详细内容
Agentic Enterprise Intelligence.
More Reliable Predictions and Smarter Decisions for Business.
Problem
Gartner predicts50% of AI models will be domain-specific*by 2027 yet today’s general purpose AI models fail to reliably solve domain-specific problems.
Solution
Genius is a cutting edge agentic enterprise intelligence platform for rapidly building reliable domain-specific predictions and decisions and is particularly useful for problems that involve volatility, uncertainty, complexity or ambiguity.
Who is Genius for?
Genius is designed from the ground up to accelerate time-to-value for machine learning researchers, engineers and data scientists working on enterprise-class challenges.
Genius Agentic Enterprise Intelligence - YouTube
VERSES
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Genius Agentic Enterprise Intelligence
VERSES
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VERSES Genius Beta 2 0 Release - YouTube
VERSES
1.87K subscribers
VERSES Genius Beta 2 0 Release
VERSES
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Genius is designed to help machine learning professionals and data scientists
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Build causal models that learn continuously in real time
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Generate predictions that are more reliable, more explainable and more efficient
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Accelerate time from data to decisions from weeks to days
"50% of AI models will be domain-specific"
Gartner
Genius Features
Previous
Graceful Exception Handling
Troubleshoot and debug errors, build resilient models and recover faster for a smoother development experience.
Drag & Drop Interface*
An intuitive no-code graphical user interface designed to help you model the causal relationships between factors and variables.
*Bayes Nets only
Guided Workflows
User guidance to help you build models and run inference fast.
Build Domain-Specific Models
Upload CSV datasets to extract variables, factors and parameters and export as JSON to perform inference.
Continual Learning & Explainability
Train, measure and update explainable models continuously
Visualize Inference
Quantify uncertainty and express probabilistic predictions of likely outcomes.
Automated Binning
Group and categorize data in order to simplify analysis and optimize inference.
Graceful Exception Handling
Troubleshoot and debug errors, build resilient models and recover faster for a smoother development experience.
Drag & Drop Interface*
An intuitive no-code graphical user interface designed to help you model the causal relationships between factors and variables.
*Bayes Nets only
Guided Workflows
User guidance to help you build models and run inference fast.
Build Domain-Specific Models
Upload CSV datasets to extract variables, factors and parameters and export as JSON to perform inference.
Continual Learning & Explainability
Train, measure and update explainable models continuously
Visualize Inference
Quantify uncertainty and express probabilistic predictions of likely outcomes.
Automated Binning
Group and categorize data in order to simplify analysis and optimize inference.
Graceful Exception Handling
Troubleshoot and debug errors, build resilient models and recover faster for a smoother development experience.
Next
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Genius Capabilities
Model & Validation Tooling
Intuitive low-code user interface designed for modeling domain-specific causal models on which to perform reasoning, planning and learning using Active Inference.
Enhanced Inference & Learning
Advanced reasoning and planning using Bayesian inference mechanisms.
Customer Success
Model & Validation Tooling
Intuitive low-code user interface designed for modeling domain-specific causal models on which to perform reasoning, planning and learning using Active Inference.
Enhanced Inference and Learning
Advanced reasoning and planning using Bayesian inference mechanisms.
Lifecycle User Enablement
Simplified deployment, tutorials and reference examples.
Enterprise Ready
Manage users, licenses, agents and support tickets.
Developer Friendly
Well-documented SDK and APIs along with customer success support.
Lifecycle User Enablement
Simplified deployment, tutorials and reference examples.
Enterprise Ready
Manage users, licenses, agents and support tickets.
Developer Friendly
Well-documented SDK and APIs along with customer success support.
Modeling & Validation Tooling
Intuitive low-code user interface for modeling and structuring cause and effect in data.
Performance Characterization
Command tool for monitoring model and inference performance in real time.
Enhanced Inference and Learning
Advanced Reasoning and planning using Bayesian inference mechanisms.
Lifecycle User Enablement
Simplified deployment, tutorials and examples for enabling users get time to value.
Easy to Install & Use
Kubernetes containers for easy deployments.
Analytics & Telemetry
Monitor user activity to enable data-driven decision-making.
Intelligence Powered by Genius
Agents powered by Genius have agency and autonomy can act as the intelligent interface to knowledge repositories, systems, devices, other AI and ML models and even other agents.
Unlimited Potential
Transcend the limitations and shortcomings of conventional machine learning.
Hallucinations
Drift
Static models
Sample inefficiency
Sensitivity to noise
Black box
Hardware inflexibility
Lack of uncertainty quantification
Goodbye
bots
Hello
agents
Instant Insight
Make sense of your data in minutes not weeks.
