Corelayer
Product & Competitive Intelligence
Automates on-call engineering for regulated industries with AI investigation and remediation.
Company Overview
Builds an AI agent platform that automates on-call engineering and incident response for regulated industries using proprietary deep research and investigation agents that monitor data and infrastructure.
Competitive Advantage & Moat
Product Roadmap & Public Announcements
SOC 2 Type I compliant. Hardware-backed secure environments and on-prem deployment for regulated data. Automated remediation including AI-generated pull requests. Deep Research Agent and Investigation Agent for contextual diagnostics. Documentation at docs.corelayer.com, ROI calculator, and live app at app.corelayer.com.
Signals & Private Analysis
Multi-agent orchestration. Confidential compute and PII redaction for regulatory audits. Goldman Sachs pedigree provides Wall Street network for early customers. Fortune 100s spend $100M+/year on first-line-of-defense production support. Expansion into government and energy likely.
Product Roadmap Priorities
AI-powered continuous monitoring that automatically detects anomalies across production systems, logs, and data pipelines in regulated industries.
An AI watchdog constantly scans your systems and alerts you the moment something looks off, before it becomes a full-blown outage.
It's like having a smoke detector that not only beeps when there's smoke but also tells you which room, what's burning, and whether you should grab the extinguisher or call 911.
AI agents that automatically investigate production incidents and identify root causes in minutes by mapping system and data flows.
Instead of engineers spending hours digging through logs at 3 AM, an AI agent traces the problem back to its source in minutes and explains exactly what went wrong.
It's like a detective who already has the blueprint of the entire building memorized, so when something breaks, they walk straight to the broken pipe instead of checking every room.
AI agents that automatically suggest fixes and generate pull requests to remediate production bugs and incidents.
The AI doesn't just find the bug — it writes the fix and submits a pull request so your engineers can review and merge instead of scrambling to code a patch at midnight.
It's like having a mechanic who not only diagnoses the weird engine noise but also orders the right part, installs it, and hands you the receipt — you just have to say "go ahead."
AI-generated transparent investigation documentation with full citations from logs and data sources for regulatory compliance and audit readiness.
Every time the AI investigates an issue, it automatically writes up a detailed report with receipts — so when auditors come knocking, you're already ready.
It's like having a court stenographer who follows your IT team around 24/7, perfectly documenting everything so you never have to reconstruct what happened from memory.
Company Overview
Key Team Members
- Mitch Radhuber, Co-Founder & CEO
- Shipra Jha, Co-Founder & CTO
Founder Force Multiplier
Mitch Radhuber (UMich Computer Engineering) and Shipra Jha (CMU MISM, ex-Oracle) both reached VP-level at Goldman Sachs building data infrastructure, where they spent many late nights debugging systems processing hundreds of billions of rows per day. Textbook founder-problem fit: they lived the on-call pain before building the solution. Featured in Forbes as one of the 21 most promising startups from YC's latest batch.
Funding History
- 2024-2025 | Mitch Radhuber and Shipra Jha co-found Corelayer.
- 2025 | SOC 2 Type I achieved.
- 2026 | Accepted into Y Combinator W26 batch.
Competitors
- AIOps: PagerDuty, Datadog, Splunk/Cisco.
- Incident Response: Shoreline.io, Rootly, FireHydrant, incident.io.
- AI-Native Ops: Selector AI, BigPanda, Moogsoft.
- Monitoring: New Relic, Dynatrace, Elastic.
