Enterprise AI in Production — Meet-up
Register for the meet-up | Members-only | 19 June 2026 | PhonePe, Bellandur, Bengaluru
The focus is on executable knowledge, operational depth, and systems that are already meeting reality.
The central question driving this event is:
How do you know it’s working?
Every submission should answer this with concrete evidence drawn from evaluation pipelines, observability and tracing, architecture decisions, operational trade-offs, failure analysis, latency and reliability data, or cost benchmarks.
If you can show it running in production, show it.
Submissions open: demos and lightning talks
Anchor talks are confirmed. We are still accepting submissions for live demos and lightning talks.
Deadline: 15 June 2026
Live demos — 15 minutes
Live demonstrations of production-grade AI systems. Not prototypes. Not conceptual walkthroughs.
Show execution traces, failure handling, evaluation outputs, rollback behavior, observability tooling, orchestration logic, cost signals, or operational controls. We especially value demos that show failures, debugging, trade-offs, and operational safeguards.
Lightning talks — 12 minutes
Short, sharp, and insight-dense. One orientation slide, then the thing itself.
Strong lightning talks are grounded in operational metrics, incident learnings, deployment trade-offs, and architectural revisions.
Who should submit?
- AI/ML and platform engineers operating production systems
- Backend engineers building AI systems
- DevOps, SRE, and AppSec practitioners
- Engineering leads running AI initiatives
- Governance and compliance practitioners
You do not need a perfect success story. Operational failures, architectural rewrites, and hard-earned lessons are equally valuable.
About the editor
Ramakrishna Reddy Yekulla leads technical strategy and AI operationalization at Red Hat’s Data + AI group. A long-time open-source contributor across Fedora, Django, GNOME, and GlusterFS, his interests span AI infrastructure, systems architecture, functional programming, and large-scale operational engineering.
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