notte's answer

Notte is built with Python and accessible via Python SDK or REST API. It performs deep DOM parsing and uses a semantic abstraction layer informed by graph-based reasoning — though the graph itself isn’t fully materialised in code. The SDK exposes a clean interface for LLM integration.

Handler's answer:

Handler uses AI analysis, TikTok content research, video metadata extraction, creative pattern detection, and a web-based dashboard to help app marketers find and understand winning TikToks.

notte's answer

Notte is purpose-built for LLM agents. It doesn’t just click DOM elements — it understands the intent behind them. That means faster, more reliable agents, no brittle scripts, and seamless integration via API or SDK. It replaces scraping + Playwright stacks with one clean abstraction layer.

Handler's answer:

Handler is focused on TikTok research for app growth, not generic social media management. It helps marketers move faster from “what should we post?” to clear creative direction based on real winning TikToks.

notte's answer

Notte turns the web into structured, semantic maps tailored for LLMs — enabling perception, navigation, and action. Unlike traditional browser automation, Notte abstracts away fragile HTML into high-level actions and natural language descriptions, reducing hallucinations, tokens, and latency.

Handler's answer:

Handler is built specifically for app marketers who want to find what is already working on TikTok. Instead of guessing content ideas, Handler helps teams discover outlier TikToks, understand winning patterns, and decide what to test next.

notte's answer

Developers building LLM agents, automation workflows, or AI-native applications. Early adopters in infra, QA, RPA, and AI tooling who want to go beyond brittle web scraping and fragile automation toward agentic, semantic control of the internet.

Handler's answer:

Handler is made for app founders, growth marketers, mobile app teams, indie app builders, and agencies that use TikTok to grow consumer apps.

notte's answer

Notte was founded by Andrea and Lucas, two ML researchers who met at EPFL in 2019 and have been building together ever since. After working across top research labs, they saw a clear gap: existing browser automation tools weren’t built for LLMs. Notte is their response — a framework that makes the web usable for agents through structured, semantic understanding. It’s designed to bridge research and real-world execution.

Handler's answer:

Handler was created because app teams spend too much time manually scrolling TikTok trying to understand what content works. We built it to make TikTok research faster, clearer, and more repeatable for app marketers.

Handler's answer:

Handler is currently early, so we are not publishing customer names yet. The product is built for app founders, consumer app teams, growth marketers, and agencies working on TikTok-based app growth.