Tolerance for Non-Determinism in AI-Assisted Incident Management?(github.com)
github.com
Tolerance for Non-Determinism in AI-Assisted Incident Management?
https://github.com/unstructai
2 comments
Exciting topic! Many mixed review on AI in general. But it can do some really awesome things in the Incident Management space.
A great case of AI + IMS is Transposit (I work for them)! Of course AI can get overwhelming and maybe a little noisy at times. We differ by adding a "human-in-the-loop element" which allows you/ your team to have more control over what's automated vs what needs more of a "human touch".
The gist: Transposit is designed to help with the entire on-call lifecycle. We have AI and automation that helps your on-call engineers triage alerts by bringing context to them. We’ve built an AI-powered, Virtual Incident Commander who identifies key moments for your team and reminds them to communicate status updates (and even writes drafts of them for you!).
We are also working on new features that use AI to bring important information like 3rd party service outages to your on-call engineers at the right time as well as dynamically identifying the appropriate engineers to bring into an incident to augment your typical escalation process.
A great case of AI + IMS is Transposit (I work for them)! Of course AI can get overwhelming and maybe a little noisy at times. We differ by adding a "human-in-the-loop element" which allows you/ your team to have more control over what's automated vs what needs more of a "human touch".
The gist: Transposit is designed to help with the entire on-call lifecycle. We have AI and automation that helps your on-call engineers triage alerts by bringing context to them. We’ve built an AI-powered, Virtual Incident Commander who identifies key moments for your team and reminds them to communicate status updates (and even writes drafts of them for you!).
We are also working on new features that use AI to bring important information like 3rd party service outages to your on-call engineers at the right time as well as dynamically identifying the appropriate engineers to bring into an incident to augment your typical escalation process.
Thanks for sharing insights about Transposit. It's great to see other players in the space acknowledge the challenges and opportunities that come with integrating AI into incident management. The "human-in-the-loop" approach is indeed a valuable mechanism to strike a balance.
With UnStruct AI, our goal has always been to seamlessly augment human capabilities without overwhelming them. Your point about AI potentially being "noisy" resonates with our observations. It's precisely why we're seeking feedback and engaging in conversations like this - to understand where the true value lies and to refine our product accordingly.
I think there is so much more that can be done in this space. The potential - if done right and we solve the right use cases and pain points - is huge.
Would love to hear more thoughts from the community on this. When do you think AI-driven interventions are most appropriate in the incident management lifecycle?
With UnStruct AI, our goal has always been to seamlessly augment human capabilities without overwhelming them. Your point about AI potentially being "noisy" resonates with our observations. It's precisely why we're seeking feedback and engaging in conversations like this - to understand where the true value lies and to refine our product accordingly.
I think there is so much more that can be done in this space. The potential - if done right and we solve the right use cases and pain points - is huge.
Would love to hear more thoughts from the community on this. When do you think AI-driven interventions are most appropriate in the incident management lifecycle?
How do you feel about deploying such tools, especially in high-tempo situations like incident management? How do you strike a balance? I'm wondering if these tools might be more appropriate for after-action reviews once the dust has settled?