Enterprise AI in Production: Mumbai Call for Proposals

Share what it takes to run AI inside an enterprise: architectures, trade-offs, and lessons from production.

Zainab Bawa

Zainab Bawa

@zainabbawa

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Submitted Oct 2, 2026

{Add your session title and a one-line pitch describing what the audience will learn}

{Describe your session in 2 paragraphs, totalling 200–400 words. Explain the problem, what you implemented, the key decisions you made, and the outcome}

{Summarise your architecture: components, data flows, models, and tools used. Add a diagram or a link to one if available}

{Share production evidence: scale, time in production, measured results, and how you measured them. Clearly identify approximate or anonymised figures}

{Describe at least one failure or trade-off: what went wrong, what you changed, or what you would do differently}

{Mention 3 specific takeaways that attendees can apply in their own work}

{Describe the audience your session will benefit and any knowledge or experience they should already have}

{Choose your preferred format: a 30-minute talk or a 45-minute deep dive, including questions}

{Add your bio: name, role, organisation, and a brief description of your relevant experience. Include your contact details and a professional profile link. Links to prior talks or writing are optional}

{Disclose any commercial interests in the tools or products discussed and any confidentiality constraints. Confirm your availability to speak in Mumbai on 31 October 2026, between 11 AM and 4 PM IST, and participate in editorial preparation. All talks will be recorded, and live streaming will be available for Fifthel annual members}

{Optional: add a link to draft slides in PDF or PPT format, with commenting access enabled where supported}

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