No-code agent builders
Design an agent and connect knowledge, models, actions, branches, and handoffs without building the orchestration layer from scratch.
Independent tool overview
AgentX at a glance
AgentX is a visual AI-agent platform for designing multi-agent workflows, connecting models and tools, evaluating behavior, deploying to customer and internal channels, and tracing production runs.
Visit the official AgentX site ↗
- Product type
- No-code and API platform for multi-agent automation
- Core lifecycle
- Build, evaluate, deploy, trace, observe, and roll back
- Models
- Multiple OpenAI, Anthropic, Google, Meta, and other model options
- Knowledge
- Websites, documents, typed content, images, and synced Google Drive
- Deployments
- API, web widget, Slack, Teams, WhatsApp, email, voice, and MCP
- Agency support
- White-label deployments and client workspaces
- Usage model
- Subscription plus credits consumed by model and tool actions
- Entry price
- Free; production builder plan starts at $49/month
- Last reviewed
- August 30, 2026
Overview
What AgentX is
AgentX has expanded well beyond the simple chatbot builder described in its original listing. It now targets solo builders, internal teams, AI agencies, and enterprises that need to design multi-agent workflows, test them against evaluation sets, deploy them through APIs and communication channels, and observe tool calls and handoffs in production. Agencies can also create branded client workspaces, while enterprise buyers can request managed implementation, dedicated infrastructure, or on-premise deployment.
The visual builder lowers the entry barrier, but a production agent is still software with probabilistic behavior and real permissions. A useful AgentX rollout starts with a narrow process, known examples, deterministic checks, least-privilege tools, human approval at consequential steps, cost and latency budgets, and a fallback queue. Multi-agent designs should earn their complexity by outperforming a simpler workflow in measured tests.
Use cases
Who AgentX is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Internal operations teams
Automate bounded document, customer-service, onboarding, research, reporting, and back-office processes with explicit review points.
AI agencies and consultancies
Manage multiple client workspaces and deliver branded agents under white-label Professional or Business plans.
Multi-agent experiments
Assign specialist roles to an orchestrator and compare the result with a single-agent baseline through repeated evaluations.
Omnichannel assistants
Publish one underlying agent workflow through web, API, chat, messaging, email, or voice surfaces.
Enterprise process automation
Request managed implementation, evaluation, SSO, dedicated infrastructure, compliance support, SLAs, and on-premise deployment.
Capabilities
Core AgentX features
Visual agent builder
Configure an agent's role, instructions, model, creativity, memory, knowledge, tools, and behavior in the web interface.
Multi-agent orchestration
Use an orchestrator to route work among specialist agents with distinct roles, permissions, tools, and knowledge.
Branching and human handoff
Create conditional workflow paths and route selected cases to a person rather than forcing full automation.
Model choice
Select from multiple hosted model families according to cost, latency, context, and quality requirements.
Knowledge bases
Ground agents in websites, sitemaps, typed content, files, OCR-extracted images, and connected Google Drive material.
Actions and tools
Let authorized agents search, retrieve knowledge, call integrations, generate media, or perform other configured actions.
Agent evaluations
Run test datasets, repeat trials, compare models, score behavior, and look for regressions before deployment.
Tracing and observability
Inspect runs, handoffs, tool calls, outputs, cost, latency, and failures to diagnose production behavior.
Versioning and rollback
Publish a versioned agent and return to a prior version when a change performs worse.
Multi-channel deployment
Deploy agents to an API, web widget, Slack, Microsoft Teams, WhatsApp, email, voice, and other supported channels.
MCP exposure
Expose an AgentX agent as an MCP server so compatible AI clients can call its approved capabilities.
API access
Interact with, track, query, or chain agents through the AgentX API after creating them in the visual platform.
White-label client workspaces
Agencies can deploy under their own brand and separate projects across customer workspaces.
Enterprise deployment options
Custom engagements can include SSO, dedicated infrastructure, on-premise operation, security support, and a managed evaluation program.
Process
How the AgentX workflow works
Step 1
Define the process
Document the trigger, inputs, current steps, business rules, systems, exceptions, owner, target outcome, and cases that must stay manual.
