STOP GUESSING. START KNOWING.
Deploy AI Agents With Unshakeable Confidence.
Zenval is built for AI teams to rigorously test, evaluate, and benchmark AI agents. Ship without anxiety and surprises.
STOP GUESSING. START KNOWING.
Deploy AI Agents With Unshakeable Confidence.
Zenval is built for AI teams to rigorously test, evaluate, and benchmark AI agents. Ship without anxiety and surprises.
Tired of the LLM Guessing Game?
The everyday frustrations for teams pushing the boundaries of AI
The Black Box Problem
The non-deterministic nature of LLMs means outputs can be unpredictable, making you unsure of what your users will experience.
Scaling Pains
The excitement of launching new features skyrockets the anxiety around regressions and inconsistent quality.
Traditional Tests Fall Short
Unit tests that work for conventional software simply can't capture the nuances of AI behavior or prompt changes.
Research Backed
Our evaluation techniques are holistic, reliable and powered by the latest research
“From Papers to Practice.”
HELM Benchmarks
Stanford-led framework for evaluating
LLM robustness and coverage
MMLU Testing
Evaluates performance across 57
academic and professional subjects
Prompt Bench Suite
Stress-tests LLMs with adversarial,
edge-case prompts
Chain-of-Thought Prompting
Improves reasoning through intermediate
step generation
Bias & Hallucination Checks
Detects fairness gaps and factual
inconsistencies in output
Iterate with Assurance
Understand the precise impact of every change, from prompt engineering to model updates.
Analyzing current workflow..
System check
Process check
Speed check
Manual work
Repetative task
Powerful & Flexible Eval Tools
Leverage over 100+ built-in evals or create your custom evaluations tailored to your specific needs.
- class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}" - class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}"
Side-by-Side Comparison
Instantly compare the performance of different prompts, models, or settings.
Our solution
Your stack
Built-in Collaboration
Leverage over 100+ built-in evals or create your custom evaluations tailored to your specific needs.
Chatbot system
Efficiency will increase by 20%
Workflow system
Update available..
Sales system
Up to date
WHY CHOOSE US?
Innovative tools and powerful insights designed to elevate your business
Unmatched Focus on Advanced Evaluation
Zenval is purpose-built from the ground up for deep, robust, and nuanced AI evaluation. This is our core, not a side feature.
Expertise in Agents & Multi-Agent Systems
We specialize in evaluating the complex logic and multi-step outputs of advanced AI agents.
Multimodality
Our vision extends to comprehensive support for multimodality and not just text.
Pricing
Custom Pricing
Our goal is to provide exceptional value, ensuring our advanced evaluation capabilities align perfectly with AI ambition
Unlimited Evaluation
Unlimited History
All Models
Unlimited Users
️Email/Slack/WhatsApp Support
White-glove onboarding
Book A Demo
What our clients say about us?
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
Built by AI Practitioners. For AI Practitioners.
We built and scaled AI agents to millions. We know the pre-deployment jitters, the unpredictable
outputs, the "deploy and pray" moments.
Zenval is born from that very real experience – to give your team the control and confidence to innovate without fear.
The Black Box Problem
The non-deterministic nature of LLMs means outputs can be unpredictable, making you unsure of what your users will experience.
Scaling Pains
The excitement of launching new features skyrockets the anxiety around regressions and inconsistent quality.
Traditional Tests Fall Short
Unit tests that work for conventional software simply can't capture the nuances of AI behavior or prompt changes.
Tired of the LLM Guessing Game?
The everyday frustrations for teams pushing the boundaries of AI
Side-by-Side Comparison
Instantly compare the performance of different prompts, models, or settings.
Our solution
Your stack
Our solution
Your stack
Research Backed
Our evaluation techniques are holistic, reliable and powered by the latest research
“From Papers to Practice.”
HELM Benchmarks
Stanford-led framework for evaluating
LLM robustness and coverage
MMLU Testing
Evaluates performance across 57
academic and professional subjects
Prompt Bench Suite
Stress-tests LLMs with adversarial,
edge-case prompts
Chain-of-Thought Prompting
Improves reasoning through intermediate
step generation
Bias & Hallucination Checks
Detects fairness gaps and factual
inconsistencies in output
“From Papers to Practice.”
HELM Benchmarks
Stanford-led framework for evaluating
LLM robustness and coverage
MMLU Testing
Evaluates performance across 57
academic and professional subjects
Prompt Bench Suite
Stress-tests LLMs with adversarial,
edge-case prompts
Chain-of-Thought Prompting
Improves reasoning through intermediate
step generation
Bias & Hallucination Checks
Detects fairness gaps and factual
inconsistencies in output
Powerful & Flexible Eval Tools
Leverage over 100+ built-in evals or create your custom evaluations tailored to your specific needs.
- class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}" - class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}"
- class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}" - class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}"
Iterate with Assurance
Understand the precise impact of every change, from prompt engineering to model updates.
Analyzing current workflow..
System check
Process check
Speed check
Manual work
Repetative task
Built-in Collaboration
Leverage over 100+ built-in evals or create your custom evaluations tailored to your specific needs.
Chatbot system
Efficiency will increase by 20%
Workflow system
Update available..
Sales system
Up to date
Chatbot system
Efficiency will increase by 20%
Workflow system
Update available..
Sales system
Up to date
WHY CHOOSE US?
