Заявка BentoLabs AI в YC

Spring 2026Active

BentoLabs AI прошел Y Combinator в потоке Spring 2026 как компания из сферы B2B. Ниже: чем занимается компания, кто ее основал, и ее заявка в YC, реконструированная вопрос за вопросом в реальной форме YC.

Поток YC: Spring 2026
Сфера: B2B
Размер команды: 5
Статус: Active
Запущено: 2026

Фаундеры

Abhinav SoniFounder
Kaushik ASPFounder

Чем занимается BentoLabs AI

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.

Заявка BentoLabs AI в YC, реконструирована

Заявка Y Combinator

BentoLabs AI, батч Spring 2026. Реальные вопросы из анкеты, ответы из публичных данных.

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.

21 еще ответ в полной заявке

Founders, Progress, Idea, Equity, Curious, Batch Preference находятся в полной версии. Создайте бесплатную учетную запись, чтобы открыть ее в YC Insights, рядом с каждым другим потоком YC.

Смотреть полную заявку

Часто задаваемые вопросы

Это реальная заявка BentoLabs AI в YC?

Нет. Y Combinator держит поданные заявки в приватности. Это реконструкция: реальные вопросы формы YC, ответы на которые основаны на публичных данных BentoLabs AI (заметки о запуске, бэкграунд фаундеров, описание продукта). Это показывает, как компания вроде BentoLabs AI представила бы себя YC, а не текст, который они подали.