Enterprise Use cases and assessment framework for agentic workflow orchestration layer
You decide to implement AI agents in your organisation, demo works exceptionally well. Weeks later, it made into production but the very next day nobody knows why it made a particular decision.
As enterprises adopt AI through AI agents, challenges like end-to-end observability, traceability, testability, governance, and Human-In-The-Loop aspects of the AI system arise. With a widespread adoption of vibe coding, need for a dedicated orchestration platform sounds futile. While this "custom" orchestration software has its own place in the AI ecosystem (For example for adhering with organisation specific policies and tech limitations or extreme scaling scenarios), it generally struggles in complex integration / workflow scenarios where code becomes overly complex and hard to manage/maintain. It is challenging to test each and every part of the orchestration code, conduct experimentation and extend for further integrations / orchestration.The orchestration code also need a compute environment to run, such as containers / VMs or serverless environment (If the steps are fairly straightforward and short-living). These pose challenges like operational scaling, and traceability.
A dedicated orchestration layer platforms provided by third party vendors such as Amazon, Microsoft, n8n, Activepieces, etc can help address aforementioned challenges, particularly during experimentation, or deploying them for executing complex workflow scenarios with human in the loop.
A comprehensive framework and set of considerations, while choosing such layer, along with architectural context is provided as part of this whitepaper to help enterprise:
- Assess the need of a dedicated orchestration layer.
- How to choose orchestration platform.
- Articulate the value and ROI of such a platform to stakeholders.
It's worth noting that all the big players in the market like Google, Microsoft, Amazon are investing in building native orchestration into their AI platforms, which also gives a hint on its importance. Orchestration platforms are equally valuable for deterministic, step-based workflows and not just for agentic AI systems. If you're leading an AI adoption programme or evaluating orchestration tooling for an enterprise context, this whitepaper is written for you.
Download the whitepaper here: <Link>
What topics or considerations would you like to see covered? I'd welcome your thoughts. Please leave a comment below: