Grep AI

YC company profile

Self-improving agents that automate your growth bottlenecks

Grep AI is the fastest way to create, optimize, and deploy agents for tedious, complex operational work that slows down your business. Our self-improving agents learn from every run, making them smarter and cheaper as you scale. IG.com a global retail brokerage used our agents to review compliance alerts and now 80% of their customers onboad without manual intervention, doubling first trades and propelling them to a FTSE 100 company.

Customers including Airwallex, Worldpay, Citizens Bank, FV Bank and Shopmonkey have used our agents to automate over 250,000 of operational work across compliance, onboarding, underwriting, corporate due diligence, document verification, merchant categorization, market and competitive research, rev ops and much more.

We founded Grep AI after experiencing firsthand how manual workflows can prevent a business from growing when we ran the platform team at Brex. We're now on a mission to rid businesses of tedious, repetitive so their employees can focus on the most high leverage tasks that matter.

• YC batch: Fall 2026
• Founded: 2023
• Team size: 6
• Location: San Francisco
• Country: US
• Status: Active
• Industry: B2B
• Stage: Early
• Tags: Fintech, AI
• YC partner: Garry Tan

Founders

AJ Asver — Founder/CEO

Building AI agents for high-stakes work you can't afford to get wrong at Grep AI. I previously led AI/ML-related products at Coinbase and Brex. My first startup, Scoopler (YC S08), was acquired by Google, where I worked on integrating AI into Google Photos and Android phones/tablets.

LinkedIn · X

How did your company get started? (i.e., How did the founders meet? How did you come up with the idea? How did you decide to be a founder?)

We met at Brex in 2020, where we worked on the platform team and saw how manual operational work could become a bottleneck to growth. Even straightforward onboarding tasks required people to research information, handle exceptions, and make decisions.

We started Parcha in 2023 to build AI agents for compliance workflows. That gave us firsthand experience with repetitive, high-stakes work where accuracy and control matter. We built Grep AI to make those capabilities available to teams automating repetitive knowledge work across their business.

What's the history of your company from getting started until the present day? What were the big inflection points?

We started in 2023 as Parcha, building AI agents for compliance teams. Working on those workflows taught us how to handle complex research, exceptions, and judgment while keeping people in control.

We also saw the same need beyond compliance. In 2026, we expanded into Grep AI, a managed agent platform for repetitive, high-stakes knowledge work across operations, research, and other business functions. We are now building self-improving agents that learn from repeated work, with the goal of improving accuracy and reducing cost as they scale.

What is the core problem you are solving? Why is this a big problem? What made you decide to work on it?

Businesses are full of repetitive work that still requires research, judgment, and context. Reviewing documents, investigating a business, or researching a prospect can look similar from one case to the next, but exceptions make rigid automation difficult.

The people who understand these jobs often have to do them manually or wait for engineering help. Grep AI lets them describe the work and create managed agents to repeat it, with tools, shared context, and controls. Our focus is work that needs to be accurate and economical when it runs thousands of times.

At IG Group, our agents review screening alerts during customer onboarding, clearing false positives and escalating cases that need manual review. The IG case study reports that activation time for flagged customers fell from 2–3 days to under 10 minutes.

What is your long-term vision? If you truly succeed, what will be different about the world?

We want to rid businesses of tedious, repetitive work so their employees can focus on the highest-leverage tasks. The people who know a workflow best should be able to turn it into a managed agent without having to build and maintain the infrastructure themselves.

As those agents repeat the work, they should become more useful and less expensive to run. Success means teams can grow without manual operational work becoming the bottleneck.

Source: Y Combinator · Retrieved 2026-11-02. Company information is self-reported on YC.