AI events. Find your people.

⌖ Toronto · Hyatt Regency Toronto

Hosted by TESTINGMIND

AI Engineering Summit Toronto 2026 brings 150+ practitioners together for a full day on building, deploying and scaling production AI systems. Taking place on Thursday 29 October 2026, from 9am to 5pm, this in-person summit at the Hyatt Regency Toronto is designed for people turning AI concepts into dependable software. Expect real implementation stories, practical engineering patterns and candid discussion of what it takes to move from code to production, without vendor pitches. What the summit covers The programme is single-track and practitioner-led, with sessions spanning six core themes: - Agentic development: multi-agent systems, tool calling and long-horizon autonomous workflows - AI to production: LLMOps, evaluations, cost and latency management, deployment, monitoring and operating at scale - Responsible AI: red teaming, evaluation frameworks, safety, compliance and governance - AI architecture: RAG patterns, LLM gateways, inference and AI-native system design - AI-first leadership: integrating AI into the software development lifecycle, designing teams and hiring around AI - AI data infrastructure: vector databases, embeddings and the pipelines behind intelligent systems The summit also looks ahead to emerging production standards, including agentic systems and MCP. Rather than focusing only on models or demos, it addresses the architecture, operational discipline and organisational decisions needed to make AI useful, scalable and trustworthy. Who should attend? This is a production-focused event for developers shipping AI-powered products, engineers building intelligent systems, architects responsible for scale and reliability, and technical leaders shaping organisational AI adoption. It is also relevant to compliance and governance professionals working to ensure AI systems are safe and accountable. The content is particularly suited to attendees already involved in building, operating or overseeing AI initiatives. Participants should leave with tools, patterns and informed questions they can bring back to their teams. A conference built for useful conversations… Register for this event

⌖ Singapore · Four Points by Sheraton Singapore, Riverview

Hosted by TESTINGMIND

AI Engineering Summit Singapore is a one-day conference on 3 December 2026 for teams building, deploying and scaling production AI systems. Taking place from 9am to 5pm at Four Points by Sheraton Singapore, Riverview in Singapore, this in-person summit brings together more than 150 engineers, practitioners and technology leaders. The focus is firmly on lessons from people shipping AI into production: practical engineering decisions, proven patterns and honest accounts of what works, without vendor pitches. What to expect The event follows a single-track, single-room format, giving attendees a shared programme and making it easier to continue conversations between sessions. Practitioner-led talks span six core themes: - Agentic development: multi-agent systems, tool calling and long-horizon autonomous workflows - AI to production: LLMOps, evaluations, cost, latency, deployment and monitoring at scale - Responsible AI: red teaming, evaluation frameworks, safety and governance - AI architecture: RAG patterns, LLM gateways, inference and AI-native system design - AI-first leadership: AI in the software development lifecycle, team design and hiring around AI - AI data infrastructure: vector databases, embeddings and the pipelines behind intelligent systems The programme also examines MCP and the technologies likely to become future production standards. Rather than staying at the level of AI demos, sessions are designed to help attendees understand how intelligent systems can remain scalable, reliable, observable and trustworthy after deployment. Who should attend? This summit is built for developers shipping AI-powered products, engineers creating intelligent systems and architects designing for scale and reliability. It is also relevant to engineering and organisational leaders deciding how their teams should adopt AI, alongside compliance and governance professionals responsible for making AI systems safer and more trustworthy.… Register for this event