AgentX

What is AgentX?

AgentX is a web platform for building and running AI agents, from single chatbots to multi-agent teams. It covers design, evaluation, deployment, tracing and monitoring in one place.

You build workflows in a drag-and-drop editor, giving each agent a role, model, memory and tools. AgentX Inc. says it started in early 2023 with backing from Plug and Play. The service was live in October 2026.

Key Features

• Multi-agent orchestration: AgentX chains several agents on a drag-and-drop canvas, each with its own role, model, memory and tools. An orchestrator agent hands work to workforce members, and branching logic plus human handoff steps cover tasks a single chatbot cannot finish.
• Evaluation suite: AgentX scores agents against test datasets before release, flagging regressions and hallucinations. Scoring runs at both step and outcome level across multiple runs, and the company describes the process as a CI/CD pipeline for continuous improvement.
• Framework-agnostic tracing: The trace pipeline logs prompts, model calls, tool calls and decisions for every run. It also accepts agents built with LangChain, CrewAI, the OpenAI Agents SDK, Anthropic tools or Google ADK, so existing code can be observed without a rebuild.
• One-click deployment: Finished agents publish to an API, Slack, Discord, email, voice or an embeddable web widget in a single step. Shopify, WordPress, Wix and Squarespace are also listed as website platforms, along with Zapier for wider automations.
• Versioned releases: Each deployment is versioned, and AgentX says a faulty release can be rolled back with one click. This gives teams a safety net when a prompt or tool change behaves differently in production than it did in testing.
• Runtime monitoring: An LLM-as-judge reviews live agent behaviour around the clock after launch. Problems that slip past pre-release testing can therefore surface from real conversations instead of waiting for customer complaints.
• White-label workspaces: The Professional and Business plans let agencies resell agents under their own brand. Separate client workspaces keep each customer’s agents and settings apart, which suits consultancies managing several accounts.
• Security controls: AgentX states SOC 2 controls with audit trails, role-based access and encryption in transit and at rest. Enterprise buyers can add SSO, dedicated infrastructure and an on-premise option for stricter data requirements.

Pros

• Full lifecycle coverage: Building, testing, deploying and monitoring sit in one product, so teams avoid stitching several tools together. Directory reviews single this out as the main difference from builders that stop once an agent is created.
• Works with existing code: Tracing and evaluation accept agents from LangChain, CrewAI and other frameworks. Developers can add AgentX observability to a working system without rewriting it inside the visual editor.
• Free starting point: The free plan gives 200 one-time credits, up to five agents and API access with no card required. That is enough to design a workflow and run a small evaluation before paying anything.
• Wide channel reach: One agent can go live on Slack, Discord, email, voice, a web widget or an API. Teams serving customers in several places can reuse the same logic instead of rebuilding it for each channel.
• Agency friendly: White-label deployment and client workspaces on the $199 and $299 plans suit consultancies. Agencies can build an agent once and hand branded versions to clients without exposing the AgentX name.

Cons

• No free production: The free plan cannot deploy agents to production. Any live use, even a small internal bot, needs at least the $49 Solo Builder plan, so the free tier works only as a sandbox.
• Credit-based billing: Usage draws on monthly credit allowances, which makes the total cost harder to forecast. Busy multi-agent workflows and repeated evaluation runs can use credits faster than a simple chatbot would.
• Steep plan jump: White-label features start at $199 a month, about four times the $49 Solo Builder price. Small agencies have no middle tier between solo use and full reselling, which raises the cost of a first client project.
• Learning curve: Multi-agent orchestration, evaluation datasets and tracing take time to learn. Directory reviewers note that newcomers may struggle, so non-technical users should expect some trial and error before the first reliable workflow.
• Thin independent reviews: Independent user reviews of AgentX remain scarce, and directories such as GetApp still show older prices. Buyers have limited outside evidence of reliability and should run their own pilot first.

Who is Using AgentX?

• Product teams: They test and monitor customer-facing agents.
• Agencies: They build branded agents for clients.
• Support teams: They answer routine queries on Slack and websites.
• Solo builders: They prototype workflows on the Solo plan.

Pricing

AgentX is freemium, with paid plans from $49 per month (official pricing page, October 2026).

GetApp still lists older $19 and $59 tiers that no longer match the official page. Credit allowances may change, so check the vendor site before paying.

What Makes AgentX Unique?

Evaluation and monitoring set it apart from basic chatbot builders. AgentX lets the same team design an agent, score it on datasets and watch it after launch, even when the agent was coded in another framework.

Compatibilities and Integrations

• Platforms: Browser dashboard, with cloud or on-premise options.
• Channels: Slack, Discord, email, voice, widget, Shopify and WordPress.
• Frameworks: LangChain, CrewAI, OpenAI Agents SDK and Google ADK.
• API: API access on every plan, plus Zapier.

AgentX Tutorials

A first agent takes one short session.

1. Sign up for the free plan.
2. Create an agent and set its role and model.
3. Add agents on the canvas for multi-step tasks.
4. Run a test dataset and review traces.
5. Upgrade and deploy to your chosen channel.

How We Rated It

Summary

AgentX suits teams and agencies that want one place to build, test and watch AI agents. The main limitation is cost, since production use needs a paid plan and credits can run out quickly. Independent reviews are still thin, so test it yourself. Start on the free tier and run a small evaluation dataset before you commit.