Corelayer
AI on-call engineer that debugs using data
Winter 2026ActiveB2BEngineering, Product and DesignArtificial IntelligenceDeveloper ToolsB2BEnterprise SoftwareAISan Francisco, CA, USA
Company
https://www.corelayer.comWe’re building AI agents that do on-call support for data-heavy industries like financial services and fintech, healthcare, and insurance.
On-call engineers in these industries need to inspect data to debug production issues. We monitor both data and infrastructure for issues and use AI 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 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.
Verdict
High Signal
Market Opportunity
Targeting financial services, fintech, healthcare, and insurance — all large, high-margin B2B verticals with serious on-call engineering costs and regulatory data requirements. AIOps/observability market is multi-billion dollar TAM. The data-sensitivity angle (on-prem, secure enclaves) creates a defensible wedge in regulated industries that pure SaaS competitors can't easily address. Clear ICP: data-heavy enterprises with complex production systems.
High Signal
Founder Signal
Both founders have 7+ years at Goldman Sachs working on data infrastructure at serious scale (100s of billions of rows/day), giving them deep domain credibility and direct experience with the exact pain point they're solving. Shipra rose to VP at GS after starting as a software engineer, with prior experience at Oracle; Mitch also reached VP-level software engineer at GS after 7+ years. CMU MISM and UMich Computer Engineering are solid technical backgrounds. This is a textbook founder-problem fit.
Medium Signal
Competition
AIOps and incident management space has established players like PagerDuty, Incident.io, Rootly, and FireHydrant, plus AI-native entrants like Shoreline and Moogsoft. The differentiated angle here is data-aware debugging (not just infra metrics) combined with secure on-prem deployment for regulated industries — a genuinely narrower and harder-to-replicate niche. However, large observability platforms (Datadog, Dynatrace) are actively expanding AI capabilities and could encroach.
Medium Signal
Product
No live demo, pricing page, API docs, or named customer logos visible. Product description is substantive — AI agents for on-call debugging with on-prem/secure enclave deployments for regulated industries — but no revenue figures, usage metrics, or customer testimonials cited. Still in early go-to-market phase based on available evidence.
OverallA Tier
Corelayer has textbook founder-market fit: two ex-Goldman Sachs VPs who personally felt this pain at scale and left to solve it. The pivot toward regulated industries (finance, healthcare, insurance) with on-prem/secure enclave deployment is a smart moat-building move that sidesteps pure SaaS competitors. The main risk is product maturity — no visible traction, customer logos, or revenue metrics makes it hard to validate execution beyond the idea stage. The AIOps space is crowded and Datadog/Dynatrace are well-resourced incumbents, but the data-debugging angle in regulated verticals is a defensible niche. Strong A — would upgrade to S with evidence of paying customers.
Active Founders