Step 2
Build the simplest agent
Start with one agent, one knowledge set, and the minimum tools required; add specialist agents only when evaluation data shows a benefit.
Step 3
Connect controlled knowledge and tools
Use approved sources, scoped credentials, read-only access where possible, and explicit schemas for every system action.
Step 4
Create an evaluation set
Include normal cases, edge cases, adversarial inputs, missing data, policy conflicts, tool failures, and known expected outcomes.
Step 5
Set thresholds and approvals
Define accuracy, cost, latency, refusal, escalation, and consistency targets, with human checkpoints for consequential decisions or writes.
Step 6
Deploy gradually
Release to a limited channel or audience, monitor every trace, compare the automation with the prior process, and keep a manual fallback.
Step 7
Operate and improve
Review failures, update the evaluation set, version changes, retest across models, cap credit spend, and roll back regressions quickly.
Cost
AgentX pricing and free plan
AgentX combines plan fees with usage credits. The current pricing page lists additional credits at $10 per 1,000 for paid self-service and agency plans. Every response, extraction, or tool action can consume a different number of credits, so total cost depends on model choice and workflow depth.
Free
$0 forever
For learning, testing, and building a first agent.
- 1 workspace
- Up to 5 agents
- 200 one-time credits
- 1 seat
- Multi-agent workflows and API access
- Not intended for sustained production use
Solo Builder
$49/month or $490/year
For an individual builder or internal team owner deploying production workloads.
- Unlimited workspaces
- Up to 25 agents
- 5,000 credits per month
- 1 seat
- Production deployment
- Multi-agent workflows, API, and demo evaluation mode
- Additional credits at $10 per 1,000
Professional
$199/month or $1,490/year
For agencies beginning to deliver branded agents to clients.
- Unlimited workspaces
- Up to 25 agents
- 10,000 credits per month
- 2 seats
- White-label deployment
- Client workspaces
- Extra seats at $10/month
- Additional credits at $10 per 1,000
Business
$299/month or $2,990/year
For agencies scaling a larger multi-client agent operation.
- Unlimited workspaces and agents
- 20,000 credits per month
- 2 seats
- White-label and client workspaces
- Priority support and SLA
- Extra seats at $10/month
- Additional credits at $10 per 1,000
Enterprise
Custom per process
For enterprise infrastructure, managed process automation, or regulated deployment needs.
- Unlimited workspaces, agents, and seats
- Custom credit volume
- Full evaluation program
- SSO and security support
- Dedicated or on-premise infrastructure
- Enterprise SLA and deployment support
Pricing checked . Check current pricing at the source ↗
Assessment
AgentX strengths and limitations
Where it stands out
- Covers more of the production lifecycle than a prompt-only chatbot builder
- Visual design makes models, knowledge, tools, handoffs, and specialist roles accessible to non-developers
- Evaluation, tracing, versioning, and rollback are first-class product concepts
- Supports multiple model providers instead of locking every workflow to one model family
- One workflow can be published through several internal and customer-facing channels
- Knowledge ingestion covers websites, files, OCR, and connected Google Drive sources
- Agency plans include white-label delivery and separated client workspaces
- API and MCP routes allow agents to participate in broader technical systems
- Human-in-the-loop checkpoints can be added to higher-risk processes
- Enterprise options include dedicated and on-premise infrastructure
What to consider
- A no-code builder does not remove the need for process design, data mapping, evaluation, security, and ongoing operations
- The API can interact with existing agents, but current documentation says agent creation still happens through the web interface
- Every model response, extraction, and tool action can consume credits, so multi-step or multi-agent workflows can become expensive
- The free plan includes only 200 one-time credits and is best treated as a short evaluation environment
- Multi-agent workflows add latency, more failure points, more prompts, and greater nondeterminism than a simpler agent
- An LLM-as-judge score is not ground truth and can share biases or blind spots with the system being evaluated
- Demo evaluation access on self-service plans is less extensive than the full enterprise evaluation program
- Website and document knowledge can become stale, conflicting, poorly parsed, or vulnerable to embedded prompt injection
- Tool-enabled agents can take incorrect or unauthorized actions unless credentials, schemas, approvals, and limits are carefully scoped
- MCP, search, messaging, CRM, email, and voice connections expand the attack surface and number of data processors
- Voice and messaging workflows introduce channel-specific consent, recording, telecom, accessibility, and deliverability requirements
- White-label agencies remain responsible for client disclosures, support, quality, security, and downstream data handling
- Vendor-reported automation and savings claims need validation against the buyer's own baseline and exception rate
- On-premise deployment, SSO, dedicated infrastructure, and the full evaluation program require a custom enterprise engagement
- High-stakes decisions in finance, healthcare, employment, legal, safety, or identity require qualified human ownership and specialized controls
Compare
AgentX alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Business Operations
Voiceflow
Voiceflow is a mature visual platform for customer-facing chat and voice agents with a strong conversation-design workflow.
