Corelayer: AI on-call engineer for data pipelines

Hey everyone! 👋

We’re Mitch and Shipra - before Corelayer, we built data infrastructure at Goldman Sachs where we spent many late nights and weekends debugging systems that processed 100s of billions of rows a day.

TL;DR

When you’re on call in data-heavy industries like fintech, healthcare, or insurance, you need to inspect data to debug production issues. We built a platform that monitors both data and infrastructure for anomalies and uses AI agents to debug and suggest fixes in minutes.

Corelayer Launch Video

On-call support is painful and expensive

All engineers hate being on call. Production issues kill velocity, erode user trust, and become more and more costly as companies scale.

Fortune 100s spend $100M+/year on first-line-of-defense production support.

Smaller companies can’t afford to burn scarce engineering resources on time-consuming support and maintenance.

The (sensitive) data problem

If you’re a backend engineer at a fintech, you probably own a service that queries data, applies some business logic, and stores the result somewhere (i.e., a data pipeline).

When this service is running in production, you’ll see two failure modes:

1. Exceptions in logs and/or failing jobs
2. Bad data produced by your service

“Bad data” can mean anything from incorrect values to entirely missing or duplicated rows.

This is really common in certain products and industries, but you’re totally blind to these errors without monitoring data for anomalies and querying data while debugging.

In regulated environments where this problem is prevalent, production data is sensitive, which is another constraint we have to solve for.

Corelayer solves this

We continuously monitor logs, metrics, and data for anomalies and use AI agents to debug, root-cause, and suggest fixes for issues.

We also filter out false positives and group related issues to reduce alert noise.

Every team is different. We take feedback from human engineers so our agents learn your systems and improve over time.

Data is especially sensitive in regulated industries. We’re SOC 2 compliant, offer on-prem deployments and confidential compute (hardware-backed secure environments), and expose an audit trail of each step performed by the agent with citations.

Our Asks

Does your team deal with data or integrations and spend more time on production support than you’d like? Let’s chat.

Can you connect us with an engineering leader at a finserv, fintech, healthcare, or insurance company? Reach out at founders@corelayer.com.

Thank you!