XpViz — The Explainable Deep Learning Workbench
XpViz gives data scientists and business teams a shared, high-level understanding of how deep models behave — not through low-level introspection, but through clear, actionable explanations that connect performance to business outcomes.
Ante-Hoc Transparency for Deep Model Understanding
XpViz is built on Xpdeep's ante-hoc, self-explainable deep learning framework.
Unlike post-hoc XAI, which approximates a model's behavior after training, XpViz exposes the true internal logic of the model from the start.
No Post-Hoc. Ever.
This foundation enables precise understanding, trustworthy optimization, and actionable intelligence grounded in the model's real reasoning.
Understand, Analyze, and Improve
With XpViz, data scientists can:
- Analyze the training data and monitor explainability across epochs.
- Examine which variables truly drive performance and trim those that don't — creating more frugal, compliant models aligned with the AI Act and other regulations.
- Identify and correct false positives and false negatives through targeted counterfactual analysis.
- Refine predictive regions one at a time to enhance model precision and stability.
These insights empower teams to make every optimization meaningful — guided by real understanding, not trial and error.
How XpViz Differs from Post-Hoc Tools and AI Observability Platforms
Most solutions explain or monitor a model after it has already been trained or deployed.
XpViz is fundamentally different:
- It visualizes ante-hoc explainability, built inside the model architecture
- It reflects the model's true internal computations, not approximations
- It connects explanations directly to optimization levers
- It enables audit-readiness and certification by tracing decisions back to the model's internal structure
Comparison:
- Post-Hoc XAI: Adds interpretability layers on top of black-box models
- AI Observability: Monitors behavior after deployment
- XpViz: Native transparency → optimization → certification → actionability
From Explainability to Business Alignment
Optimizing a deep model only makes sense when it serves business goals.
XpViz turns explainability into a strategic asset, helping data scientists align model behavior with real-world KPIs — quality, yield, uptime, risk, or sustainability.
It's the tool that brings engineers, product owners, and business experts back into the AI loop.
Faster, Smarter Model Design
With XpViz, design cycles accelerate by up to 4×, as teams move from exploration to certification with clarity and confidence.
Every visualization, metric, and "how-to improve" insight is generated from within the model — enabling faster iteration and higher impact for every training run.
Explainability That Drives Optimization and Action
XpViz transforms explainability into an operational lever.
By exposing the model's internal logic, XpViz enables:
- Precise reduction of unnecessary variables or sensors
- Improved robustness and reduced false positives
- Faster model iteration cycles
- Seamless transition to the XpAct action layer
- Compliance validation in XpComply
Learn how explainability delivers measurable ROI through cost savings and new growth opportunities.
Time-Series Native Explainability
For temporal models, XpViz reveals how the model's reasoning evolves over time — enabling trustworthy analysis of sequences, delays, and multi-step dependencies.
XpViz turns explainability from a diagnostic tool into a strategic advantage — enabling enterprises to design, optimize, certify, and deploy deep models with complete transparency and No Post-Hoc approximations.
XpViz is all you need to know you built the right model — explainable, optimized, and aligned with your business objectives.
Request a DemoPricing for XpViz and the Xpdeep Hub
Choose the plan that fits your technical and compliance needs — from free exploration to governed enterprise deployment.