How to Efficiently Deploy Production AI in CX
AI can sound impressive in a demo. Production is different. Join Koen Van Duyse, Head of Solutions Engineering at Replicant, for a technical masterclass on how enterprise conversation data can be transformed into governed, production-ready AI agents without sacrificing control, compliance, or consistency. Learn how to move from prompt-based experimentation to scalable, deterministic automation built for real-world CX environments.
Save Your Spot
If you’re responsible for bringing AI into production, you’re feeling the pressure to move faster, automate more, and prove value.
At the same time, you know what happens when demos outperform reality and new AI tools add complexity, slow teams down, or quietly go unused.
The promise of “AI building AI” is compelling, but only matters if it can translate to a production environment. Can AI really learn from your conversation data and generate agents that reflect how your best team members operate? And if so, how do you ensure those agents remain governed, consistent, and compliant as you scale?
In this masterclass, we’ll break down how enterprise conversation data can be transformed into production-ready agents and what it takes to do it safely.
We’ll explore:
- Why building from prompts and templates can create long-term maintenance risk
- What it really means for AI to learn from your best performers
- How generated agents must be architected with deterministic enforcement and system constraints
- What technical leaders should evaluate to ensure speed does not compromise governance
You’ll leave with a clearer understanding of how to turn your proprietary CX data into higher-resolution automation and scale AI agents without compromising consistency, compliance, or customer experience.
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