Corelayer — Engineering Analytics Platform
Engineering AnalyticsLayer 4UnknownFounded 2025|San Francisco, CA|2-10
Visit websiteWhat is Corelayer?
Corelayer is an AI-powered on-call engineering platform purpose-built for data-intensive, regulated industries like financial services, healthcare, and insurance. Part of YC W2026, the company was founded by Mitch Radhuber (CEO) and Shipra Jha (CTO), both previously at Goldman Sachs where they built large-scale data infrastructure handling hundreds of billions of rows daily.
Unlike traditional infrastructure monitoring that only catches system failures, Corelayer also detects data quality problems — incorrect values, missing rows, duplicates — issues invisible without proactive data monitoring. The platform operates in three phases: Detect (continuous monitoring of logs, metrics, and data stores), Root-Cause and Fix (AI agents debug and suggest fixes within minutes), and Audit (citations with links to relevant logs and code).
For regulated industries where data sensitivity is paramount, Corelayer offers hardware-backed confidential compute environments, PII detection and masking, zero-data retention by default, and read-only access with fine-grained controls. It is SOC 2 Type I compliant and integrates with AWS, GCP, Snowflake, Airflow, dbt, GitHub, Datadog, and more.
Key Features
- ✓AI on-call engineer
- ✓Anomaly detection
- ✓Secure enclave debugging
- ✓SOC 2 compliance
- ✓Regulated industry focus
Pros & Cons
Pros
- +Deep data quality monitoring beyond infrastructure — detects missing rows, incorrect values, and duplicates
- +Purpose-built for regulated industries with confidential compute, PII masking, and SOC 2 compliance
- +Goldman Sachs pedigree with founders who built systems handling hundreds of billions of rows daily
- +Flexible deployment options including cloud-hosted and on-premises for strict data residency
- +System improves from engineer feedback over time through agent learning
Cons
- -No transparent pricing — custom/enterprise-only pricing makes evaluation difficult for smaller teams
- -Narrow industry focus primarily targeting financial services and regulated industries
- -Very early stage 2-person team with SOC 2 Type I only (not yet Type II)
- -Limited public documentation makes it hard to evaluate feature depth externally
Corelayer Pricing
EnterpriseCustom
- ✓Custom pricing based on team size
- ✓SOC 2 compliant
- ✓Confidential compute
- ✓PII masking
- ✓On-prem deployment option
Common Use Cases
Engineering teams in regulated industries (finance, healthcare)
- •On-call automation
- •Anomaly detection in regulated industries
- •Secure incident debugging
- •Healthcare/finance monitoring
Using Corelayer with Respan
Corelayer monitors data infrastructure in regulated industries, while Respan monitors the AI/LLM components of applications. Together they provide comprehensive observability across both data quality and AI model performance.
- ✓Monitor data pipeline health with Corelayer and LLM performance with Respan in a unified workflow
- ✓Correlate data quality issues detected by Corelayer with AI output quality tracked by Respan
- ✓Ensure compliance across both data infrastructure and AI components in regulated environments
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Last verified: March 27, 2026