AgentX
A quality-control inspector for AI agents — before your AI assistant goes live and starts talking to real customers, AgentX tests it, points out exactly where it messes up, and suggests a fix, instead of you finding out from an angry customer.
🔗 Visit AgentX
Description
Building an AI agent is one thing; trusting it enough to let it talk to real customers unsupervised is another. AgentX exists for that gap — it's a testing ground where you can run your agent through many scenarios, see exactly where it hallucinates or goes off-script, and get a one-click suggested fix before anything embarrassing happens in production.
AgentX is an AI agent orchestration and evaluation platform: build multi-agent systems with defined roles, instructions, and model choices, then run them through an LLM-as-judge evaluation layer that flags hallucinations and behavioral drift, tracks regressions with versioning and one-click rollback, and inserts human-in-the-loop checkpoints where needed. It integrates with LangChain, CrewAI, the OpenAI Agents SDK, and Google's ADK, deploys agents to API, Slack, web widgets, email, or voice channels, and offers SOC 2 compliance with encryption and role-based access control for teams that need that assurance. Pricing runs free (200 credits) up to Solo Builder ($49/month), Professional ($199/month, white-label), and Business ($299/month, white-label), with custom pricing for managed enterprise engagements.
💬 Our review
The short version: AgentX is aimed at teams who've already built an AI agent and are nervous about what happens the first time it meets a real, unpredictable user — its evaluation and rollback tooling is squarely about de-risking that jump from demo to production.
Compared to dedicated LLM-eval specialists like Braintrust or Patronus AI, AgentX bundles evaluation together with the orchestration and deployment layer itself, which is convenient if you want one platform end-to-end but less appealing if you've already committed to a different agent-building stack and just want a plug-in eval layer. The pricing ladder ($49 → $199 → $299/month) is transparent, which is a real point in its favor versus several competitors in this review batch that don't publish pricing at all — but the white-label features only unlock at the Professional tier and above, worth checking if that matters for a client-facing use case.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Gratuit (200 crédits) ; Solo Builder 49$/mois ; Professional 199$/mois (marque blanche) ; Business 299$/mois (marque blanche) ; sur devis pour un service géré personnalisé
Pros
Évaluation LLM-as-judge intégrée avec détection d'hallucination
Suivi de régression avec rollback en un clic
Tarification publique et claire, contrairement à plusieurs concurrents
Déploiement multi-canal (API, Slack, widget web, email, voix)
Cons
Marque blanche réservée aux paliers Professional/Business et plus
Aucune info publique sur financement ou fondateurs
Moins spécialisé qu'un outil d'éval pur (Braintrust, Patronus) si l'évaluation est le seul besoin