BentoLabs AI YC 지원서

Spring 2026Active

BentoLabs AI은(는) Spring 2026 배치에서 B2B 회사로 Y Combinator를 거쳤습니다. 아래에는 회사의 사업 내용, 창립자, 그리고 실제 YC 양식에 맞춰 재구성한 YC 지원서가 있습니다.

YC 배치: Spring 2026
산업: B2B
팀 규모: 5
상태: Active
출시됨: 2026

창업자

Abhinav SoniFounder
Kaushik ASPFounder

BentoLabs AI의 사업 내용

BentoLabs is the monitoring and learning layer for long-running agents. We detect when agents silently fail or drift from the user's goal, system prompt, or tool contracts, show affected users and root cause, and suggest the prompt, skill, or harness fix. As more teams deploy agents, keeping them reliable in production becomes mission-critical. Bento sits directly in the production loop and gives teams the operational leverage required to scale agent ecosystems without scaling human firefighting alongside them. The result is a system that turns opaque agents into agents that can be monitored, debugged, and improved continuously. The founders learned this problem at Emergent (YC S24), where they built and operated production coding agents used by 5M+ users. Abhinav was hire #1 and helped Emergent hit SWE-Bench #1 and scale from $0 to $100M ARR in just 8 months. Kaushik was hire #2, led full-stack engineering at Emergent, and was key to building the infrastructure that made production agents reliable, observable, and debuggable. Bento's self-learning engine has also lifted ARC-AGI-3 (internal) by 2.6x and Terminal-Bench 2.0 (internal) from 42.2% to 52.4% pass@1 with the same model, tools, and budget.

BentoLabs AI의 YC 지원서, 재구성됨

Y Combinator 지원

BentoLabs AI, Spring 2026 기수. 공개 데이터를 기반으로 작성된 실제 지원 질문.

Founders2
Company7
Progress7
Idea4
Equity3
Curious2
Batch Preference1

Company

Company name

BentoLabs AI

Describe what your company does in 50 characters or less.

Monitoring and learning layer for long-running agents

What is your company going to make? Please describe your product and what it does or will do.

We built a system that monitors long-running AI agents in production, detects silent failures or when they drift from their intended goals, system prompts, or tool contracts. BentoLabs shows affected users and root causes, then suggests fixes like prompt, skill, or harness improvements. It sits directly in the production loop so teams can scale agents without massively scaling human firefighting.

Where do you live now, and where would the company be based after YC?

We live in San Francisco and will keep the company based here after YC.

Explain your decision regarding location.

San Francisco is where both of us are based and where our early customers and ecosystem are. Staying here keeps us close to product feedback and potential partners.

전체 지원서에서 21개의 추가 답변

Founders, Progress, Idea, Equity, Curious, Batch Preference는 전체 버전에 있습니다. 무료 계정을 만들어 YC Insights에서 모든 YC 배치 옆에 열어보세요.

전체 지원 보기

자주 묻는 질문

BentoLabs AI의 실제 YC 지원서인가요?

아닙니다. Y Combinator는 제출된 지원서를 비공개로 유지합니다. 이것은 재구성된 것입니다. 실제 YC 양식 질문에 BentoLabs AI의 공개 데이터(출시 노트, 창업자 배경, 제품 설명)를 기반으로 답변했습니다. BentoLabs AI과 같은 회사가 YC에 어떻게 자신을 소개하는지 보여주며, 그들이 제출한 텍스트는 아닙니다.