PromenautHow we compare
How Promenaut compares, and how you can check
Most tools answer a build, run or automate question. Promenaut answers a different one. Here is how that lines up against the tools it is measured against, with our claims open to inspection and theirs sourced to their own pages.
Checked against our code
Each Promenaut claim cites the catalogue capability behind it. Open one to read it; the site build fails if a cited capability stops holding.
No self-scores
Tools are placed by the question each one answers, not by marks we give ourselves.
Dated and sourced
Each competitor line links to the vendor’s own page, read in October 2026.
Where rivals win
Each comparison says where the other tool is stronger.
Six questions, six kinds of tool
Each kind of tool answers one question. Comparing across questions is how feature checklists mislead, so each table below compares tools that answer the same one.
Automation
“Automate a task across my apps.”
n8n, Zapier, Make
Agent framework
“Build my own agent’s logic.”
LangChain and LangGraph, CrewAI
Agent runtime
“Host and secure the agent I built.”
AWS AgentCore, Vertex Agent Engine, Azure AI Foundry
Horizontal agent platform
“Spin up an agent fast.”
Lyzr
Suite agents
“Add agents to the suite I already run.”
Salesforce Agentforce, Microsoft Copilot Studio, ServiceNow
Governed digital workforce
“Run a workforce that already does the work, and show how it was governed.”
Promenaut
Promenaut and the agent suites
Salesforce, Microsoft and ServiceNow add agents to the platforms they already run for you. They are serious, well-built products. The difference is where the work runs, and who assembles the workforce.
Promenaut ships a governed workforce of agents, teams and workflows, and can run in your own cloud account.
| What a regulated firm asks | Promenaut | Agentforce | Copilot Studio | ServiceNow |
|---|---|---|---|---|
| Where it runs | In your own cloud account from a shipped kit, including one with no outbound access | Salesforce cloud (Hyperforce), grounded in Data 360Source ↗ | Microsoft cloud; knowledge indexed in DataverseSource ↗ | The ServiceNow AI Platform, with a self-hosted Private Stack offeredSource ↗ |
| Choice of model | Anthropic, OpenAI and Google directly, Amazon Bedrock, or your own AI gateway | Salesforce-managed models, or your own through Bedrock, Azure OpenAI, Vertex AI and othersSource ↗ | Microsoft’s default model, with Anthropic and others available to addSource ↗ | Third-party models by default, with bring-your-own offeredSource ↗ |
| Whose authority an agent uses | For knowledge, a deputy of the person who launched the run, within their permissions | A running user per agent; new agents start with no permissionsSource ↗ | An Entra Agent ID for each agentSource ↗ | The invoking user with roles masked, or a dedicated AI user, set per agentSource ↗ |
| A person decides | Work held for a person’s decision; a sensitive knowledge change needs a checker who did not launch the work | Confirmation in the conversation; approvals built with FlowSource ↗ | Multistage approvals in agent flows, in previewSource ↗ | Each tool set to supervised, where a person approves first, or autonomousSource ↗ |
| Cost before a run | Estimated before launch, against the pool and the business unit’s budget | Flex Credits, metered per actionSource ↗ | Published per-action credit rates, with a credits estimatorSource ↗ | Assists metered daily; usage beyond the entitlement invoicedSource ↗ |
| Evidence from a run | A verdict from each run on the agents that ran, in a tamper-evident ledger | An audit trail of prompts and responses, stored in Data 360Source ↗ | Purview audit of admin, maker and user activitySource ↗ | AI Control Tower: discovery, runtime monitoring and a kill switchSource ↗ |
| Who assembles the workforce | Shipped as modules of agents, teams and workflows, extended with the SDK | Prebuilt templates, assembled in Agentforce BuilderSource ↗ | Templates and Microsoft-built agents, assembled by makersSource ↗ | Prebuilt agents, plus AI Agent StudioSource ↗ |
As of October 2026. Compare one at a time: Promenaut vs Agentforce, Promenaut vs Copilot Studio, Promenaut vs ServiceNow.
Promenaut and the tools you build agents with
Frameworks, runtimes and automation tools are how you build or host agents and flows. They hand you the parts; you supply the work and most of the governance.
Promenaut ships the workforce those tools leave you to build: modules of agents, teams and workflows, with approval, budgets and run evidence around them.
| What a regulated firm asks | Promenaut | LangGraph | AgentCore | n8n |
|---|---|---|---|---|
| What it is | A governed workforce: modules of agents, teams and workflows | An open-source agent framework and low-level orchestration runtimeSource ↗ | Managed services to build, deploy and run agentsSource ↗ | Workflow automation with AI built inSource ↗ |
| Where it runs | In your own cloud account from a shipped kit, including one with no outbound access | The library runs anywhere; LangSmith in their cloud, hybrid or self-hostedSource ↗ | Fully managed and serverless in AWSSource ↗ | Your infrastructure or theirs, including air-gappedSource ↗ |
| Choice of model | Anthropic, OpenAI and Google directly, Amazon Bedrock, or your own AI gateway | Any model provider, through a standard interfaceSource ↗ | Any foundation model, in or outside BedrockSource ↗ | Any model, cloud or offlineSource ↗ |
| Who builds the work | Shipped as modules of agents, teams and workflows, extended with the SDK | You build the agents and the graphsSource ↗ | You build or bring the agentsSource ↗ | You build the flows, from a large template librarySource ↗ |
| A person decides | Work held for a person’s decision, approved or rejected with its history kept | Interrupts pause a run and wait for a personSource ↗ | Inline functions hand a call back to your code for approvalSource ↗ | A review step before chosen AI tools runSource ↗ |
| How cost works | Credits by each agent’s tier, estimated before launch | A free library; LangSmith per seat and usage, cost tracked per traceSource ↗ | Pay per use, by the second and per requestSource ↗ | Free to self-host; paid plans per workflow executionSource ↗ |
| Governance around it | Deputy access to knowledge, budgets per business unit, and a verdict from each run | LangSmith tracing of each step, with evaluationsSource ↗ | Agent identity, policy on tool calls, and traces in CloudWatchSource ↗ | Role-based access, SSO and audit logs on enterprise plansSource ↗ |
As of October 2026. Compare one at a time: Promenaut vs LangGraph, Promenaut vs AgentCore, Promenaut vs n8n.
How to read this
Tools are compared with tools that answer the same question. Our cells cite the capability behind them; open one to read it. Their cells link to the vendor’s own page, read in October 2026, and vendors move quickly, so check the date. Where a line could not be sourced from the vendor, it is not here.
Compare it on your own work
Bring one process and the tool you are weighing us against. We run the comparison on your material, with the people who would use it.
