1
Agent action ready
Email, CRM, refund, sheet, API
Private beta for action-taking AI agents
Agentic AI Moves Fast. Argos Puts Control In The Loop
Review, edit, approve, or block risky actions before they reach customers, records, or systems - with evidence saved for every decision.
For teams with live or near-live action-taking AI agents.
Start with one workflow where an AI agent can affect a customer, record, refund, spreadsheet, or internal system. We help you put the first approval checkpoint in place.
For technical teams: Argos wraps risky tool calls with one beforeAction() checkpoint, then returns allow, block, escalate, or approval_required.
2
Argos checkpoint
Risk checked before execution
3
Human review
Approve, edit, deny, or escalate
4
Evidence saved
Decision and outcome recorded
Problem
AI agents are no longer just writing drafts.
They are sending messages, updating records, triggering workflows, and touching systems your team depends on. That creates a new kind of risk: not just a bad answer, but an action that should never have happened.
Argos gives your team a checkpoint before the action becomes real.
Interactive simulation
Try the control flow
Choose a risky action and see how Argos pauses it before anything reaches a customer, record, refund, spreadsheet, or internal system.
Step 1 · Agent attempts action
Send client email
Agent wants to send a follow-up email to a high-value customer.
- Tool
- Target
- External customer
- Risk
- High-value account
Action attempted
Agent wants to send a follow-up email to a high-value customer.
Risk flagged
High-value account
Reviewer decision
Sarah, Operations reviewer
Evidence saved
Decision saved with the risk explanation and approval snapshot.
Result: Sent after review
Sarah J. approved the customer email after checking the account context and risk note.
What Argos does
Argos turns risky agent actions into reviewable decisions.
Argos sits between your AI agent and the tools it uses. When an agent tries to take a sensitive action, Argos checks the tool, target, business object, and risk level.
Low-risk actions can continue. Risky actions pause for human approval. Blocked actions stop before they reach the customer or system.
Afterward, Argos saves a clear record of what happened, who approved it, and why.
Evidence packet
Stopped before execution
- 1
AI drafted
- 2
Argos paused
- 3
Human approved
Before executionHuman reviewEvidence saved
Email sent after review
Agent requests permission
beforeAction() carries the tool, target, workflow, and business context before anything executes.
Argos checks context
Argos evaluates the tool, target, business object, and risk level before the action reaches the system.
Risky actions pause
Sensitive actions wait for a reviewer to approve, deny, or escalate with the reason clearly visible.
Evidence stays attached
Argos keeps a clear record of what happened, who approved it, and why.
SDK/API checkpoint
One checkpoint before the action.
Add Argos before the tool call that matters. Your agent asks for permission before it sends, updates, refunds, deletes, or edits something important.
Example: Before An Agent Sends A Customer Email.
Your system still executes the action. Argos controls whether it should proceed, pauses risky actions for approval, and records the evidence afterward.
await argos.beforeAction({
agentId: "sales-agent-01",
workflowId: "client-email-approval",
tool: "email",
action: "send",
targetType: "customer"
});Who this is for
Argos is for teams whose AI agents can act.
If an agent can change something your business depends on, you need a checkpoint before that action becomes real.
Argos is for you if:
- ✓Your AI agent can email customers.
- ✓Your AI agent can update CRM records.
- ✓Your AI agent can edit spreadsheets or trackers.
- ✓Your AI agent can trigger refunds, invoices, or internal workflows.
- ✓Your clients ask, "How do we know the AI won't mess up?"
Argos is not for you if:
- -You only use ChatGPT manually.
- -Your AI does not take actions.
- -You only need prompt debugging or model traces.
Where Argos adds control
Built for the moments where AI mistakes become business problems.
Start with one workflow. Add approval only where risk matters.
Revenue Ops
Control CRM changes before they affect pipeline, forecasting, or customer records.
Example: an agent tries to move a deal to Closed Won. Argos pauses the update and routes it for approval.
Customer Support
Review sensitive replies before they reach customers.
Example: an agent drafts a refund confirmation or policy response. Argos checks the context before release.
Finance
Block or escalate actions involving money movement.
Example: an agent triggers a refund or changes an invoice field. Argos requires finance sign-off first.
Internal Operations
Keep spreadsheets and internal trackers from becoming silent points of failure.
Example: an agent edits rows in an operational tracker. Argos records the change and the approval trail.
