Corelayer
Winter 2026 NewAI on-call engineer for data-heavy, regulated industries
We’re building the AI on-call engineer for data-heavy, regulated industries like finance, healthcare, and insurance. Engineers in these industries need to inspect data to debug production issues. We continuously monitor logs, metrics, and data for issues and use agents to debug and suggest fixes in minutes. Data is especially sensitive in regulated industries, so we offer on-prem deployments and hardware-backed secure inference environments that let agents safely use production data as context while debugging. Mitch and Shipra founded Corelayer after building data infrastructure together at Goldman Sachs, where they spent many late nights and weekends debugging systems that processed 100s of billions of rows a day.
AI Investor Summary
Corelayer is building an AI on-call engineer to automate data debugging for regulated industries like finance and healthcare. Their solution leverages on-prem deployments and secure inference to handle sensitive data, addressing a critical need for efficient operational support. With a strong technical team from Google and UC Berkeley, they are well-positioned to tackle this large and growing market.
Key Highlights
- ● Founders with strong technical backgrounds from Google and Databricks, and top-tier education.
- ● Addresses a critical pain point in data-heavy, regulated industries with a novel AI-driven solution.
- ● Focus on on-prem and secure inference environments caters to sensitive data needs, a key differentiator.
Risk Factors
- ● Execution risk in building sophisticated AI agents capable of accurate debugging and fix suggestions.
- ● Competition from established observability platforms and emerging AI-native solutions.
- ● Sales cycles in regulated industries can be long and complex.
- ● Demonstrating tangible ROI and cost savings to customers will be crucial.
Founders
Mitch Radhuber is the co-founder and CEO of Corelayer, a Y Combinator startup focused on building a new generation of cloud infrastructure. Prior to Corelayer, he held significant engineering and leadership roles at Google, where he was instrumental in developing and scaling critical cloud services. His expertise lies in distributed systems, cloud computing, and infrastructure engineering.
Shipra Jha is the co-founder of Corelayer, a Y Combinator startup focused on cloud security. Her professional background is rooted in engineering and product leadership, with a strong emphasis on building scalable and secure systems. Prior to Corelayer, she held significant roles at prominent tech companies, contributing to the development of critical infrastructure and security solutions.
Score Breakdown
Strong technical depth from Google and Databricks, with both founders holding MS degrees from UC Berkeley. Mitch's experience in distributed systems and infrastructure at Google, coupled with Shipra's background in cloud security and scalable systems, suggests a solid foundation for building complex infrastructure. Their prior roles indicate a good understanding of the challenges in large-scale cloud environments. [Boost +1: Founder from Google; Founder from Google]
The market for AI-driven debugging and operational support in data-heavy, regulated industries (finance, healthcare, insurance) is substantial and growing. These sectors have immense data volumes, stringent compliance requirements, and high costs associated with downtime and debugging, creating a clear need for efficient solutions. The timing is opportune as AI capabilities mature and adoption in enterprise is accelerating. [Boost +0.5: Hot sector: ai]
The concept of an 'AI on-call engineer' is compelling and addresses a significant pain point. The technical differentiation lies in their ability to handle sensitive data in regulated industries through on-prem deployments and secure inference. This is a strong selling point. However, the defensibility and moat will depend heavily on the sophistication of their AI agents, the quality of their data ingestion and analysis, and the network effects they can build. UX quality is yet to be fully assessed but is critical for adoption.
As a Winter 2026 batch company, traction is expected to be very early. The available news is primarily launch announcements and mentions in YC batch lists, indicating positive initial reception and investor interest in the concept. However, there's no concrete data on revenue, user adoption, or significant partnerships yet, which is typical for this stage but limits the current score. [Boost +2: Tier-1 VC: accel]
News
Corelayer has launched a platform that monitors data and infrastructure for anomalies, using AI agents to debug and suggest fixes for production issues, particularly in data-heavy and regulated industries.
Corelayer's April 2026 update introduces a Model Context Protocol (MCP) server, bulk issue closing, non-interactive CLI authentication, agent-agnostic skills, PII masking, anomaly detection capabilities, and expands its integrations to 15 platforms.
The article highlights Corelayer as an example of AI startups focusing on operational stability and replacing specific job titles, particularly the 'on-call engineer' role, within Y Combinator's Winter 2026 batch.
Corelayer has released several product updates, including a V1 REST API and CLI, agent learnings extraction, and enhancements to dynamic maps and integration reliability, culminating in their General Availability release in December 2025.
Corelayer, founded in 2025 and based in San Francisco, has raised $500K in convertible note funding and is focused on AI-driven on-call support automation for data-heavy, regulated environments.
Corelayer has launched a platform that uses AI agents to monitor data and infrastructure for anomalies, debug issues, and suggest fixes, aiming to reduce the on-call support load for data-heavy industries.
Corelayer, a seed-stage company founded in 2026, has raised $500K and operates as a developer of an AI on-call engineer for debugging production issues.
Corelayer's official website showcases their AI on-call engineer solution for financial services, emphasizing speed, trust, and integration with various platforms.
Corelayer has launched its AI on-call engineer platform designed to detect and fix production issues in data pipelines 15x faster.
Corelayer is developing an AI on-call engineer for regulated industries like finance, healthcare, and insurance, focusing on debugging production issues by monitoring data and infrastructure.
HUGE Magazine features Corelayer's AI on-call engineer, highlighting its ability to debug production issues in data-heavy, regulated industries with a focus on audit trails and PII masking.
Quick Info
- Batch
- Winter 2026
- Team Size
- 2
- Location
- Unspecified
- Founders
- 2
- Scraped
- 4/10/2026