The execution layer for AI agents handles verification, payments, phone calls, and the edge cases that stall autonomous workflows mid-task.
SAN FRANCISCO, CA — ActionLayer emerged from stealth today, opening a waitlist at [actionlayer.io](https://actionlayer.io) for what the company calls “the execution layer for AI agents.” The platform takes over the unglamorous middle of an agent’s job — verification codes, payments, negotiation, phone calls, and the edge cases that stall autonomous workflows — and is designed to work with leading agent stacks and frameworks, including OpenClaw, Claude Code, Hermes Agent, and Google Gemini.
“Most AI agents quit at the hard part. We make it happen,” said a spokesperson for ActionLayer, which is operating in stealth ahead of public launch. “We’re the missing piece between ‘agent demo’ and ‘agent in production.’ Your agent’s agent.”
Closing the demo-to-production gap
Agent demo videos look effortless. Production reality is harder. AI agents routinely break on the unglamorous middle of a task: a 2FA code that arrives by SMS, a checkout page that demands a real card, a vendor that only takes phone calls, an off-platform workflow with no clean API, an edge case the model has no template for. Today, those moments end the workflow — or fall back to a developer at 2 a.m.
ActionLayer is built to absorb exactly those moments. A user gives their agent a goal in plain English. ActionLayer figures out what needs to happen, handles the parts that usually break an agent — verification, login codes, payment, negotiation, off-platform errands — and reports back when the task is done. When the model alone can’t carry the workflow, ActionLayer takes over, all within budgets and guardrails the user has set.
The result is autonomy that doesn’t quietly fail at minute seven of a 40-minute workflow.
Built to work with the agent stacks developers already use
Rather than asking teams to rebuild around a new framework, ActionLayer is designed to work alongside the stacks already in production. The platform is compatible with leading agent frameworks, including OpenClaw, Claude Code, Hermes Agent, and Google Gemini — no rewrites, no glue code.
“What holds back useful agents isn’t more model intelligence — it’s an execution layer that finishes what the model starts,” said Jose Antonio Rey, a member of ActionLayer’s founding team. “We built ActionLayer so the agent doesn’t have to be the smartest entity in the room. It just has to finish the job.”
Waitlist and early access
ActionLayer is in pre-launch. Developers, founders, and teams shipping agentic products can:
– Join the waitlist** at [actionlayer.io](https://actionlayer.io)
– Request early access** by emailing [hello@actionlayer.io](mailto:hello@actionlayer.io) with details on their use case and the workflows they need to put into production
Priority is being given to teams already running agent products with real users, where the cost of an agent stalling mid-task is measurable. Onboarding includes per-workflow configuration of budgets, guardrails, and approval policies.
About ActionLayer
ActionLayer is a San Francisco–based startup building the action layer for AI agents. The platform lets agents take real-world actions end-to-end — signing up, verifying, paying, negotiating, and finishing the task — within budgets and guardrails the user sets. Team and funding details will be announced at public launch.
Media Contact
Jose Antonio Rey
ActionLayer
[press@actionlayer.io](mailto:press@actionlayer.io)
[https://actionlayer.io](https://actionlayer.io)
