pricing
Flexible Pricing for any Scale
Choose the plan that fits your needs. All plans include a 14-day free trial with no credit card required.
Starter
Get started at no cost
/month, per user
What’s Included
Up to 5 AI agents
1,000 tasks per month
Basic integrations
Email support
API access
Professional
popular
Level up your AI workflows
/month, per user
yearly billing (save 20%)
What’s Included
Up to 25 AI agents
10,000 tasks per month
Advanced integrations
Priority support
Custom workflows
Enterprise
Maximize team collaboration
/month, per user
yearly billing (save 20%)
What’s Included
Unlimited AI agents
Unlimited tasks
Custom integrations
Dedicated support
API access
Custom SLA
On-premise deployment
Advanced security
Starter
Get started at no cost
/month, per user
What’s Included
Up to 5 AI agents
1,000 tasks per month
Basic integrations
Email support
API access
Professional
popular
Level up your AI workflows
/month, per user
yearly billing (save 20%)
What’s Included
Up to 25 AI agents
10,000 tasks per month
Advanced integrations
Priority support
Custom workflows
Enterprise
Maximize team collaboration
/month, per user
yearly billing (save 20%)
What’s Included
Unlimited AI agents
Unlimited tasks
Custom integrations
Dedicated support
API access
Custom SLA
On-premise deployment
Advanced security
Compare Plans
Starter
Professional
Enterprise
Agent Capabilities
Number of AI Agents
1
10
Unlimited
Conversations per month
100
Unlimited
Unlimited
Custom workflows
Multi-language support
Integrations & Data
Basic integrations
All integrations
API access
Custom integrations
Data retention
7 days
9 days
Unlimited
Support & Security
Community support
Priority support
Dedicated support
SLA guarantees
Advanced security
On-premise deployment
Compare Plans
Starter
Agent Capabilities
Number of AI Agents
1
Conversations per month
100
Custom workflows
Multi-language support
Integrations & Data
Basic integrations
All integrations
API access
Custom integrations
Data retention
7 days
Support & Security
Community support
Priority support
Dedicated support
SLA guarantees
Advanced security
On-premise deployment
Compare Plans
Professional
Agent Capabilities
Number of AI Agents
10
Conversations per month
Unlimited
Custom workflows
Multi-language support
Integrations & Data
Basic integrations
All integrations
API access
Custom integrations
Data retention
9 days
Support & Security
Community support
Priority support
Dedicated support
SLA guarantees
Advanced security
On-premise deployment
Compare Plans
Enterprise
Agent Capabilities
Number of AI Agents
Unlimited
Conversations per month
Unlimited
Custom workflows
Multi-language support
Integrations & Data
Basic integrations
All integrations
API access
Custom integrations
Data retention
Unlimited
Support & Security
Community support
Priority support
Dedicated support
SLA guarantees
Advanced security
On-premise deployment
Compare Plans
Starter
Professional
Enterprise
Agent Capabilities
Number of AI Agents
1
10
Unlimited
Conversations per month
100
Unlimited
Unlimited
Custom workflows
Multi-language support
Integrations & Data
Basic integrations
All integrations
API access
Custom integrations
Data retention
7 days
9 days
Unlimited
Support & Security
Community support
Priority support
Dedicated support
SLA guarantees
Advanced security
On-premise deployment
TESTIMONIALS
What People Are Saying
The orchestration layer simplifies complex workflows and makes easier to manage.
Reduction in manual work
“AgentLab brings much-needed structure to AI automation workflows. The orchestration layer makes complex systems easier to understand, manage efficiently, and scale without breaking.”
Colton Pond
Head of Partnership
Orchestration layer simplifies workflows and improves overall system efficiency
Reduction in manual work
"AgentFlow brings structure to AI workflows, while its orchestration layer simplifies complexity and improves efficiency, enabling scalable and reliable system performance without breaking under scale."
Ethan Walker
CTO
Orchestration layer brings clarity and structure to complex digital workflows
Reduction in manual work
"AgentFlow organizes automation workflows effectively, and its orchestration layer reduces system complexity, enhances control, and enables smooth scalable growth with consistent performance and operational stability."
Sophia Martinez
Product Manager
Orchestration layer unifies multiple services into one streamlined workflow system
Reduction in manual work
"AgentFlow delivers clarity to automation processes, while its orchestration layer simplifies complex systems and improves coordination, ensuring consistent scalable performance with reliable and stable execution."
Noah Williams
Cloud Engineer
TESTIMONIALS
What People Are Saying
The orchestration layer simplifies complex workflows and makes easier to manage.
Reduction in manual work
“AgentLab brings much-needed structure to AI automation workflows. The orchestration layer makes complex systems easier to understand, manage efficiently, and scale without breaking.”
Colton Pond
Head of Partnership
Orchestration layer simplifies workflows and improves overall system efficiency
Reduction in manual work
"AgentFlow brings structure to AI workflows, while its orchestration layer simplifies complexity and improves efficiency, enabling scalable and reliable system performance without breaking under scale."
Ethan Walker
CTO
Orchestration layer brings clarity and structure to complex digital workflows
Reduction in manual work
"AgentFlow organizes automation workflows effectively, and its orchestration layer reduces system complexity, enhances control, and enables smooth scalable growth with consistent performance and operational stability."
Sophia Martinez
Product Manager
Orchestration layer unifies multiple services into one streamlined workflow system
Reduction in manual work
"AgentFlow delivers clarity to automation processes, while its orchestration layer simplifies complex systems and improves coordination, ensuring consistent scalable performance with reliable and stable execution."
Noah Williams
Cloud Engineer
TESTIMONIALS
What People Are Saying
The orchestration layer simplifies complex workflows and makes easier to manage.
