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SOAT vs Vertex AI Agent Builder

Vertex AI Agent Builder is a managed agent platform (Proprietary (ADK is Apache-2.0), managed). SOAT is agent infrastructure (Apache-2.0, self-hosted). Of the 15 capabilities the benchmark tracks, Vertex AI Agent Builder covers 8 natively and SOAT 12.

At a glance​

Vertex AI Agent BuilderSOAT
Typea managed agent platformagent infrastructure
LicenseProprietary (ADK is Apache-2.0)Apache-2.0
Deploymentmanagedself-hosted
Native capabilities8 of 1512 of 15
Last verified2026-08-142026-08-14

Where each one leads​

  • Vertex AI Agent Builder is native where SOAT is not: code execution.
  • SOAT is native where Vertex AI Agent Builder is not: identity & governance, data & secrets, human-in-the-loop, multi-tenancy, declarative deployment.

What Vertex AI Agent Builder is​

Google Cloud's managed platform for building and deploying agents: Agent Development Kit, managed Agent Engine runtime, RAG Engine, and Google Cloud IAM, billing, and observability. Vertex AI Agent Builder documentation.

Capability by capability​

Agent runtime​

Agent loop, sessions, and generation lifecycle.

  • Vertex AI Agent Builder: Native. Agent Development Kit plus the managed Agent Engine runtime with sessions. (source)
  • SOAT: Native. Agents, sessions, chats, and generations with full lifecycle tracking. (source)

Orchestration​

Multi-step pipelines, workflows, and triggers.

  • Vertex AI Agent Builder: Native. Multi-agent composition in ADK (sequential, parallel, loop agents); broader pipelines lean on other Google Cloud services. (source)
  • SOAT: Native. DAG orchestrations, workflow state machines, durable tasks, and triggers (manual, webhook, schedule). (source)

Knowledge & memory​

Documents, embeddings, semantic search, and recall.

  • Vertex AI Agent Builder: Native. RAG Engine and Vertex AI Search for grounding; Memory Bank for session memory. (source)
  • SOAT: Native. Documents with per-chunk embeddings, named memories, unified semantic search, and ingestion rules for PDFs, images, and audio. (source)

Tools & integration​

Tool calling, MCP, providers, and webhooks.

  • Vertex AI Agent Builder: Native. Function tools, MCP support, and prebuilt connectors to Google and third-party systems. (source)
  • SOAT: Native. HTTP, MCP, client, and agent-to-agent tools; model routes with failover; webhooks; any LLM provider. (source)

Identity & governance​

IAM, guardrails, approvals, quotas, and audit.

  • Vertex AI Agent Builder: Partial. Google Cloud IAM, quotas, and audit logging — cloud-level, not agent-action-level; no built-in guardrail/approval queue for tool calls. (source)
  • SOAT: Native. AWS-inspired IAM, actors, scoped API keys, guardrails, human approvals, quotas, and an append-only audit log. (source)

Observability​

Traces, activity, usage, and failure queues.

  • Vertex AI Agent Builder: Native. Cloud Trace/Logging integration and Agent Engine tracing of agent runs. (source)
  • SOAT: Native. Traces of every tool call and model response, activity feed, usage/cost tracking, and an exceptions queue. (source)

Data & secrets​

File storage and encrypted secrets.

  • Vertex AI Agent Builder: Partial. Via adjacent Google Cloud services (Cloud Storage, Secret Manager) rather than the agent platform itself. (source)
  • SOAT: Native. File storage over local/S3/GCS backends and encrypted secrets storage. (source)

Evaluation​

Datasets, scorers, and eval-gated improvement.

  • Vertex AI Agent Builder: Native. Vertex AI evaluation service with agent-specific evaluation flows. (source)
  • SOAT: Native. Datasets, scorers, and scored runs; eval-gated promotion of agent versions. (source)

Channels​

Built-in gateways to messaging platforms and UIs.

  • Vertex AI Agent Builder: Partial. Chat-platform delivery through Conversational Agents (Dialogflow) channel integrations, adjacent to Agent Builder itself. (source)
  • SOAT: Absent. Surfaces are REST, MCP, CLI, and SDK — no built-in gateways to messaging platforms like Slack, WhatsApp, or Telegram.

Code execution​

Sandboxed code or terminal runtimes for agents.

  • Vertex AI Agent Builder: Native. Built-in code execution tooling in ADK and the Vertex AI code interpreter extension. (source)
  • SOAT: Absent. Tool types are HTTP, MCP, client, and agent-to-agent — no built-in sandboxed code or terminal runtime.

Human-in-the-loop​

Pausing a run for human approval, then resuming it.

  • Vertex AI Agent Builder: Partial. Agents on Agent Engine can pause through framework-level checkpoint breakpoints and resume on the same thread, but the platform provides no managed approval queue or tool-call gate. (source)
  • SOAT: Native. Approvals are a first-class human-decision queue with frozen evidence, and guardrails classify each tool call so risky actions pause for a decision. (source)

Multi-tenancy​

Projects or workspaces scoping resources and permissions.

  • Vertex AI Agent Builder: Partial. Isolation comes from generic Google Cloud project-level and per-resource IAM bindings, with no agent-specific tenant, workspace, or namespace construct. (source)
  • SOAT: Native. Projects are multi-tenant namespaces scoping every resource, with IAM policies and quotas enforced per project. (source)

Declarative deployment​

Templates that provision agent resources as one stack.

  • Vertex AI Agent Builder: Partial. Agent deployment is documented as suitable for generic tools such as Terraform, but there is no first-party agent template format with its own plan/apply and dependency graph. (source)
  • SOAT: Native. Formations provision providers, memories, tools, agents, orchestrations, and webhooks from one template, resolving refs into a dependency graph with tracked operations. (source)

Versioning & rollout​

Agent versions, canary rollout, gated promotion.

  • Vertex AI Agent Builder: Native. Updating versioned fields creates an immutable revision with active and deprecated states, and traffic percentages can be split across active revisions for canary rollout and rollback. (source)
  • SOAT: Native. Every config change is archived as an append-only agent version, with canary rollout to a slice of traffic and eval-gated promotion. (source)

Skill learning​

Agents authoring reusable skills from their own experience.

  • Vertex AI Agent Builder: Absent. No first-party mechanism for an agent to author or refine reusable skills from its own experience.
  • SOAT: Absent. Memories and knowledge store retrievable context, but agents do not author or refine reusable skills from their own experience.

How this is rated​

Each rating comes from the public documentation linked beside it: Native is built in, Via plugin needs an add-on, Partial covers part of the capability, Absent is not offered. Every solution side by side is on the benchmark. A rating that is out of date is a bug: open an issue.