Use VerifiedX when your agents can:

• update records
• write memory
• change workflow state
• send messages
• call webhooks
• take other high-impact actions that affect business

Wrong actions happen for both adversarial and non-adversarial reasons: content injection (web search results and user-generated inbounds), weak grounding, stale context, drift, overeagerness, and long-term memory poisoning.

What you get

• fewer wrong actions in production
• agents that get the job done without executing actions that fuck you or your users over
• clear decisions your system can act on
• integration in a few lines of code

What decisions are based on

VerifiedX does not judge an action in isolation.

It looks at:

• what the agent is about to do
• what the agent has already done in this run
• the evidence the agent gathered before the action
• upstream context when the run is part of a multi-agent or agent+human system

How it works

1. Get your API key.
2. Add VerifiedX to the runtime or adapter you already use.
3. When an agent is about to take a high-impact action, VerifiedX checks it.
4. VerifiedX returns a decision and clear next steps.
5. The wrong action does not execute and the agent keeps working toward the same goal.

Possible outcomes:

• allow
• allow_with_warning
• replan_required
• goal_fail_terminal

If the action is wrong but the goal is still valid, VerifiedX is built to stop the bad action and send back a replan so the system can keep working instead of stopping.

Works for real agent systems

Built for single-agent, multi-agent, and agent+human systems.

In a single-agent system, that replan loop stays with the same agent.

In a multi-agent or agent+human system, VerifiedX returns the decision in a way that lets the next agent, orchestrator step, or human step take over cleanly.

Works with your stack

VerifiedX works with Python and TypeScript, plus native adapters for OpenAI, Anthropic, OpenAI Agents SDK, Claude Agent SDK, LangGraph, LangChain, Vercel AI SDK, and MCP.