Reduction in manual work
“AgentLab brings much-needed structure to AI automation workflows. The orchestration layer makes complex systems easier to understand, manage efficiently, and scale without breaking.”
Colton Pond
Head of Partnership
Orchestration layer simplifies workflows and improves overall system efficiency
Reduction in manual work
"AgentFlow brings structure to AI workflows, while its orchestration layer simplifies complexity and improves efficiency, enabling scalable and reliable system performance without breaking under scale."
Ethan Walker
CTO
Orchestration layer brings clarity and structure to complex digital workflows
Reduction in manual work
"AgentFlow organizes automation workflows effectively, and its orchestration layer reduces system complexity, enhances control, and enables smooth scalable growth with consistent performance and operational stability."
Sophia Martinez
Product Manager
Orchestration layer unifies multiple services into one streamlined workflow system
Reduction in manual work
"AgentFlow delivers clarity to automation processes, while its orchestration layer simplifies complex systems and improves coordination, ensuring consistent scalable performance with reliable and stable execution."
Noah Williams
Cloud Engineer
FAQs
Have questions? Find answers.
Have more questions?
Reach out to our friendly support team
What Exactly Is an AI Agent?
An AI Agent is more than just a chatbot; it is a system designed to perform tasks autonomously. While a chatbot answers questions, an agent can use tools, browse the web, and execute workflows (like booking a meeting or updating a CRM) to achieve a specific goal.
What Tools Can the AI Agent Connect To?
AI agents can connect to a wide range of tools to expand their capabilities and automate tasks more effectively. These typically include APIs, databases, CRM systems, cloud platforms, messaging apps, and third-party services.
How Do we Measure if the AI Agent Is Successful?
You measure an AI agent’s success by how well it achieves its goals and improves outcomes over time. Key indicators include task completion rate, accuracy of responses, and how often users get the right result without needing help.
What Metrics Can we Use to Evaluate User Satisfaction?
User satisfaction can be evaluated using a mix of direct feedback and behavioral data. Common metrics include customer satisfaction scores (CSAT), where users rate their experience, and Net Promoter Score (NPS), which measures how likely they are to recommend the service.
How Frequently Should we Conduct Performance Reviews of the AI?
AI performance reviews should be done on a regular, structured cycle—plus continuous monitoring in the background. For most use cases, a monthly review works well to assess key metrics like accuracy, task success rate, and user satisfaction.
How Long Does It Take to Design and Deploy an AI Agent?
The biggest factors affecting time are the scope of features, data availability, integration needs, and testing requirements. Planning, iteration, and optimization are just as important as the initial build, so deployment is often just the beginning of ongoing improvements.
FAQs
Have questions? Find answers.
Have more questions?
Reach out to our friendly support team
What Exactly Is an AI Agent?
An AI Agent is more than just a chatbot; it is a system designed to perform tasks autonomously. While a chatbot answers questions, an agent can use tools, browse the web, and execute workflows (like booking a meeting or updating a CRM) to achieve a specific goal.
What Tools Can the AI Agent Connect To?
AI agents can connect to a wide range of tools to expand their capabilities and automate tasks more effectively. These typically include APIs, databases, CRM systems, cloud platforms, messaging apps, and third-party services.
How Do we Measure if the AI Agent Is Successful?
You measure an AI agent’s success by how well it achieves its goals and improves outcomes over time. Key indicators include task completion rate, accuracy of responses, and how often users get the right result without needing help.
What Metrics Can we Use to Evaluate User Satisfaction?
User satisfaction can be evaluated using a mix of direct feedback and behavioral data. Common metrics include customer satisfaction scores (CSAT), where users rate their experience, and Net Promoter Score (NPS), which measures how likely they are to recommend the service.
How Frequently Should we Conduct Performance Reviews of the AI?
AI performance reviews should be done on a regular, structured cycle—plus continuous monitoring in the background. For most use cases, a monthly review works well to assess key metrics like accuracy, task success rate, and user satisfaction.
How Long Does It Take to Design and Deploy an AI Agent?
The biggest factors affecting time are the scope of features, data availability, integration needs, and testing requirements. Planning, iteration, and optimization are just as important as the initial build, so deployment is often just the beginning of ongoing improvements.
FAQs
Have questions? Find answers.
Have more questions?
Reach out to our friendly support team
What Exactly Is an AI Agent?
An AI Agent is more than just a chatbot; it is a system designed to perform tasks autonomously. While a chatbot answers questions, an agent can use tools, browse the web, and execute workflows (like booking a meeting or updating a CRM) to achieve a specific goal.
What Tools Can the AI Agent Connect To?
AI agents can connect to a wide range of tools to expand their capabilities and automate tasks more effectively. These typically include APIs, databases, CRM systems, cloud platforms, messaging apps, and third-party services.
How Do we Measure if the AI Agent Is Successful?
You measure an AI agent’s success by how well it achieves its goals and improves outcomes over time. Key indicators include task completion rate, accuracy of responses, and how often users get the right result without needing help.
What Metrics Can we Use to Evaluate User Satisfaction?
User satisfaction can be evaluated using a mix of direct feedback and behavioral data. Common metrics include customer satisfaction scores (CSAT), where users rate their experience, and Net Promoter Score (NPS), which measures how likely they are to recommend the service.
How Frequently Should we Conduct Performance Reviews of the AI?
AI performance reviews should be done on a regular, structured cycle—plus continuous monitoring in the background. For most use cases, a monthly review works well to assess key metrics like accuracy, task success rate, and user satisfaction.
How Long Does It Take to Design and Deploy an AI Agent?
The biggest factors affecting time are the scope of features, data availability, integration needs, and testing requirements. Planning, iteration, and optimization are just as important as the initial build, so deployment is often just the beginning of ongoing improvements.