Control layer
Not another dashboard after the damage is done.
Observability tools help teams understand what happened inside an AI system.
Argos focuses on the moment before the business action happens.
Instead of only asking “what did the model output?”, Argos asks:
- Should this action be allowed?
- Who needs to approve it?
- What business object is affected?
- Can we prove what happened later?
Primary question
Observability tools
What did the model output?
Argos
Should this action have been allowed?
Primary user
Observability tools
AI engineers and developers
Argos
Ops leads, agency founders, CTOs
Main event
Observability tools
LLM call or trace
Argos
Business action attempted by an agent
Output
Observability tools
Trace, metrics, evals
Argos
Approval decision, risk case, evidence packet
Timing
Observability tools
After execution
Argos
Before risky action + after evidence
Argos complements observability tools. It does not replace them.
Native approvals
Why not just use native SDK approvals?
Native agent frameworks can pause a tool call. Argos gives teams the operational control layer around that pause: policy rules, reviewer routing, an approval inbox, evidence packets, audit-friendly records, and reusable controls across workflows.
Comparison 1
Native HITL approval
Tool-level pause
Argos
Workflow-level policy checkpoint
Comparison 2
Native HITL approval
Developer-managed state
Argos
Approval inbox and decision record
Comparison 3
Native HITL approval
App-specific implementation
Argos
Reusable control layer across workflows
Comparison 4
Native HITL approval
Approval or rejection only
Argos
Allow, block, escalate, approval_required, and evidence
Comparison 5
Native HITL approval
Hard to show clients
Argos
Client-safe evidence packets and reports
Comparison 6
Native HITL approval
Lives inside one agent stack
Argos
Works around custom agents and API/tool calls
Argos complements native approval tools. It does not replace your agent stack.
Pricing
Start with one risky workflow.
One approval checkpoint. Mapped within 7 days. Founder-assisted, not self-serve.
Currently open
Founding Design Partner
For AI agencies and teams deploying agents into live business workflows.
$299/mo
Locked in for the founding scope while your subscription remains active.
We personally help you identify your riskiest AI agent action, wrap it with the Argos SDK, route it through approval, and generate an evidence trail your team or client can trust.
What you get:
- ✓Founder-led onboarding call
- ✓We map your riskiest agent workflow together
- ✓First approval checkpoint configured with you
- ✓Approval inbox for your review team
- ✓Evidence packets for every intercepted action
- ✓Plain-English risk explanations
- ✓API key setup and SDK integration support
- ✓Direct founder access during the pilot
- ✓Your workflow priorities shape the roadmap directly
Pilot scope:
- 1 controlled workflow
- Up to 2 agents
- Up to 3 reviewers
- Email, CRM, Sheets, refund, or internal API workflow
Our commitment: First approval checkpoint mapped within 7 days, assuming access to the workflow and a technical point of contact. If we cannot identify and configure a viable checkpoint with you, you do not continue.
Agency plans start at $999/mo when you expand beyond the founding scope.
Enterprise and self-hosted deployment available on request.
FAQ
Frequently asked questions
How does Argos integrate?
You add Argos before the tool call that matters. Your agent calls beforeAction(), Argos returns allow, approval_required, block, or escalate, and your workflow continues based on that decision.
Do I need to replace my agent stack?
No. Argos is designed to sit around your existing agent workflow. It can work with custom agents, LangChain, CrewAI, LlamaIndex, OpenAI Assistants, n8n, or any system that calls tools or APIs.
Does Argos send the email or update the CRM for me?
No. Your system still executes the action. Argos controls whether the action should proceed, pauses risky actions for approval, and records the evidence afterward.
What data does Argos store?
By default, Argos stores metadata and redacted action summaries only. It should not receive raw email bodies, API keys, credentials, customer lists, or secrets.
Who is Argos for?
Argos is for teams whose AI agents can send, update, edit, refund, delete, or call APIs. It is not for teams only using ChatGPT manually.
Company
Built by Aurevon Technologies Limited
Argos is built by Aurevon Technologies Limited, based in DIFC. We are building infrastructure for safer AI agent deployment - starting with pre-action control, approval workflows, and evidence trails.
Bring one risky workflow.
We will help you map one risky AI-agent workflow, configure the first approval checkpoint, and generate an evidence trail your team or client can trust.
Evidence trail
- 1Action attempted
- 2Approval required
- 3Reviewer approved
- 4Evidence saved