AgentNeo builds AI agents with the operational rigor of enterprise systems, and open-sources the safety patterns needed to run them in the real world.
Personal AI copilot. Single-operator tooling — runs locally, posts on behalf of one human.
Luz Vera
Our most advanced agent — an AI-native creator demystifying agents
dame5
Turnkey reputation management for local businesses
Despachate
Import-regime comparator with an AI copilot
ReaKtiva
Reactivate your dormant client base on WhatsApp with AI
Meta Tech Provider · WhatsApp Business PlatformAKtivate
Cold-outbound campaign engine — AI that prospects and books on WhatsApp
Meta Tech Provider · WhatsApp Business PlatformThe safety layer between an AI agent and the strangers it talks to.
Put an AI agent on a public channel — a WhatsApp line, a support chat — and it can leak private data or get prompt-injected by anyone who messages it. You can't stop the model from drafting a reply; by then the draft exists.
So instead of sending it, we hold it — and a senior AI agent audits it first.
Human-in-the-loop approval gates are well established. The twist: the reviewer is a senior AI agent, not a human — so it scales. Junior drafts, senior approves. Tested live against system-prompt extraction, instruction-repeat, and social-engineering attacks — none got through.
The portable runtime our agents are built on — a single, vendor-neutral chassis you run yourself.
Most agent runtimes are a thin loop around one vendor's SDK. NEO Portable puts the model behind an interface: the same agent loop has run end-to-end against local and frontier models alike — proven, not claimed. Swap the brain, nothing else changes.
Every tool call passes through a held-by-default gate — nothing runs unless it's explicitly allowed. Safety designed in, not bolted on.
Cheap local models do the leaf work; a frontier model is lit up only when judgment is required — so it runs anywhere you do and costs nothing when idle. The safety membrane is the same pattern we open-source as Agent Audit Gate.