- Rapidly ideate and validate Bayesian models for inference that explicitly map causal relationships.
- Build agents that respond to dynamic environments with online learning and planning based on real time observations and explainable decisions.
- Streamline complex integrations and deployments.
- ML Researchers can spend less time implementing and more time experimenting.
- ML Engineers can spend less time adjusting models that fail to perform in the face of complexity and uncertainty.
Adaptable
Continual and online learning
Autonomous
Self-directed goal setting & decision making
Composable
Modular and reusable knowledge models
Efficient
Requires few samples and minimal compute
Explainable
Transparency into how predictions and decisions are made
Flexible
Powerful specialized GPUs are not required but optional
Interoperable
Shared knowledge means better decision making
Reliable
Predictions have confidence score qualifiers
Resilient
Fault tolerance and able to recover from failure
Scalable
Run in the cloud or at the edge
Sustainable
Less compute and less retraining means less energy
Quantify Uncertainty
Thrive in spite of of noisy, sparse or missing data
Previous
Being able to explicitly model the cause-effect relationships of complex systems and quantify uncertainty means we can generate something not possible with traditional ML tools – results that are reliable, explainable, and assurance ready.
Andy Tasker
Founder and Chief Strategist Prodigii
At Analog, we believe intelligence is about adapting, evolving, and seamlessly integrating into the fabric of everyday life. Genius didn’t just prove it could handle complexity—it showed us it could anticipate and creatively respond to real-world challenges. By embedding Genius Enterprise as a component of our solutions, we’re crafting the nervous system of tomorrow’s cities: intelligent, intuitive, and human-centric.
Alex Kipman
Founder and CEO Analog
Our Fortune 500 clients want AI that speaks their language, respects their rules, and delivers results they can trust. Off-the-shelf platforms rarely meet those standards. We believe that Genius lets us generate reliable, domain-specific predictions in weeks instead of months, and our team provides the know-how to take those models live. Becoming the first Certified Genius Reseller allows us to bring VERSES’ next-generation capability to enterprises worldwide.
Gaurav Agrawal
Founder and CEO Soothsayer
We're excited to join VERSES in building trustworthy, explainable intelligence designed to enhance rather than replace human capabilities. Together, we will help organizations transition from unreliable, generic AI to domain-specific intelligence that adapts and grows alongside the businesses it serves. We feel that we are breaking significant new ground with our Enterprise program with VERSES while enabling our clients to be at the forefront of using cognitive AI as a catalyst for reinvention.
Ken Rastin
Founder and CEO Kalosys
Being able to explicitly model the cause-effect relationships of complex systems and quantify uncertainty means we can generate something not possible with traditional ML tools – results that are reliable, explainable, and assurance ready.
Andy Tasker
Founder and Chief Strategist Prodigii
At Analog, we believe intelligence is about adapting, evolving, and seamlessly integrating into the fabric of everyday life. Genius didn’t just prove it could handle complexity—it showed us it could anticipate and creatively respond to real-world challenges. By embedding Genius Enterprise as a component of our solutions, we’re crafting the nervous system of tomorrow’s cities: intelligent, intuitive, and human-centric.
Alex Kipman
Founder and CEO Analog
Our Fortune 500 clients want AI that speaks their language, respects their rules, and delivers results they can trust. Off-the-shelf platforms rarely meet those standards. We believe that Genius lets us generate reliable, domain-specific predictions in weeks instead of months, and our team provides the know-how to take those models live. Becoming the first Certified Genius Reseller allows us to bring VERSES’ next-generation capability to enterprises worldwide.
Gaurav Agrawal
Founder and CEO Soothsayer
We're excited to join VERSES in building trustworthy, explainable intelligence designed to enhance rather than replace human capabilities. Together, we will help organizations transition from unreliable, generic AI to domain-specific intelligence that adapts and grows alongside the businesses it serves. We feel that we are breaking significant new ground with our Enterprise program with VERSES while enabling our clients to be at the forefront of using cognitive AI as a catalyst for reinvention.
Ken Rastin
Founder and CEO Kalosys
Being able to explicitly model the cause-effect relationships of complex systems and quantify uncertainty means we can generate something not possible with traditional ML tools – results that are reliable, explainable, and assurance ready.
Andy Tasker
Founder and Chief Strategist Prodigii
Next
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Use Cases
Risk Assessment
Assessing the probability of financial default for a loan applicant.
Fault Diagnosis
Detecting system malfunctions in a manufacturing line.
Recommendation Systems
Personalizing movie recommendations for streaming services users.
Predictive Maintenance
Scheduling maintenance for a fleet of industrial machines.
