Beyond the hype: why OpenAI's Agent Builder isn't the enterprise workflow solution you need

The launch of OpenAI's Agent Builder has generated significant excitement. It’s a toolkit that gives developers the building blocks to explore the potential of AI-driven automation. It is, first and foremost, a tool for a technical audience; one that is comfortable with complex setup, intricate prompt engineering, and navigating the nuances of an experimental new technology.

However, a vast chasm exists between a developer toolkit and a production-grade, enterprise-ready platform.

When workflows are mission-critical, enterprises need more than a set of disconnected parts. They need a reliable, secure, and intuitive platform that empowers both technical and business teams to collaborate. They need a solution that handles the complexity behind the scenes.

While OpenAI might provide the workshop for developers, Decision Computing provides the industrial-grade machinery for your entire organization.

At a glance: developer toolkit vs. enterprise platform

Capability	OpenAI Agent Builder	Decision Computing
Target user	❌ Developers. Requires technical expertise for setup, prompt engineering, and connecting components.	✅ Enterprise teams. An integrated platform for both business and technical users, with low-code/no-code interfaces.
Workspace & analytics	⚠️ Single-transaction view. Traces one execution at a time, which is useful for debugging individual transactions.	✅ Holistic system view. Visualizes and analyzes all transactions at once, enabling system-wide performance monitoring and ML-powered discovery.
Data retrieval	⚠️ Component-based. Requires manually connecting separate components like file search, vector stores, and 3rd party databases, which can be brittle.	✅ Native & intelligent. A unified retrieval layer uses a combination of vector, full-text, and SQL search across all data types for robust and precise results.
Multi-modal data	⚠️ Limited. Primarily focused on text and document inputs with expanding capabilities.	✅ Natively supported. Built from the ground up to ingest, search, analyze, and generate outputs across text, documents, images, audio, and more.
Lifecycle & auditing	❌ Build & evaluate. Core focus is on the initial creation and testing of agents.	✅ 360° lifecycle. A complete loop to automate, monitor, improve, and audit with full "time-travel" to reconstruct past states for compliance.
Security & governance	⚠️ Cloud-based. Runs on OpenAI's infrastructure.	✅ Enterprise-grade. Deploys on-prem or in your own Virtual Private Cloud (VPC) with end-to-end encryption and Role-Based Access Control (RBAC).

1. Eliminating the developer burden: automation intelligence

With Agent Builder, your team is constantly responsible for manual, low-level work. This starts with the prompt itself. You don't just tell the agent what to do; you have to manually code who it is and how it should access data. Developers must take care in writing out the necessary context in each prompt, for example “You are a customer retention agent…”. This gets even worse when doing something more complex like querying a database, where brittle instructions and a full database schema are required within the prompt to enable accurate SQL query generation. This makes complex prompt engineering a constant, time-consuming burden.

Decision Computing abstracts this manual complexity. We provide an integrated, native platform where the agent's role context, data schemas, and operating procedures are automatically provided based on the workflow. This Automation Intelligence allows your team to focus on building business value, not writing glue code or tuning brittle prompts.

Decision computing's automation intelligence simplifies prompting

2. Robust retrieval for complex enterprise data

Consider a common task like generating a customer quote. This requires finding contract details, searching a product catalog, and applying specific pricing rules. With Agent Builder, a developer must manually wire together file search with one or more vector stores, custom functions, and database (MCP) connectors. This approach is not only complex to build but is often fragile in production.

Error trying to setup a simple MCP connection in Agent Builder

Our platform solves this with native, intelligent retrieval. Our sophisticated hybrid search layer automatically indexes, understands, and retrieves the exact context your agents need from any data type—be it text, documents, images, audio, or video—providing a unified, reliable source of truth.

3. From single traces to system-wide analytics

OpenAI's Agent Builder confines your view to the internal logic of a single request, showing you a trace of one transaction flowing through the workflow. While essential for debugging a failure, this singular focus provides no insight into the total health or long-term trends of your business process. You are only seeing one tree, not the forest.

A single transaction/chat flowing through Agent Builder's workflow

Our platform provides a single workspace to visualize and analyze all your transactions at once. By aggregating data across every run, we allow you to apply ML components directly across all workflow transactions to spot trends and anomalies, turning automation into system-wide intelligence.

Integrated analytics: Apply ML components like clustering and classification directly across all workflow transactions to spot trends and anomalies.
Unsupervised discovery: Identify new customer segments or detect emergent issues without pre-defined rules.

Decision Computing's Integrated Analytics

4. Beyond text: natively multi-modal AI

Enterprise data is messy and diverse: PDFs, images of defects, compliance call audio, and database records. Whilst OpenAI supports document and image input, our platform was built from the ground up for this reality. We deeply integrate a wide range of data types, allowing your agents to:

Ingest any data type.
Search and analyze across images, audio, and documents.
Generate multi-modal outputs, like reports combining text, charts, and images.

5. The 360° automation lifecycle: automate, monitor, and improve

Building an agent is Day 1. The real work is in managing, monitoring, and improving it over time. Whilst OpenAI's Agent Builder offers logging, tracing and automated improvement for individual agent steps, they stop there.

Our platform provides a complete, enterprise-grade operational loop designed for system-wide governance and mission-critical reliability.

Real-time monitoring: Observe the health of all your automated workflows from a central dashboard and receive alerts when performance degrades or anomalies are detected.
Automated Root-Cause Analysis: When an issue occurs, our platform helps you diagnose the problem by identifying the source of the failure, rather than just flagging the symptom.
Unparalleled auditing with "time-travel": Our high-performance data layer with heavily optimised data transfer and a data lake lets you instantly reconstruct the exact state of your workflow and its data at any point in the past. This is a non-negotiable for compliance, high-stakes debugging, and building true trust in your systems.

Decision Computing's Root Cause Analysis

6. Security & governance: own your deployment

For any serious business application, security is the foundation. OpenAI provides robust security features for data privacy, encryption, and compliance within its cloud environment.

However, for mission-critical enterprise workloads, the requirement often moves from secure in the cloud to secure in our control. We provide the deep controls and deployment flexibility enterprises demand:

Control area	OpenAI Agent Builder	Decision Computing
Deployment location	Cloud-based. Runs on OpenAI's infrastructure.	Your control. Deploys on-premises or in your own Virtual Private Cloud (VPC).
Data control	Data processing subject to OpenAI policies.	Full data sovereignty. Data can remain entirely within your infrastructure and boundaries.
Access & encryption	Encrypted in transit and at rest. RBAC unclear.	Enterprise-grade. End-to-end encryption and granular RBAC across the platform.

From a box of parts to a reliable engine

OpenAI's Agent Builder provides a box of parts for skilled developers to assemble. But enterprises can't run on solutions that rely on endless developer labor.

Enterprises need a reliable, secure, and complete automation engine today. Decision Computing delivers an integrated platform that abstracts away the low-level complexity, empowering your entire organization to build, manage, and trust AI-driven automation at scale.