Security experts spent 30 minutes manually triaging each threat. Now, AI analyzes logs, cutting triage time to under a minute at petabyte scale.
A cloud-native decision intelligence platform that helps large enterprises translate massive volumes of fragmented cybersecurity logs, alerts, and operational signals into actionable insights.
Security experts required up to 30 minutes to manually analyze raw data and determine which alerts to escalate. Furthermore, the legacy...
“Our principle has been to not be tied to one specific provider or solution, but to always look for the best one. Our increased experience with Google Cloud showed us that, for threat related and security operations use cases, Google Cloud and its AI models are best placed to get the best output.”
Human Managed's Threat analysis is part of this use case:
Decision intelligence platform for cyber, risk, and digital operations.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Helped Human Managed expand its I.DE.A. platform using BigQuery, Dataplex, and Vertex AI.
Related implementations across industries and use cases
Infrastructure upkeep drained engineering time. Parallel AI agents now run security audits in 80 seconds, down from 5 minutes.
Keyword filters missed trust-building scams. Gen AI now analyzes message context to detect complex fraud patterns instantly.
Manual teams couldn't catch scams that vanish in an hour. AI now filters noise and classifies threats, cutting response time to minutes.
Infrastructure upkeep drained engineering time. Parallel AI agents now run security audits in 80 seconds, down from 5 minutes.
Keyword filters missed trust-building scams. Gen AI now analyzes message context to detect complex fraud patterns instantly.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Security experts spent 30 minutes manually triaging each threat. Now, AI analyzes logs, cutting triage time to under a minute at petabyte scale.
A cloud-native decision intelligence platform that helps large enterprises translate massive volumes of fragmented cybersecurity logs, alerts, and operational signals into actionable insights.
Security experts required up to 30 minutes to manually analyze raw data and determine which alerts to escalate. Furthermore, the legacy...
“Our principle has been to not be tied to one specific provider or solution, but to always look for the best one. Our increased experience with Google Cloud showed us that, for threat related and security operations use cases, Google Cloud and its AI models are best placed to get the best output.”
Human Managed's Threat analysis is part of this use case:
Decision intelligence platform for cyber, risk, and digital operations.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Helped Human Managed expand its I.DE.A. platform using BigQuery, Dataplex, and Vertex AI.
Related implementations across industries and use cases
Infrastructure upkeep drained engineering time. Parallel AI agents now run security audits in 80 seconds, down from 5 minutes.
Keyword filters missed trust-building scams. Gen AI now analyzes message context to detect complex fraud patterns instantly.
Manual teams couldn't catch scams that vanish in an hour. AI now filters noise and classifies threats, cutting response time to minutes.
Infrastructure upkeep drained engineering time. Parallel AI agents now run security audits in 80 seconds, down from 5 minutes.
Keyword filters missed trust-building scams. Gen AI now analyzes message context to detect complex fraud patterns instantly.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.