Optimization
Finding the best delivery routes for logistics companies.
Resource Allocation
Distributing limited medical supplies during a health crisis.
Beyond smart. Genius.
Genius enables agents to generate predictions that are highly reliable, explainable and sustainable.
Reliable
Predictions have confidence score qualifiers
Explainable
Transparency into how predictions and decisions are made
Sustainable
Less compute and less retraining means less energy
Spring 2025 Release Highlights
Genius Model Editor
- Dozens of usability improvements including a model wizard to streamline building, validating, training and saving your models.
- Models include Partially Observable Markov Decision Process (POMDP), Markov Decision Process and Discrete Bayes Net.
- Continuous learning and latent/hidden variables are now supported
- Model validation and testing
- Enhanced inference and learning
Genius Customer Portal
- Renamed Developer Portal to Customer Portal
- More robust account administration including a dashboard and management of users, licenses, agents, models, tickets and more.
- User analytics with telemetry.
Genius Hosted Services
- We found that a minority of users required or had the technical skills to self-host so we are primarily hosting instances of Genius with all the benefits, security and assurances of a major cloud services infrastructure.
Streamline Your Pipeline
Simplify and automate from planning to production.
Genius provides familiar ways to ingest, validate, and preprocess data in preparation for creating machine learning models.
Genius provides tools to build, analyze, and validate probabilistic causal models of complex dynamic systems that can quantify uncertainty.
Deploy agents with your preferred tools and see your agent use active inference to reason, plan, and learn and act. They will continuously evolve with new observations and become specialized domain experts with ever-improving prediction accuracy and reliability.
Pricing
Pricing and terms subject to change
- Starter
- Professional
- Enterprise
| Starter | Professional | Enterprise | |
|---|---|---|---|
| Monthly Price | Get Started<br>$99<br>After 30 day FREE trial | For Individuals<br>$199<br>After 30 day FREE trial | For Organizations<br>Contact for demo |
| Capabilities | |||
| Model Editor | |||
| SDK | |||
| API | |||
| Users | 1 | 1 | Flexible |
| Inference Agents | 1 | 3 | Flexible |
| Support | Priority | ||
| Hosting | Cloud | Cloud | Cloud/Self Hosted |
| Learn More | Learn More | Signup |
Research Spotlight
Mastermind multi-step reasoning was built using Genius while other videogame benchmarks employ methods and techniques that underwrite the technology behind Genius.
Genius Outperforms DeepSeek R1 in Code-Breaking Challenge, Mastermind
Mastering Atari Games with Natural Intelligence
*Gartner article from February 2025
FAQ
Our objective is to democratize Active Inference agents and Bayesian methods starting with supporting machine learning engineers who struggle with a model creation and deployment pipeline. As Genius evolves its features and capabilities will expand to include other personas. If you are looking for the following features and capabilities today then Genius was made for you.
- Intuitive tools for rapid prototyping and validation.
- Seamless integration with existing research libraries (e.g., PyTorch, TensorFlow).
- Advanced diagnostic capabilities to analyze model performance.
- Ability to create modular models that can be easily reused and adapted for future research.
- Reliable, scalable infrastructure for deploying models without needing extensive rewriting.
- Instrumentation and logging to understand model behavior in production.
- Support for retraining and fine-tuning models based on real-time data.
- Tools to efficiently update and deploy model versions.
- Advanced Bayesian modeling techniques for uncertainty quantification.
- A sandbox environment for fast iteration and debugging.
- Easy-to-use interfaces for testing and comparing different models.
- Visualizations for understanding model behavior and decision boundaries.
- Automated pipelines for model deployment, testing, and rollback.
- Easy integration with existing DevOps tools (e.g., Kubernetes, Docker, CI/CD systems).
- Real-time monitoring and alerting for drift and performance issues.
Visual and interactive tools for troubleshooting and debugging.
Genius is ideal for tackling complex problems that require quantifying uncertainty and making inferences on the likelihood of causes given observed effects. Some examples:
Rain, Sprinkler, Wet Grass
What is the probability that it rained or that the sprinkler was on, given grass is wet?
→ P (rain | wet grass)
Cold, Flu, Cough
Given that someone has a cough, determine the probability that it is due to a cold or a flu or both.
→ P (cold | cough)
Infection, Viral Illness, High Fever
Given a high fever, determine the probability that it is due to infection or viral illness?
→ P (infection | cough)
Defective Machine, Power Fluctuation, Production Halt
Given that the production has halted, determine the probability that it's due to a defective machine, power fluctuation or both.
→ P (defective machine | production hault)