Lili CTO Liran Zelkha on Building AI that Disappears

Why It Matters

By letting existing consumer AI handle interactions, Lili reduces friction for small businesses and creates a scalable competitive edge in fintech data services. The approach could redefine how financial platforms deliver value, prioritizing integration over in‑app experiences.

Key Takeaways

• Fintech AI focus shifts from in-app bots to external assistants
• Lili aims to serve small businesses via any trusted AI
• Goal: owners ask AI about cash flow, receive Lili‑backed answers
• Reduces learning curve, letting entrepreneurs focus on core work
• Sets precedent for API‑first fintech integration with consumer AI platforms

Pulse Analysis

The fintech sector has been caught in an AI arms race, slapping chatbots onto dashboards and adding summary generators to transaction feeds. While these features sound innovative, adoption among small‑business owners remains tepid; many entrepreneurs run their operations with a handful of apps and lack the bandwidth to master new interfaces. This mismatch has prompted a reevaluation of where artificial intelligence can truly add value, especially for firms whose customers prioritize speed and simplicity over flashy tech.

Lili’s chief technology officer, Liran Zelkha, proposes a radical pivot: instead of building a proprietary AI layer, the company will make its financial data consumable by any AI the user already trusts—whether that’s a smartphone assistant, a ChatGPT‑powered chatbot, or a voice‑activated smart speaker. By exposing cash‑flow metrics through robust APIs, Lili enables business owners to ask, for example, “What’s my projected runway for the next quarter?” and receive an answer backed by Lili’s analytics, without opening the Lili app. This "AI that disappears" philosophy aligns with the reality that small‑business founders rarely engage with multiple platforms and prefer a single, familiar conversational interface.

If Lili’s model gains traction, it could spark a broader shift in fintech architecture toward API‑first, AI‑agnostic designs. Companies that lock their data behind proprietary bots risk obsolescence as consumers gravitate toward the AI assistants they already use daily. Moreover, seamless integration raises questions about data security, consent, and the standards needed for reliable financial disclosures across disparate AI ecosystems. For investors and competitors alike, the move signals a new frontier where the value of a fintech platform is measured not by the polish of its own UI but by how effortlessly it can feed accurate, real‑time data into the AI tools users already trust.