Causal Generative
Blackbox AI Platform
As data science practitioners, we understand the limitation of blackbox AI, hence pioneer this new field. We distill hidden signals from multimodal data, then use generative models to simulate complex scenarios and experiment with them to quantify cause-and-effect relationships.
Act confidently when you know Why and What-if
DataFusion
Discover hidden signals from integrated multimodal data
Real-world data come in different forms: images, texts, time series, and more, but finding "what" is relevant can be challenging. Vizuro's data staging and integration platform, DataFusion, specializes in integrating massive, high-dimension, mix-modal data for holistic modeling like humans do with multiple senses, so that key signals are not obliviated. Capability highlights:
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Preprocessed external data sources to enrich your internal data asset
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Cross-modal, synthetic data generation for model building without actual training sets
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Site-to-site data transformation for federated learning while preserving privacies
Augmenting DEG analysis using preprocessed TCGA, GTex, DepMap data for target identification to expedite drug discovery
Generating realistic part images for object identification and defect detection AI training directly from CAD models.
Reconstructing synthetic brain MRI (right) from the original (left) for federated learning while preserving privacy without loss of anatomical and tumor features
Augmenting DEG analysis using preprocessed TCGA, GTex, DepMap data for target identification to expedite drug discovery
100X
Data Augmented
10X
Ramp-Up Speed
Minimal
Training Set Needed
ModelCraft
Incorporating external indicators (PMI, CPI, Google Trends, etc.) into sales data to generate granular forecasts for better financial, production, and supply-chain planning
Assessing campaign lifts with their response curves for marketing mix, omnichannel, and next best action optimization
Clinical prognosis and early intervention of hospital readmissions to save lives and costs
Incorporating external indicators (PMI, CPI, Google Trends, etc.) into sales data to generate granular forecasts for better financial, production, and supply-chain planning
100%
Explainable Models
5X
Data Shift Robustness
Unlimited
What-Ifs Exploration
Build generative, causal models that ponder what-ifs and explain why
Blackbox models are often biased and cannot be trusted. To answer the question of "why", our AI does causal discovery, by sifting through millions of hypothesis and A/B testing from data automatically.
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Decisions often beg the "what-if" questions, and this is where correlation-based predictive models fail. Vizuro's modeling tool, ModelCraft, is capable of envisioning - inferring impact of actions via generative AI, like Dr. Strange does in the multiverse. Capability highlights:
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Causal graph generation from historical data
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Key features identification​
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Response curve assessment
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Editable to incorporate prior knowledge
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Scenario simulation from digital twins
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"What-if" pondering​
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Mission-specific content generation
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ActionWorks
Make mission-critical decisions with pivotal foresights and action roadmaps
Empowered by the causal intelligence from ModelCraft, you can answer the "how" questions with our highly configurable decision augmentation platform, ActionWorks. It contain suites of domain-specific apps that manifests the optimal course of actions with deployment roadmap based on infrastructure maturity, resource and budget, to deliver immediate impacts and max long-term ROI. Capability highlights:
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Constrained, stochastic optimization to handle resource availability and changing dynamics
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Mixture and priority of actions (e.g., marketing mix and omnichannel)
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Cadence of actions (e.g, next best actions)
Fine-tuning media budgets to yield the highest ROI under various constraints
Prescriptive maintenance to maximize ROI that balances costs associated with AIoT, maintenance, yield loss and throughput disruptions.
Fine-tuning media budgets to yield the highest ROI under various constraints
100%
Deployable Actions
20%+
ROI
Increase
< 1 Year
Payback Period
Deployment Timeline
Want It? Go Live In Six Months
0.5 Month
Problem Definition
0.5 Month
Data Asset Audit
2 Months
Data Preparation
2 Months
Causal Modeling
1 Months
Apps
Deployment
0.5 M
Goal & Gap Analysis
0.5 M
Data Asset Audit
2 M
Data
Staging
2 M
Causal Modeling
1 M
Apps Deployment