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AI in Production

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About this event

What to expect

Two-day, in-person AI in Production conference in Newcastle (June 4–5, 2026) featuring workshops and conference talks, with a drinks reception included.

AI in Production 2026 brings together practitioners and builders to explore production-grade AI. Hosted by Jumping Rivers at The Catalyst in Newcastle upon Tyne, the event blends practical, hands-on workshops with a full day of talks from industry experts. Attendees will gain actionable insights into deploying, monitoring, and governing AI systems in real-world environments, with a focus on reliability, scalability, and governance in production pipelines.

What to expect

  • A two-day program: Day 1 features an afternoon of interactive workshops, designed to give you hands-on experience with production-ready AI workflows. Day 2 hosts a full conference program with talks from practitioners about real-world deployments, lessons learned, and best practices in MLOps, data quality, monitoring, and governance.
  • Networking and community building: In addition to structured sessions, expect plenty of opportunities to connect with peers, potential collaborators, and speakers over a drinks reception on Thursday evening, included with your ticket.
  • Practical focus: Sessions are geared toward engineers, data scientists, platform teams, and product builders aiming to move AI from pilot to production at scale.

Location and logistics

  • Venue: The Catalyst, 3 Science Square, Newcastle Helix, Newcastle upon Tyne NE4 5TG. An accessible, well-connected venue with proximity to transport links.
  • Dates and times: June 4, 2026, 09:00–17:00 (GMT+1) for Day 1 workshops (afternoon focus); June 5, 2026, 09:00–17:00 for Day 2 conference talks. The schedule reflects the two-day format with in-person programming.
  • Refund policy: Refunds available up to 7 days before the event.

Who should attend

  • AI/ML engineers, platform engineers, data engineers, and product builders who want practical guidance on deploying AI in production.
  • Leaders and teams seeking to improve reliability, governance, data quality, and operational aspects of AI systems.
  • Developers exploring production-ready patterns for monitoring, alerting, scaling, and securing AI deployments.

Why this matters

  • Learn from real-world deployment experiences and connect with a community of practitioners focused on moving AI beyond theory into reliable, scalable production.
  • The two-day format provides balance between hands-on learning (workshops) and strategic talks (confe

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