Adps AI
AI-native SRE platform that detects, diagnoses, and resolves incidents autonomously.
Adps AI is a compelling choice for cloud-native SRE teams seeking to reduce on-call burden with autonomous incident response. However, its opaque pricing and reliance on AWS/Kubernetes make it difficult to evaluate without a demo, and smaller teams may find it inaccessible.
- SRE teams looking to reduce on-call burden with autonomous incident response
- DevOps engineers managing large-scale Kubernetes clusters
- Platform engineering teams automating cloud-native operations
- Organizations seeking to move from reactive firefighting to proactive, autonomous SRE
- Teams without cloud or Kubernetes environments
- Organizations requiring custom on-premise deployment
- Non-technical users seeking no-code automation tools
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In short
Adps AI — AI-native SRE platform that detects, diagnoses, and resolves incidents autonomously. Best for SRE teams looking to reduce on-call burden with autonomous incident response, DevOps engineers managing large-scale Kubernetes clusters, Platform engineering teams automating cloud-native operations. Contact Sales pricing.
What's new in Adps AI
Checked 14 days agoAcross the latest 5 updates: 5 changelog entries.
June Jetstream Update
One-click optimize 30% faster for complex sites; real-time alerts via email/mobile.
May Surge Update
Unified Analytics & Monitoring hub; new Performance Trends graph; PageSpeed integration.
March Momentum Update
JS/CSS minification 25% more efficient; new Code Health report in Analytics.
February Flash Update
Image compression 15% faster; AVIF support; pre-optimization preview tool added.
Launch Blitz Update
One-click optimize 20% faster; onboarding tutorial and welcome dashboard for new users.
Viability Score
How likely is Adps AI to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Real-time incident detection across cloud and Kubernetes
- Automated root cause analysis across logs, metrics, traces, changes
- Self-healing infrastructure with automatic rollback, restart, scaling
- Proactive anomaly detection and healing
- Kubernetes HPA/VPA autoscaling
- Smart traffic routing with service mesh
- Real-time cluster performance tuning
- Observability with metrics, logs, traces, Kubernetes events
- Service-level indicators and objectives (SLIs/SLOs)
- Git change intelligence and CI/CD agents
- AIOps detection and anomaly detection agents
- Incident-SRE and incident-reliability agents
- Policy-driven safe remediation actions
- Continuous learning to prevent repeat incidents
- AI-native SRE platform with specialized AI agents
About Adps AI
Adps AI is an AI-native SRE platform designed for DevOps and SRE teams that manage production environments across cloud, Kubernetes, and CI/CD pipelines. It uses a network of specialized AI agents to continuously monitor systems, perform root cause analysis, and execute policy-driven remediation—reducing MTTR by up to 99%. The platform offers real-time incident detection, automated root cause analysis across logs, metrics, traces, and changes, and self-healing infrastructure with automatic rollback, restart, and scaling. It also provides Kubernetes intelligence features like HPA/VPA autoscaling, smart traffic routing with service mesh, and real-time cluster performance tuning. Observability is unified with metrics, logs, traces, and Kubernetes event tracking, plus SLIs/SLOs. Unlike traditional alerting tools such as PagerDuty, Adps AI goes beyond detection to autonomous remediation, but its pricing is not publicly listed—requiring a demo—and it is primarily focused on cloud-native environments.
Behind the Verdict
Adps AI aims to be the autonomous SRE layer that many DevOps teams dream about—detecting, diagnosing, and fixing incidents without human intervention. For organizations running large-scale Kubernetes clusters and cloud-native stacks, this could be transformative, cutting MTTR from hours to seconds. The platform's network of specialized AI agents (Git Change Intelligence, AIOps Detection, Incident-SRE, etc.) provides granular coverage across the incident lifecycle. Where it falls short is in transparency: there's no public pricing for the SRE platform (the pricing page only shows a separate website optimization product called 'Jet'), and the heavy AWS/Kubernetes focus means teams outside that ecosystem may need to look elsewhere. Compared to PagerDuty or Opsgenie, Adps AI replaces humans in the loop for remediation, which is a major leap but also a risk for teams that want manual approval gates. We'd recommend this for mature cloud-native organizations ready to automate incident response, but suggest a thorough evaluation via the demo before committing.
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Use Cases
- Automatically detect and resolve Kubernetes pod failures without manual intervention
- Reduce MTTR from hours to seconds for cloud production incidents
- Perform root cause analysis by correlating logs, metrics, and traces
- Self-heal AWS infrastructure by automatically rolling back faulty deployments
- Monitor and remediate CI/CD pipeline failures using AI agents
Limitations
- Pricing for the actual SRE platform is not publicly available; the listed plans on /pricing appear to be for a different product (website optimization).
- The platform likely requires a demo or sales conversation.
- Model training and accuracy depend on integration depth with existing monitoring tools.
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