Cleric

Cleric

AI platform for service reliability engineering

About Cleric

Simplify's Rating
Why Cleric is rated
C+
Rated D+ on Competitive Edge
Rated B on Growth Potential
Rated B on Rating Differentiation

Industries

Enterprise Software

AI & Machine Learning

Company Size

11-50

Company Stage

Seed

Total Funding

$4.3M

Headquarters

San Francisco, California

Founded

2023

Overview

Cleric provides an AI-powered platform that focuses on service reliability engineering (SRE) to help businesses manage their cloud and Kubernetes environments. The platform works by automatically triaging and diagnosing alerts from production applications, which saves product teams from having to manually investigate issues. This self-service tool prioritizes critical problems and suggests root causes without needing traditional runbooks. Unlike its competitors, Cleric offers a subscription-based service that integrates smoothly into existing workflows, allowing companies to enhance their cloud operations and minimize downtime. The main goal of Cleric is to enable enterprises to concentrate on product development while ensuring their operational stability.

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Simplify's Take

What believers are saying

  • Growing demand for AI-driven SRE tools in cloud-native environments.
  • Rising interest in autonomous systems to reduce human intervention in IT operations.
  • Increased adoption of Kubernetes-native solutions for seamless cloud integration.

What critics are saying

  • Competition from established providers like AWS and Google Cloud expanding AI SRE capabilities.
  • Concerns over AI reliability and false positives in alert triaging.
  • Rapid technological changes may outpace Cleric's platform updates, risking obsolescence.

What makes Cleric unique

  • Cleric autonomously triages alerts, reducing manual investigation for engineering teams.
  • The platform integrates data sources to provide root cause analysis with evidence.
  • Cleric offers a subscription-based model, ensuring predictable costs for enterprises.

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Funding

Total Funding

$4.3M

Above

Industry Average

Funded Over

1 Rounds

Seed funding is usually the first official round after pre-seed, when a startup has a prototype or concept. It’s typically used to develop the product, test the market, and start building the team. Investors here are often angel investors or early-stage venture capitalists.
Seed Funding Comparison
Above Average

Industry standards

$3.3M
$2M
Netflix
$2.3M
Instacart
$3M
Robinhood
$4.3M
Cleric

Company News

PR Newswire
Mar 21st, 2024
Cleric Unveils The First Autonomous Ai Site Reliability Engineer

Cleric's AI SRE teammate runs 24/7, triages 1,000s of alerts simultaneously, and only takes five minutes to solve issues in complex cloud infrastructures.Co-founders (Gojek DevOps & ML platform leader + Tecton Principal Engineer & creator of Feast OSS) raise $4.3M in Seed funding, led by Zetta Venture Partners.To transform your organization's productivity, request early access at cleric.io .SAN FRANCISCO, March 21, 2024 /PRNewswire/ -- Cleric announced today the first autonomous AI site reliability engineer (SRE) teammate to free engineering teams from the burden of providing on-call support. Cleric has secured $4.3M in Seed funding led by Zetta Venture Partners with participation from AI infrastructure angel investors including leaders at Google Cloud, Sysdig, Tecton and Neo4J.Cleric co-founders Shahram Anver (CEO) and Willem Pienaar (CTO).Engineering teams managing large-scale, sprawling infrastructure are burdened with on-call support, detracting from their core tasks. This not only imposes a heavy cognitive load but it consumes nearly 80% of tech companies' resources and budgets. Cleric's co-founders, Shahram Anver and Willem Pienaar, saw firsthand the challenges that product and platform teams faced while managing the sprawling infrastructure at Gojek.Cleric eliminates these challenges by enabling engineering teams to resolve orders of magnitude and many issues in a fraction of the time. Cleric operates 24/7, autonomously navigating complex infrastructure and observability systems to identify the root cause of an issue within minutes. It integrates various data sources like code, documentation, and logs to provide a root cause and resolution suggestions with supporting evidence."For the first time, AI can use judgment to operate tools on our behalf

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