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KloudMate Unveils India's First Agentic Observability Platform with Auto-RCA and Self-Healing Workflows

Bengaluru (Karnataka) [India], August 24: Unplanned downtime across cloud infrastructure, applications, and networks costs enterprises between $5,000 and $7,500 per minute; a significant financial hemorrhage according to industry benchmarks. For digital-first businesses, that figure compounds even faster, resulting in disrupted transactions, eroded customer trust, and engineering teams that are forever consumed by firefighting.

ANI Aug 24, 2026 10:30 IST googleads

KloudMate Unveils India's First Agentic Observability Platform with Auto-RCA and Self-Healing Workflows

VMPL
Bengaluru (Karnataka) [India], August 24: Unplanned downtime across cloud infrastructure, applications, and networks costs enterprises between $5,000 and $7,500 per minute; a significant financial hemorrhage according to industry benchmarks. For digital-first businesses, that figure compounds even faster, resulting in disrupted transactions, eroded customer trust, and engineering teams that are forever consumed by firefighting.
AI-native Auto-RCA and Self-Healing Workflows compress incident resolution cycles by upto 50%, optimize operational expenditure, and reclaim engineering time lost to reactive firefighting.
Bengaluru & Texas-based deeptech startup, KloudMate, today announced the launch of its Agentic Observability suite, an AI-native observability platform that detects, investigates, and autonomously resolves incidents, compressing resolution times from hours to seconds.
The launch positions KloudMate among a select group of global technology providers pioneering agentic AI within enterprise-grade observability ecosystems, and marks a pivotal moment for India's fast evolving enterprise technology story.
The suite introduces natural-language querying, Smart Alert Grouping, and Automated Root Cause Analysis (Auto-RCA) with Autonomous Triage, engineered to attack the two primary metrics that define operational economics: Mean-Time-to-Resolution (MTTR) and engineering productivity. In most early deployments, customers have seen MTTR drop by upto 50% and alert noise reduce by upto 70%, while significantly increasing monitoring their coverage.
Extending this intelligence into action, KloudMate has also introduced 'Workflows', a visual, drag-and-drop orchestration engine that lets engineering teams design automated response playbooks for their infrastructure and applications. Workflows enables teams to pre-define deterministic sequences of remediation actions, such as restarting a service, scaling a resource, or rotating a credential, that execute automatically the moment a condition is met (or subject to engineer sign-off for critical workflows).
Human judgment stays in the loop; the toil does not.
A New Paradigm in Observability, SRE-Ops & Incident Management
Traditionally, observability platforms have functioned as passive repositories of telemetry data, i.e. logs, metrics, and traces, that engineers must manually correlate during high-pressure outages. KloudMate's new suite reverses this paradigm entirely. The moment an anomaly is detected, the platform's AI infrastructure autonomously initiates an investigation, correlating disparate signals and surfacing a probable root cause before a human responder is even engaged.
For enterprise leadership, this translates into a tangible shift: reliability stops being a cost-center that scales with headcount, and becomes an autonomous capability that scales with the business. In an environment where engineering talent is scarce and expensive, that is not a convenience. It is a competitive moat.
Commenting on the launch, the founders of KloudMate, Amitava Saha, Bidyut Baruah and Pranab Buragohain unanimously echoed the same sentiments:
"Observability was built to collect data. We built KloudMate to close incidents. For decades, the industry equated observability with data volume: more dashboards, more logs, more alerts, more noise. We have inverted that model. The minute an anomaly surfaces, KloudMate begins investigating, often before an engineer has even acknowledged the alert. This is not about replacing human involvement and judgment. It is about giving engineering teams a decisive headstart, backed by transparent, auditable evidence".
A Milestone for Indian AI & Enterprise Tech.
The announcement arrives at a moment when global enterprises are grappling with escalating tool sprawl, alert fatigue, and mounting operational costs tied to legacy observability stacks, where pricing models have long penalized growth and engineers lose upto 30% of their week triaging false positives.
KloudMate's launch signals a broader inflection point: India's technology story is evolving from services-led delivery, to deep, IP-driven product innovation, that competes on the global stage. As enterprises worldwide race to operationalize AI, the infrastructure that keeps those AI systems reliable becomes mission-critical, and KloudMate is building that layer.
Enterprises and engineering teams can experience KloudMate's Agentic Observability suite by registering at www.kloudmate.com. A detailed technical overview is available on this blog: Observability 3.0 Is Here.
About KloudMate
Based in Bengaluru (India) and Austin, TX (USA), KloudMate is an AI-powered Observability and agentic SRE-Ops platform built on open standards, enabling engineering teams to monitor, troubleshoot, and resolve incidents across modern, distributed systems, with unmatched speed and precision.
KloudMate is also available in the AWS India Marketplace.
Press contact: press@kloudmate.com
(ADVERTORIAL DISCLAIMER: The above press release has been provided by VMPL. ANI will not be responsible in any way for the content of the same.)

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