Operations | Monitoring | ITSM | DevOps | Cloud

Why do so many AI pilots succeed in testing but fail to reach production? In this webinar, Resolve and IT leaders from RisePoint explore one of the biggest challenges facing enterprise AI adoption today: trust. While organizations are investing heavily in AI agents and automation, many initiatives stall before deployment due to governance concerns, compliance requirements, risk management, and lack of operational visibility.

The real unlock is flagging what actually needs human review, not shipping 5,000-line PRs and hoping for the best.

The era of token maxing is over. When Claude Fable 5 launched last week at $10/$50 per million tokens - double the price of Opus 4.8 - it was a clear reminder that the most powerful model isn't always the right model. Not every task needs the Ferrari. The fastest way to burn your Al budget is sending every request to the most expensive model by default. The real question for the next phase of Al cost management isn't "can this model do the job?" — it's "is it the right model for the job?".

IT documentation doesn't have to be a wall of jargon. Here's how to use AI to compress technical information into user-facing docs that are clear, fast, and actually useful.

Sandboxing your AI agent is only half the story. The other half is where your data goes when it hits your LLM provider's API. In this clip from our secure execution agents webinar, Ben Norris, founding engineer at relaxAI, explains why the sovereignty of your AI provider matters just as much as the security of your agent's environment and why relaxAI was built on a sovereignty-first principle, with inference running exclusively in the UK and no foreign data transfer.