How Malleable compares

Agentic operations, maintained by the people who run them.

Most tools make you choose between an open-ended AI agent and a fixed automation flow. Malleable brings the best of both. The AI follows the steps your team set and uses judgment only where you allow it. When the work changes, your team changes the steps in plain English.

Three ways teams do this today

Open-ended agents

You give an AI agent instructions and tools. It works out the steps itself, every run.

ChatGPT, Claude, Microsoft Copilot Studio, Google Gemini Enterprise, ChatGPT Workspace Agents, Salesforce Agentforce, ServiceNow, Glean, Lindy, Coworker, Manus, OpenClaw

Malleable vs. AI agents and assistants →

Fixed automation flows

A builder draws every path ahead of time. AI can fill in a step, but the drawn paths decide what happens next.

Zapier, Workato, Parabola, Power Automate, n8n, Fillout, Zapier Forms

Malleable vs. automation platforms →

Custom software

Engineers, a consultant or a vibe-coding tool writes software around your process.

Internal technical team, External consultant, Vibe-coding tool

Malleable vs. building it yourself →

Malleable

How Malleable does it

Your team says which steps always run the same way and where the AI can use judgment. One agent follows those steps for the whole run.

agent log · live

Reading purchase request · alex@acme.com

Pulled team Slack · checked spend policy · cross-referenced budget

Logging to request tracker · row 47automatic

Over the auto-approve limit. Ask @eric to approve?

Routed to @eric for approval · request marked pending

Each step has its own limits: what it has to get done, which apps it can use, and whether the AI can use judgment there.

A supplier emails an invoice, and the price is higher than on the purchase order.

Open-ended agents: The agent starts fresh each time, reading the invoice and deciding what it should run. It sometimes has notes for itself, but each run can influence another and there's no audit trail along the way.
Fixed automation flows: The flow runs the same path every time. An AI step can read the invoice, but if nobody built a path for a price change, the run stops or takes the default branch, and someone has to sort it out by hand.
Custom software: Engineers write code for each check, and it does exactly what it was written to do. When the controller adds a rule, it waits on a ticket for whoever maintains the code.
Malleable: Matching the invoice to the purchase order runs the same way every time. The AI decides whether the new price looks like a mistake, using your price list. Anything over a set amount goes to the controller, as a form with the invoice, the purchase order and a recommendation.

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