Predict & Explain
Generate native, real-time explanations and 'how-to improve' analyses directly from your deep models. Every prediction ships with its justification — no post-hoc approximations, no latency overhead.
Ante-Hoc Explainability — Real-Time, Native, Zero-Latency Transparency
Every prediction delivered by Xpdeep includes its own explanation, generated natively inside the model.
There is no post-hoc approximation, no external explainer, and no added latency.
This ante-hoc architecture ensures complete consistency between what the model predicts and how it justifies its decision — even in real-time environments.
Deploy explainable models into production with full real-time transparency. Xpdeep delivers predictions enriched with confidence intervals, human-readable explanations, and "how-to improve" analyses. APIs and dashboards make it simple to integrate explainable intelligence into any workflow — ensuring operators and stakeholders receive clear, immediate reasoning behind every decision.
Real-Time Scoring & Confidence Intervals
Generate predictions with native confidence intervals and risk indicators. Xpdeep quantifies uncertainty per prediction, enabling informed, traceable decision-making at every step.
API Integration for Applications
Integrate Xpdeep's explainable predictions directly into your applications. REST APIs provide real-time scoring, explanations, monitoring, and transparent outputs for production systems.
Natural-Language Explanations
Every output comes with a clear, human-readable explanation — no jargon required. Stakeholders understand the reasoning behind each prediction instantly.
With Xpdeep, every prediction is explainable at the moment it is produced. The framework embeds a native explanation engine within the model itself, ensuring that each output includes:
- its justification
- its structural reasoning
- its key contributing factors
- a counterfactual "how-to improve" analysis
This is true ante-hoc self-explainability, not post-hoc interpretation. It maintains mathematical and logical consistency between the model's reasoning and its outcome — an essential requirement for domains with operational, safety, financial, or regulatory impact.
Engineers and domain experts can inspect these explanations directly in XpViz, evaluate influences, and export the explanation chain for documentation or compliance. This turns explainability into real-time actionability.
→ Every prediction tells its story — instantly, precisely, and certifiably.
Key Capabilities
Native Explainability
Native explainability per prediction — generated directly inside the model
Counterfactual "How-To" Analysis
Counterfactual "how-to improve" insights — minimal actionable changes to reach a target KPI
Prescriptive Control
Prescriptive control — enabling real-time adjustments and closed-loop decisions grounded in transparent logic
Why It Matters
Improve operator trust and model adoption
Reduce decision latency — no external interpretability layer
Quantify risk with confidence intervals and sensitivity indicators
Enable human-in-the-loop corrections with full transparency
Perfect For
Predictive maintenance with self-explanations
Financial or fraud models requiring immediate reasoning
Healthcare and quality systems where traceability is critical
Real-time control loops needing explainable autonomy
Real-Time Intelligence. Zero Compromise.
Xpdeep delivers predictions that are instantly explainable, actionable, and certifiable — enabling operators, auditors, and regulators to trust every result.
Learn more: Explain & Certify • Act • XpViz • XpAct • Time-Series Explainability
ROI Impact: Savings ROI • Growth ROI