Problem

Investment firms need to understand a company and its market deeply before committing capital, but commercial diligence is slow, expensive, and difficult to scale. LATO’s materials say that reaching the right people can take weeks, a commercial study can cost more than $300k, and each study typically starts from scratch. The killer use case is commercial due diligence: rapidly validating an investment thesis by learning what customers, operators, and domain experts actually think about a market or company.

Product / Service

LATO is an agent-native research and simulation platform for investors. Its agents find and interview hundreds of verified experts and customers, in any language, producing recordings, transcripts, and analysis of the key themes. The platform then combines those interviews with thousands of public documents and the investment fund’s proprietary data into a completed study in hours rather than weeks.

The resulting study becomes a live market simulation that investors can use to run scenarios and assess where a market may be headed. LATO positions the same workflow for market sizing, competitive mapping, pricing studies, deal sourcing, inbound screening, customer research, and portfolio value creation, giving investment teams faster research with broader primary-market coverage.

Market

LATO competes in B2B investing market research, specifically the emerging category of AI-enabled commercial diligence and agentic market intelligence. The company materials do not name a direct competitor. Its practical competitive set includes legacy diligence and expert-research workflows, as well as adjacent AI products such as AlphaSense, which provides researchers with content including expert interviews, and Keye, which automates deal-file due diligence into structured investor-ready outputs. Those products overlap with parts of LATO’s workflow, although the evidence does not establish them as exact substitutes.

LATO is an early-stage company: Y Combinator lists it as an active Summer 2026 company founded in 2026 with a two-person team in San Francisco. It has disclosed early customer validation from Blume Equity and FoodLabs, and says that 70% of its use cases are research-focused, spanning work from deal sourcing through portfolio support. The available evidence does not disclose revenue, pricing, or a customer count, so LATO should be viewed as showing early commercial traction rather than proven scaled revenue, with its precise pre-revenue status not publicly established.