AgentX
Visual multi-agent builder with built-in evaluation and deployment.
AgentX's built-in evaluation and white-label deployment make it a strong pick for agencies and solo devs deploying production agents. The managed service is a rare differentiator for ops teams. However, limited native integrations and a tight free tier mean it's not for everyone. Evaluate against Relevance AI for integration depth.
Verified 9d ago · liveness 70/100 · cite: rightaichoice.com/tools/agentx
- Solo developers building production-ready AI agents with evaluation and deployment built in.
- AI agencies deploying agents under their own white-label brand for clients.
- Operations leaders wanting to automate manual processes without building themselves.
- Teams needing built-in evaluation to catch agent hallucinations before production.
- Users needing deep pre-built integrations with Salesforce, HubSpot, or similar CRMs.
- Those looking for a no-code platform with no technical skills (builder track still requires logic design).
- Teams that require on-premise deployment for the builder track (only managed service offers on-prem as of now).
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Skip AgentX if you need deep native integrations with Salesforce, HubSpot, or Zendesk, or if you require multi-language support out of the box.
Overage credits at $10 per 1,000 after monthly allowance
AgentX's credit-based model is transparent but can become expensive for high-volume usage. Solo Builder at $49/mo with 5,000 credits is competitive for solo devs, while agencies should budget $199-$299/mo plus overages. Managed service pricing is custom. Compared to Relevance AI (starts at $20/mo per agent) or Custom GPTs (free with ChatGPT Plus), AgentX is pricier but includes evaluation and deployment tooling.
In short
AgentX — Visual multi-agent builder with built-in evaluation and deployment. Best for Solo developers building production-ready AI agents with evaluation and deployment built in., AI agencies deploying agents under their own white-label brand for clients., Operations leaders wanting to automate manual processes without building themselves.. Free to start; paid plans from $49/mo.
What's new in AgentX
Checked 18 days agoAcross the latest 5 updates: 2 feature updates, 2 changelog entries and 1 news mention.
GPT-4.1: Smarter, Faster, and More Capable
GPT-4.1 model added to AgentX platform, offering improved speed and capability for agent tasks.
How AgentX Charges for AI Usage
AgentX published its credit-based pricing model for AI usage, detailing consumption rates per model.
Understanding the Differences Between Meta Llama 3.2 3B, Llama 3.2 11B, and Llama 3.3 70B
Guide comparing Meta Llama model variants available on AgentX for optimal model selection.
Understanding the Differences Between Claude 3.5 Haiku, 3.7 Sonnet, and 3 Opus
Guide comparing Claude model variants available on AgentX for performance and cost trade-offs.
Connect Your AgentX AI Agent with Notion and Expand Its Knowledge
New Notion integration allows AI agents to access and learn from Notion workspaces.
Viability Score
How likely is AgentX to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Visual drag-and-drop multi-agent workflow builder
- Built-in evaluation framework with test sets and regression tracking
- One-click deploy to API, Slack, web widget, email, voice
- Versioned deployments with rollback and run logs
- Human handoff checkpoints in workflows
- White-label deployment for agencies with custom branding
- Dedicated client workspaces for agency clients
- Bring your own model (BYOM) or use AgentX models (GPT-4.1, Claude 3.7 Sonnet, Gemini Pro, Llama 3.3 70B)
- SOC 2 compliance controls, RBAC, and encryption
- Managed automation service (AgentX builds and runs your process)
- Cloud or on-premise deployment options (managed service only)
- Agent templates library for quick starts
- Notion integration for knowledge access
- Credit-based pricing across all models (no per-API fees)
- Demo evaluation mode
About AgentX
AgentX is an enterprise platform for orchestrating, evaluating, tracing, and observing AI workforces. It provides a visual drag-and-drop workflow builder to design multi-agent systems with tools, memory, branching logic, and human handoff. The built-in evaluation framework lets you test agents against test sets before deployment, tracking regressions and catching hallucinations or broken tool calls. Once ready, you can deploy agents in one click to API, Slack, web widget, email, or voice, with versioned deployments and rollback. AgentX also offers a managed service where they scope, build, and operate automations for you. The platform uses a credit-based pricing model across supported models like GPT-4.1, Claude 3.7 Sonnet, Gemini Pro, and Llama 3.3 70B. Trusted by 150,000+ users, it's ideal for solo developers, agencies, and operations leaders who prioritize evaluation and deployment reliability over deep native integrations.
