Engineers manually scoured dashboards to investigate alerts. Now, they query an AI agent to pinpoint root causes and surface exact fixes.
A global manufacturing enterprise manages a highly complex IT environment containing approximately 550 Microsoft Azure resources within a single architectural monolith.
Site reliability engineering teams were inundated with up to 40 daily performance alerts. Investigating these incidents required manually navigating...
“My vision for the SRE team is to empower them to focus on what truly matters, reducing the time spent on determining root causes. This is where I believe the SRE Agent holds tremendous potential, paving the way for a more efficient and impactful workflow.”
Water, hygiene, and infection prevention services for global industrial markets.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Ecolab's Incident response is part of this use case:
Related implementations across industries and use cases
Comparing quotes and sorting inquiries manually bottlenecked staff. Now, AI handles both while custom agents proactively flag supply risks.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
Scouring foreign technical sources took months. AI now translates and analyzes materials in minutes.
With 4,000 services, manual triage couldn't keep up. AI agents now run parallel checks to pinpoint the root cause in seconds.
A small team manually investigated alerts across 35 AWS accounts. Now, engineers use AI chat to instantly pinpoint system anomalies.
Manual 12-day checks for EU deforestation rules created risk. Now, an AI traces the supply chain in 3 minutes, ensuring full compliance.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
12,000 employees overwhelmed 20 IT agents. AI now resolves routine tickets, cutting calls 30% to support 2x scale without new hires.
Endpoint blind spots exposed critical operations. Now, AI automatically investigates and summarizes alerts so analysts act faster.
Engineers manually scoured dashboards to investigate alerts. Now, they query an AI agent to pinpoint root causes and surface exact fixes.
A global manufacturing enterprise manages a highly complex IT environment containing approximately 550 Microsoft Azure resources within a single architectural monolith.
Site reliability engineering teams were inundated with up to 40 daily performance alerts. Investigating these incidents required manually navigating...
“My vision for the SRE team is to empower them to focus on what truly matters, reducing the time spent on determining root causes. This is where I believe the SRE Agent holds tremendous potential, paving the way for a more efficient and impactful workflow.”
Water, hygiene, and infection prevention services for global industrial markets.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Ecolab's Incident response is part of this use case:
Related implementations across industries and use cases
Comparing quotes and sorting inquiries manually bottlenecked staff. Now, AI handles both while custom agents proactively flag supply risks.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
Scouring foreign technical sources took months. AI now translates and analyzes materials in minutes.
With 4,000 services, manual triage couldn't keep up. AI agents now run parallel checks to pinpoint the root cause in seconds.
A small team manually investigated alerts across 35 AWS accounts. Now, engineers use AI chat to instantly pinpoint system anomalies.
Manual 12-day checks for EU deforestation rules created risk. Now, an AI traces the supply chain in 3 minutes, ensuring full compliance.
Minor updates required 3.5-hour re-recordings. Now, teams use AI avatars to regenerate training videos from slides in 30 minutes.
12,000 employees overwhelmed 20 IT agents. AI now resolves routine tickets, cutting calls 30% to support 2x scale without new hires.
Endpoint blind spots exposed critical operations. Now, AI automatically investigates and summarizes alerts so analysts act faster.