation and AI space: enterprises aren't struggling with AI platforms as much as they are with deployment. Specifically, when it comes to "agentic orchestration," the ambition of enterprise AI organizations is running significantly ahead of reality. For SaaS teams, this isn't just an interesting trend; it's a clear signal demanding a strategic response in product development, integration strategy, and how we empower our users.
Embrace the Hybrid Control Plane for Integrations
One of the most salient findings is that enterprises are deliberately building hybrid control planes to avoid vendor lock-in, even as agent orchestration consolidates onto model-provider platforms like Anthropic's Claude. For SaaS teams, this means your integration strategy cannot afford to be monolithic or overly reliant on a single AI provider's ecosystem. While certain underlying models may gain traction, the overarching enterprise need is for flexibility.
Your product's APIs must be designed to be agnostic, robust, and accessible to a variety of orchestration layers. Think about how your core functionality can be exposed as discrete actions or data points that an external agent, managed by a hybrid enterprise system, can consume and act upon. This isn't just about offering a webhook; it's about providing a granular, well-documented API that allows for complex, multi-step workflows to be built around your software, rather than forcing enterprises into a specific AI stack.
Move Beyond the Chatbot Wrapper for True Value
The research reveals a stark reality: most deployed "agents" are still effectively chatbot wrappers. While conversational interfaces have their place, the enterprise goal is "reliable multi-step execution." This presents a significant opportunity for SaaS teams to differentiate. Instead of merely integrating a chatbot into your product, consider how your software can become a vital component in genuinely complex, automated workflows.
How can your SaaS provide specific, automatable functions that an orchestration layer can sequence? Can your platform facilitate data enrichment, trigger specific actions based on agent analysis, or provide outputs that feed into subsequent automated steps? SaaS teams should focus on exposing their unique domain logic and capabilities in a way that allows these "agents" to perform meaningful work, moving beyond simple Q&A to actual operational automation within the enterprise's existing processes.
Prioritize Granular Control and Cost Visibility
The lack of real-time fiscal control over token burn is a critical pain point highlighted in the VentureBeat report. While SaaS teams may not directly manage a customer's token burn with a foundational model, there's a clear opportunity to contribute to overall cost visibility and control for AI-driven workflows that interact with your product.
Consider how your product can provide better usage analytics related to AI interactions, especially if your platform consumes tokens or resources from external AI services. Can you offer detailed logs, performance metrics, or even estimated cost insights for actions initiated by agents interacting with your software? Enabling greater transparency and control over the resource consumption of AI-powered workflows will be highly valued by enterprises grappling with the financial realities of AI deployment.
Focus on Your Core Value as an Orchestration Endpoint
The core message is that enterprises have a deployment problem, not solely a platform problem. This means SaaS teams should double down on what they do best: providing robust, reliable software that solves specific business problems. Your product, rather than trying to become the entire AI orchestration layer, should aim to be an excellent, automatable endpoint within an enterprise's broader agentic strategy.
Think about how your software's unique capabilities—whether it's CRM, ERP, HR, marketing automation, or development tools—can be leveraged by intelligent agents to achieve complex business outcomes. This involves clear API documentation, consistent performance, and a willingness to integrate deeply with the tools and platforms enterprises are already adopting for their hybrid AI environments.
How to automate this with Make.com
Responding to the enterprise's need for hybrid control planes and reliable multi-step execution often involves connecting disparate systems – model providers, internal tools, and various SaaS applications. Make.com provides a visual, no-code platform to build these sophisticated workflows. SaaS teams can leverage Make.com to prototype how their product's APIs could interact with various AI models (like Anthropic's Claude, as mentioned), orchestrate data flow between their software and other enterprise systems, or even build internal tools that provide better cost visibility for AI operations. By creating scenarios that demonstrate seamless integration and multi-step execution, SaaS teams can show how their product becomes an integral part of an enterprise's agentic strategy, without requiring heavy development resources for each integration.
FAQ:
Q: What does "agentic orchestration" mean for my SaaS product?
A: It means your product should be designed to be a consumable component within automated, AI-driven workflows. Instead of just offering standalone features, consider how an "agent" could trigger actions, extract data, or process information using your software in a sequence of steps orchestrated by an enterprise's AI system.
Q: How can SaaS teams ensure their products are ready for hybrid AI environments?
A: Focus on creating robust, well-documented APIs that are as platform-agnostic as possible. Avoid deep dependencies on a single AI provider's ecosystem. Ensure your APIs expose granular functionalities, allowing enterprises to build flexible, multi-step workflows that can adapt to their chosen orchestration layers.
Q: Why is "reliable multi-step execution" so important, and how can my SaaS contribute?
A: Enterprises are moving beyond simple chatbots and seek AI that can complete complex tasks across multiple systems. Your SaaS can contribute by providing consistent, predictable API responses, clear error handling, and exposing distinct, automatable actions that an orchestrator can trust to execute correctly as part of a larger workflow.