Behind the Verdict
AgentX differentiates itself from most agent builders by treating evaluation and deployment as first-class citizens, not afterthoughts. If you're building agents that must work reliably in production—especially for clients—the built-in test sets, regression tracking, and one-click deploy to multiple channels are genuine time-savers. The white-label plans (Professional at $199/mo, Business at $299/mo) let agencies deploy agents under their own brand with dedicated client workspaces, which is a clear advantage for reselling. For operations leaders who'd rather not build at all, the fully managed service (scoped per process, cloud or on-prem) is a rare offering—most competitors expect you to build yourself. That said, AgentX's native integration list is short: Slack, Notion, email, web widget, and voice. If you need deep CRM, ERP, or database connectors, you'll have to build custom integrations via API. The free tier is genuinely limited (200 one-time credits, 5 agents max), so it's more of a trial than a usable free plan. Compared to Relevance AI, AgentX leans harder on evaluation and managed service, while Relevance has a richer integration ecosystem. We'd pick AgentX when quality assurance and white-label client delivery matter most, and pass on it when you need out-of-the-box connections to Salesforce, HubSpot, or similar tools.
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Real-world workflow fit
Concrete scenarios for the personas AgentX actually fits — and what changes day-one when you adopt it.
You build a multi-agent workflow with a front-line FAQ agent and a handoff to a human agent for complex queries. You evaluate against a test set of 100 support tickets, then deploy via web widget on your site.
Outcome: Agent handles 80% of incoming queries, reducing support ticket volume by 60%. Runs on Solo Builder plan ($49/mo + ~$30 overage).
You create dedicated workspaces for 5 clients, each with custom-branded agents. You use white-label deployment and bill clients monthly. Professional plan ($199/mo) covers all workspaces.
Outcome: Scalable client management with no per-client platform fee. Each client sees your brand, not AgentX. Total monthly cost ~$349 including overage credits.
You engage AgentX's managed service to scope, build, and deploy an invoice extraction and routing automation on-premises.
Outcome: Automation processes 500 invoices/month, reducing manual effort by 90%. Fixed scope, clear success criteria, delivered in weeks. Custom pricing.
Use Cases
- Answering common customer support FAQs on a website
- Qualifying leads via Facebook Messenger chatbot
- Providing 24/7 automated responses for e-commerce stores
- Collecting feedback through conversational surveys
- Automating back-office document handling and data extraction
- Automating inbound email triage and response
Models Under the Hood
as of 2026-07-14
Limitations
- AgentX offers a visual multi-agent builder with built-in evaluation and one-click deploy to API, Slack, web, and voice.
- The free tier provides only 200 one-time credits, insufficient for ongoing use.
- On-premises deployment is available only via the managed service, not the builder track.
- Credit costs can accumulate quickly for high-volume agents (e.g., $10 per 1,000 credits overage).
as of 2026-06-26
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published AgentX tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Solo developers learning the platform and building a first prototype agent.
What this tier adds
Starting tier with 200 one-time credits, 5 agents, 1 workspace, and 1 seat. No production deployment.
Solo Builder
$49/mo
Ideal for
Solo developers shipping agents to production with moderate usage (up to 5,000 credits/month).
What this tier adds
Adds unlimited workspaces, 25 agents, 5,000 monthly credits, production deployment, and demo evaluation mode.
Professional
$199/mo
Ideal for
Small agencies starting client work with white-label deployment and client workspaces.
What this tier adds
Adds white-label deployment, client workspaces, 10,000 credits/month, 2 seats (expandable at $10/mo each).
Business
$299/mo
Ideal for
Agencies scaling client work with priority support and unlimited agents.
What this tier adds
Adds unlimited agents, 20,000 credits/month, priority support and SLA.
Enterprise
Custom
Where the pricing makes sense
The company stage and team size where AgentX's pricing actually pencils out — and where peers do it cheaper.
AgentX's credit-based model is transparent but can become expensive for high-volume usage. Solo Builder at $49/mo with 5,000 credits is competitive for solo devs, while agencies should budget $199-$299/mo plus overages. Managed service pricing is custom. Compared to Relevance AI (starts at $20/mo per agent) or Custom GPTs (free with ChatGPT Plus), AgentX is pricier but includes evaluation and deployment tooling.
Setup time & first value
How long it actually takes to get something useful out of AgentX — broken out by persona, not the marketing-page minute.
Solo Builder: 30 minutes to sign up, pick a template, and deploy a first agent to Slack or web widget. Agencies: 1-2 hours to configure white-label branding and client workspaces. Managed service: 2 weeks from scoping session to production deployment.
Switching to or from AgentX
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From custom code: Manually export workflows as JSON, then import into AgentX's visual builder
- →From Dialogflow: Rebuild intents as agent workflows; AgentX's builder supports branching logic
- →From Custom GPTs: Export GPT configuration (if available) and recreate with AgentX's multi-agent capabilities
- ↗To Relevance AI: Export agent definitions via API; rebuild workflows on Relevance AI's platform
- ↗To custom deployment: Use AgentX's API logs and run traces to reconstruct logic in Python/Node.js
- ↗To open-source frameworks (LangChain, CrewAI): Translate visual workflows into code using framework SDKs
Integrations
Resources & Guides
Official links
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