Why ActaFlow
Control
Your business needs
more than a prompt.
Automate business processes with an approved workflow. ActaFlow checks accounts, permissions and approvals before each action on your integrations.
Between each step, we are there.
Email, CRM and documents: each step has its own permissions. Explore the workflow to see which actions are allowed and which require your approval.
Read the customer detailsRead onlyWhat ActaFlow checks
AI cannot add operations or accounts to this step’s permissions.
How you work today
Before sending an offer, I check the customer’s contract and want to review the proposal.
How it becomes a workflow
- Check the contract in the CRM
- Prepare the proposal using your sources
- Wait for your approval before sending
Your method. Not the agent’s.
Turn your experience into a workflow without writing code. Describe your criteria and decisions, add your sources and approve the steps: you define the method instead of leaving it for an agent to interpret.
The agent interprets. You define the process.
Room for AI. Authority in software.
AI interprets, reasons and prepares the work. It can choose how to process the content; permission to act on your integrations comes from the approved workflow.
Software checks access. Not another AI giving the go-ahead.
AI works on the content
Interprets the request. Reads the documents. Prepares a response.
ActaFlow checks the action
Checks the account, operation and approval. Rejects anything outside the permissions of the step.
Instructions and permissions are different things.
Compare how limits are enforced. An agent can be built with robust software controls: the comparison below concerns an agent governed only by instructions and an ActaFlow controlled workflow.
| Instructions to the agent only | ActaFlow workflow | |
|---|---|---|
| Tool access | Instructions to the agent onlyThe prompt specifies which accounts and operations to use. | ActaFlow workflowThe backend checks the account and operation authorized for the step. |
| Before sending | Instructions to the agent onlyThe prompt asks the model to remember to seek confirmation. | ActaFlow workflowSteps requiring confirmation wait for valid approval of that request. |
| Next step | Instructions to the agent onlyThe model chooses which tools to call next. | ActaFlow workflowEvery step has its own permissions. One step’s permissions do not extend to the next. |
| If it misreads the context | Instructions to the agent onlyThe action depends on the model’s interpretation. | ActaFlow workflowA proposal outside the step’s permissions is rejected. An error within the scope is still possible. |
Concrete cases. Clear answers.
The accounts, sources and boundaries of the controls: what you need to assess the difference.
59 requested. Around 500, according to the account.
Sirio Berati, founder of Enhancor AI, says in the video that he has worked with APIs and agents for years. He says he requested 59 video generations and discovered around 500, with over $5,000 in charges. He also describes receiving an agent report that conflicted with what the provider later told him. The business concern is concrete: request limits must be checked before sending, and reports must be verified against actual operations.
ActaFlow has not verified this account: we do not have the original invoices, requests or logs. We do not attribute intentions to AI.
Watch the original accountSirio Berati describes his work at EnhancorAn address shared. A permission misunderstood.
Matt Robb said Muse, Meta’s agent, had shared his address with a Marketplace buyer without the approval he expected. In a later update, he explained that he had selected “Allow Always”, thinking offers would still need confirmation. The case highlights why the scope of a permission must be clear.
This account includes Robb’s September 29, 2026 update, as reported by Moneywise.
Read the case and its updateMeta: how it describes Muse controlsDoes it need more setup than an agent?
Defining a workflow takes more initial attention than a broad request to an agent. It makes the criteria, resources and approvals that matter to you visible. Start with your words, without programming the control system. When your way of working changes, review the workflow: the approved configuration remains the reference for execution.
Can I trust an AI-written activity report?
An AI-written summary is an explanation to compare against recorded operations and provider outcomes. You do not need to know every step of the model’s internal reasoning to check a request: account, operation, parameters, approval and limit are verifiable data. If the outcome of an external action is uncertain, ActaFlow stops automatic replay: blindly retrying could duplicate it.
When could an agent be enough?
Research, drafts or occasional tasks you can review before using them. An agent with appropriate controls can also be a valid choice: consider who configures them, where they are enforced and who maintains them.
What risks remain, even with these controls?
ActaFlow does not make AI infallible. An error can still occur within an authorized action. Plan AI capacity is separate from external service charges: there is no universal spending cap for every API. Providers may charge for work already accepted before a stop. Integration permissions do not automatically classify every piece of sensitive data, for example inside a web search. More sensitive processes need an appropriate scope and approvals at the points that matter.
Sources and comparison criteria
This page is published by ActaFlow and describes our approach. OpenAI documentation acknowledges prompt injection and unintended action risks, and also describes approvals and software controls. We do not claim that all agents lack them. The video is a separate personal account, not an independent technical verification.
OpenAI: agent risks and safetyOpenAI: controls and approvalsYour experience. Your rules. Your workflow.
Describe a business process, connect your tools and choose the approvals. Your first workflow starts with the way you work.