Explore Voiceflow →Business Operations
Lindy
Lindy focuses on accessible business automation agents and prebuilt integrations for teams prioritizing quick operational workflows.
Explore Lindy →Business Operations
Gumloop
Gumloop is a no-code AI automation alternative for teams that think in repeatable workflows more than autonomous multi-agent workforces.
Explore Gumloop →Questions
AgentX FAQs
What is AgentX?
AgentX is a platform for building, evaluating, deploying, tracing, and monitoring AI agents and multi-agent workflows. It serves self-service builders, agencies, internal teams, and enterprises.
Do I need to code to use AgentX?
No code is required for the visual builder and common deployments. API integrations, custom systems, identity, data governance, complex tool schemas, and production operations can still require engineering work.
Is AgentX free?
AgentX has a free plan with one workspace, up to five agents, one seat, and 200 one-time credits. Production use starts with the $49-per-month Solo Builder plan.
How do AgentX credits work?
Credits are the usage unit for model and tool activity. Different models and actions cost different amounts, so a workflow with several specialist agents or tool calls consumes more than a single lightweight response.
Can AgentX build multi-agent systems?
Yes. An orchestrator can coordinate specialist agents, each with its own role, instructions, model, memory, knowledge, tools, and permissions.
How does AgentX test agents?
Its evaluation framework can run datasets, repeat trials, compare model behavior, score outputs, and track regressions. Buyers should supplement model-based judging with deterministic checks, domain reviewers, and real outcome measurement.
Where can I deploy an AgentX agent?
AgentX advertises API, web widget, Slack, Microsoft Teams, WhatsApp, email, voice, and MCP deployments, with channel access and limits depending on plan.
Can agencies white-label AgentX?
Yes. The Professional and Business plans include branded deployment and client workspaces. Agencies should confirm domain, export, billing, support, and data-separation details before promising a client experience.
Can AgentX run on-premise?
On-premise and dedicated infrastructure are listed as Enterprise options with custom scoping and pricing.
Is AgentX safe for fully autonomous business processes?
No agent platform should be considered safe for unrestricted autonomy by default. Limit tools and credentials, require approval for consequential writes, evaluate edge cases, log all actions, set spend limits, and keep a tested manual fallback.
Bottom line
Our AgentX verdict
AgentX is now a credible platform to evaluate when a team needs the whole agent lifecycle—visual orchestration, model choice, tests, deployment, tracing, and rollback—rather than just a website chatbot. The best fit is a defined, repetitive process with measurable outputs and controlled tools. Start with one agent and one channel, prove reliability and economics, then add specialist agents or autonomy only when the evaluation evidence supports the extra complexity.
Visit AgentX website ↗Similar Business Operations Tools
View all Business Operations AI tools →
AI training for the future of work.
Get access to all our AI courses, hundreds of real-world AI use cases, live expert-led workshops, an exclusive network of AI early adopters, and more.
AI Courses
Get unlimited access to all of our current & upcoming industry-specific AI courses for the duration of your subscription.
Daily Guides
To keep up with the rapid pace of AI, our team publishes AI implementation guides daily. Our library contains 300+ practical use cases to automate real-world work.
Workshops
Join weekly, live, interactive sessions with industry leaders who are at the forefront of AI for hands-on implementation guidance and exclusive insights.
Community
Network with an exclusive community of AI-first professionals who are working smarter with AI. Learn how early adopters are using AI in their work and businesses.