Innovative tools and powerful insights designed to elevate your business
Unmatched Focus on Advanced Evaluation
Zenval is purpose-built from the ground up for deep, robust, and nuanced AI evaluation. This is our core, not a side feature.
Expertise in Agents & Multi-Agent Systems
We specialize in evaluating the complex logic and multi-step outputs of advanced AI agents.
Multimodality
Our vision extends to comprehensive support for multimodality and not just text.
What our clients say about us?
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Sophia Green
CTO of Fashion AI Product
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO, FinTech building AI customer solutions
Built by AI Practitioners. For AI Practitioners.
We built and scaled AI agents to millions. We know the pre-deployment jitters, the unpredictable outputs, the "deploy and pray" moments.
Zenval is born from that very real experience – to give your team the control and confidence to innovate without fear.
Research Backed
Our evaluation techniques are holistic, reliable and powered by the latest research
“From Papers to Practice.”
HELM Benchmarks
Stanford-led framework for evaluating
LLM robustness and coverage
MMLU Testing
Evaluates performance across 57
academic and professional subjects
Prompt Bench Suite
Stress-tests LLMs with adversarial,
edge-case prompts
Chain-of-Thought Prompting
Improves reasoning through intermediate
step generation
Bias & Hallucination Checks
Detects fairness gaps and factual
inconsistencies in output
“From Papers to Practice.”
HELM Benchmarks
Stanford-led framework for evaluating
LLM robustness and coverage
MMLU Testing
Evaluates performance across 57
academic and professional subjects
Prompt Bench Suite
Stress-tests LLMs with adversarial,
edge-case prompts
Chain-of-Thought Prompting
Improves reasoning through intermediate
step generation
Bias & Hallucination Checks
Detects fairness gaps and factual
inconsistencies in output
The Black Box Problem
The non-deterministic nature of LLMs means outputs can be unpredictable, making you unsure of what your users will experience.
Scaling Pains
The excitement of launching new features skyrockets the anxiety around regressions and inconsistent quality.
Traditional Tests Fall Short
Unit tests that work for conventional software simply can't capture the nuances of AI behavior or prompt changes.
Tired of the LLM Guessing Game?
The everyday frustrations for teams pushing the boundaries of AI
INTRODUCING ZENVAL.AI
The Gold Standard in AI Agent Testing and Evaluation
Zenval empowers you to move from uncertainty to absolute confidence in your AI product deployments
01
Define your inputs
02
Specify Expected Outputs
03
Configure evaluation criteria
Pricing
Custom Pricing
Our goal is to provide exceptional value, ensuring our advanced evaluation capabilities align perfectly with AI ambition
Unlimited Evaluation
Unlimited History
All Models
Unlimited Users
️Email/Slack/WhatsApp Support
White-glove onboarding
Book A Demo
Side-by-Side Comparison
Instantly compare the performance of different prompts, models, or settings.
Our solution
Your stack
Our solution
Your stack
Powerful & Flexible Eval Tools
Leverage over 100+ built-in evals or create your custom evaluations tailored to your specific needs.
- class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}" - class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}"
- class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}" - class AutomationTrigger:def __init__(self, threshold):
self.threshold = threshold
self.status = "inactive"
def check_trigger(self, value):
if value > self.threshold:
self.status = "active"
return "Automation triggered!"
else:
return "No action taken."def get_status(self):
return f"Status: {self.status}"
Iterate with Assurance
Understand the precise impact of every change, from prompt engineering to model updates.
Analyzing current workflow..
System check
Process check
Speed check
Manual work
Repetative task
Built-in Collaboration
Leverage over 100+ built-in evals or create your custom evaluations tailored to your specific needs.
Chatbot system
Efficiency will increase by 20%
Workflow system
Update available..
Sales system
Up to date
Chatbot system
Efficiency will increase by 20%
Workflow system
Update available..
Sales system
Up to date
WHY CHOOSE US?
Innovative tools and powerful insights designed to elevate your business
Unmatched Focus on Advanced Evaluation
Zenval is purpose-built from the ground up for deep, robust, and nuanced AI evaluation. This is our core, not a side feature.
Multimodality
Our vision extends to comprehensive support for multimodality and not just text.
Expertise in Agents & Multi-Agent Systems
We specialize in evaluating the complex logic and multi-step outputs of advanced AI agents.
What our clients say about us?
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO of ElevateTech
“..we defined precise evaluation criteria for accuracy, tone, and helpfulness for every agent. We launched knowing our product delivers a reliable user experience from day one. If you are a serious AI builder, you should definitely try zenval.”
Daniel Reed
CEO of ElevateTech
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Rober Morgan
CTO of Fashion AI Product
“Now, we rigorously evaluate every iteration against clear benchmarks. We catch regressions before deployment, ensure consistent quality, and have rebuilt stakeholder confidence.”
Rober Morgan
CTO of Fashion AI Product
Built by AI Practitioners. For AI Practitioners.
We built and scaled AI agents to millions. We know the pre-deployment jitters, the unpredictable outputs, the "deploy and pray" moments.
Zenval is born from that very real experience – to give your team the control and confidence to innovate without fear.
Pricing
Custom Pricing
Our goal is to provide exceptional value, ensuring our advanced evaluation capabilities align perfectly with AI ambition
Unlimited Evaluation
Unlimited History
All Models
Unlimited Users
️Email/Slack/WhatsApp Support
White-glove onboarding