Hybrid AI and Predictive AI success stories at MLW's HYBRID AI 2026 in San Francisco this May

Predictive AI Breakthrough: Driving Decisions with Expected Value, Not Raw Model Score

In this session, Gooder AI CTO Luba Gloukhova will cover the most underutilized – yet shockingly simple – way to multiply predictive AI’s value. Instead of driving decisions with the raw model score, drive decisions with the EXPECTED VALUE (calculated with the model score, and at least one business-side factor). This represents a paradigm shift only because it is very rare and very impactful – it’s a straightforward “no-brainer,” both technically and conceptually.

Luba will show demos of how this works – and how incredibly WELL it works – across several use cases.

More info here.

Profit, Not AUC! Using Gooder AI to Maximize Predictive AI’s Value

GenAI pilots often stall at the last mile—reliability. HP ships a hybrid AI reliability layer that fuses generative AI with predictive ML and humans-in-the-loop to make deployments robust. Samaresh shares the production patterns HP use across HP platforms (e.g., Z Boost, AI Studio, Hydra): guardrail policies that expand over time, retrieval and output validation with predictive models, confidence-aware routing between GenAI/predictive/HITL, and telemetry (success rate, hallucination/override rate, p95 latency, cost). Attendees get a reference architecture, rollout playbook (canary/shadow), and KPI templates to move from demo to dependable—turning AI’s potential into realized value.

More info here.

In the world of fraud detection, generative AI has unlocked remarkable new capabilities for analytics, and as a result, companies are racing to develop ways to explore data, summarize evidence, and build fraud-detection workflows. It has become clear that hybrid solutions – combining genAI and traditional machine learning –  are most effective when solid business use cases are paired with curated data, human oversight, and statistical rigor. 

Attendees will learn why fraud detection remains stubbornly difficult in retail and other verticals, how to design a genAI workflow with human-in-the-loop safeguards, and how ML models and genAI systems complement each other rather than compete to deliver real value for organizations. 

More info here.

See the Complete Agenda and speakers from these leading brands:

What's different about Hybrid AI 2026?

How can practitioners get genAI pilots to production – and get predictive AI from development to deployment – considering that the success rates are still extremely low?

Join the leading experts tackling these issues at HYBRID AI 2026. Take the opportunity to talk to them, as well as listen and and find the solutions to some of your key 2026 challenges in machine learning, hybrid AI and predictive analytics.

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