BEGIN:VCALENDAR VERSION:2.0 PRODID:-//HasGeek//NONSGML Funnel//EN DESCRIPTION:Call for Proposals X-WR-CALDESC:Call for Proposals NAME:Enterprise AI in Production X-WR-CALNAME:Enterprise AI in Production REFRESH-INTERVAL;VALUE=DURATION:PT12H SUMMARY:Enterprise AI in Production TIMEZONE-ID:Asia/Kolkata X-PUBLISHED-TTL:PT12H X-WR-TIMEZONE:Asia/Kolkata BEGIN:VEVENT SUMMARY:Enterprise AI in Production DTSTART:20260619T083000Z DTEND:20260619T123000Z DTSTAMP:20260601T180109Z UID:session/smDc6DRnijsbjn8bZeNPQ@hasgeek.com SEQUENCE:22 CREATED:20260420T050805Z DESCRIPTION:## Call for talks\, demos & discussions\n\n### Enterprise AI i n Production meet-up\n\n**19 June 2026 | Bengaluru**\n\nThe focus is on ex ecutable knowledge\, operational depth\, and systems that are already meet ing reality.\n\nThe central question driving this event is:\n\n> **How do you know it’s working?**\n\nEvery submission - whether a talk\, demo\, d iscussion\, or case study - should answer this with concrete evidence draw n from:\n* evaluation pipelines\,\n* observability and tracing\,\n* archit ecture decisions\,\n* operational trade-offs\,\n* failure analysis\,\n* la tency and reliability data\,\n* or cost benchmarks.\n\nIf you can show it running in production\, show it.\n\n---\n\n## What we are looking for\nWe want submissions from teams building and operating AI systems under real c onstraints:\n* latency\,\n* scale\,\n* governance\,\n* infrastructure cost \,\n* enterprise integration\,\n* reliability\,\n* security\,\n* and organ izational complexity.\n\nThis is a conference for practitioners navigating the messy middle between:\n\n> “the demo worked”\n> and\n> “the sys tem survived production.”\n\n---\n\n# Submission formats\n\n## 1. Anchor talks\n### 25-minute technical deep dive + 5-minute Q&A\nAnchor talks set the intellectual frame for the day by examining the gap between prototype AI systems and production reality.\n\nWe are looking for CTOs\, principal engineers\, architects\, and senior practitioners willing to share the re al architecture and operational lessons behind deployed systems.\n\n### Th emes we are especially interested in\n* Workflow orchestration across ente rprise systems\n* Multi-agent architectures and execution models\n* Sovere ign or air-gapped AI deployments\n* AI infrastructure and inference platfo rms\n* Evaluation systems and deployment safety\n* AI observability and tr acing\n* Governance\, auditability\, and compliance\n* Reliability enginee ring for agentic systems\n* Human-in-the-loop escalation architectures\n* Cost-aware AI systems and inference optimization\n\n### Strong anchor talk s should include\n* what worked\,\n* what failed\,\n* what was thrown away \,\n* what the metrics revealed\,\n* and the one architectural decision yo u would change today.\n\n**Requirement:** No roadmap slides. No future vis ion decks.\n\n---\n\n## 2. Live demos\n### 15 minutes each\nThese sessions are the core of the conference.\n\nWe are specifically looking for:\n\n> live demonstrations of production-grade AI systems.\n\nNot prototypes. Not conceptual walkthroughs.\n\nShow:\n* execution traces\,\n* failure handli ng\,\n* evaluation outputs\,\n* rollback behavior\,\n* observability tooli ng\,\n* orchestration logic\,\n* cost signals\,\n* or operational controls .\n\n### Example areas\n* Multi-agent systems with retries\, escalation\, and trace visibility\n* Evaluation pipelines catching real regressions in CI/CD\n* RAG systems with measurable hallucination reduction\n* AI-powered internal tooling and developer workflows\n* AI governance and policy enfo rcement systems\n* LLM routing\, caching\, and inference optimization\n* M odel evaluation dashboards and feedback loops\n* Long-running workflow orc hestration\n* AI incident debugging and recovery tooling\n* Tool use / fun ction-calling reliability at scale\n* Multimodal retrieval systems with at tribution\n* GPU utilization and inference infrastructure tooling\n\n### W e especially value demos that show\n* failures\,\n* debugging\,\n* trade-o ffs\,\n* and operational safeguards.\n\n---\n\n## 3. Lightning talks\n### 12 minutes each\nLightning talks are short\, sharp\, and insight-dense.\n\ nOne orientation slide. Then the thing itself.\n\n### Suggested themes\n* Real production inference costs\n* Evaluation methodologies that actually worked\n* AI governance in enterprise environments\n* Prompt rollback and deployment strategies\n* Agent failure modes and mitigation patterns\n* Me asuring business impact beyond token usage\n* Operating AI inside regulate d environments\n* Reusable agent skill systems\n* Human review and escalat ion patterns\n* AI deployment pipelines and release engineering\n* Observa bility strategies for agent workflows\n* Organizational lessons from deplo ying AI internally\n\nWe strongly encourage talks grounded in:\n* operatio nal metrics\,\n* incident learnings\,\n* deployment trade-offs\,\n* and ar chitectural revisions.\n\n---\n\n## 4. Startup showcase\n### Live product demonstration\nNo pitch decks.\n\nThis is for startups willing to demonstr ate:\n\n* real workflows\,\n* real operational problems\,\n* and real impl ementation details.\n\nWe are especially interested in startups solving:\n * AI infrastructure\,\n* evaluation\,\n* governance\,\n* observability\,\n * agent orchestration\,\n* or enterprise integration problems.\n\n---\n\n# # 5. Birds of a Feather (BOF) discussions\nBOFs are discussion-first rooms for practitioners dealing with difficult operational questions.\n\nNo pre sentations required.\n\nBring:\n* a hard problem\,\n* a failed experiment\ ,\n* an architectural dilemma\,\n* or a question you want debated deeply.\ n\n### Possible BOF themes\n* Agent systems that failed unexpectedly\n* Ev aluation systems that actually work in production\n* Understanding and com municating AI infrastructure cost\n* RAG vs fine-tuning: where the line ch anges\n* AI governance in large organizations\n* Observability for long-ru nning agent workflows\n* Managing “agent sprawl” across teams\n* AI su pply chain and model integrity\n* Prompt/version rollback strategies\n* Op erational debugging for AI systems\n\nFinal BOF topics will be shaped coll aboratively with participants on the day of the event.\n\n---\n\n# Who sho uld submit?\nWe are especially interested in submissions from:\n* AI/ML en gineering teams\n* Platform and infrastructure engineers\n* Backend engine ers building AI systems\n* Enterprise architects\n* AI platform teams\n* D evOps and SRE practitioners\n* Applied AI teams\n* Governance and complian ce practitioners\n* Internal tooling teams\n* Engineering leaders running AI initiatives\n\nYou do not need a perfect success story to submit.\n\nOp erational failures\, architectural rewrites\, scaling bottlenecks\, and ha rd-earned lessons are highly valuable.\n\n---\n\n# What strong submissions usually include\nStrong submissions typically contain:\n* a concrete prod uction problem\,\n* system architecture details\,\n* operational lessons\, \n* metrics or evaluation methods\,\n* trade-offs\,\n* failure analysis\,\ n* cost or reliability considerations\,\n* and implementation specifics.\n \n---\n\n# How submissions will be reviewed\nSubmissions will be evaluated on:\n\n* technical depth\,\n* operational specificity\,\n* originality\,\ n* usefulness to practitioners\,\n* clarity of lessons learned\,\n* and re levance to production AI systems.\n\nPreference will be given to talks gro unded in:\n* real deployments\,\n* measurable outcomes\,\n* and engineerin g trade-offs.\n\n---\n\n## Deadline for submissions\n**1 June 2026**\n\n-- -\n\n## About the editor\nRamakrishna Reddy Yekulla leads the technical st rategy and operationalization of AI models within Red Hat’s Data + AI gr oup.\n\nA long-time open-source contributor\, he has worked on projects in cluding Fedora\, Django\, GNOME\, and GlusterFS. His interests span AI inf rastructure\, systems architecture\, functional programming\, and large-sc ale operational engineering.\n\n---\n\n## Queries & contact information\n 💬 Comment on the discussion forum:\n[Enterprise AI in Production discus sions](https://hasgeek.com/fifthelephant/enterprise-ai-in-production/comme nts?utm_source=chatgpt.com)\n\n📞 Call/WhatsApp: +91 7676332020\n📧 Em ail: [info@hasgeek.com](mailto:info@hasgeek.com)\n LAST-MODIFIED:20260525T154239Z LOCATION:Bangalore - https://hasgeek.com/fifthelephant/enterprise-ai-in-pr oduction-cfp/ ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/enterprise-ai-in-production-cfp/ BEGIN:VALARM ACTION:display DESCRIPTION:Enterprise AI in Production in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT END:VCALENDAR