Kadoa

AI-powered, self-healing web data extraction for finance

Hand-reviewed by the Toolglade team·Updated Aug 2026

automation#web-scraping#ai#data-extraction#self-healing

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Toolglade’s take

Kadoa's self-healing, LLM-driven approach targets the single biggest weakness of conventional scrapers: breakage when sites change. That is a real and valuable differentiator, and its finance-focused pivot suggests it is leaning into reliability-critical, high-value use cases. The trade-offs are that it is a young company with a narrower public track record, consumption-based pricing that requires estimating your volumes, and LLM-based extraction that still benefits from validation on high-stakes data. Confirm source coverage, accuracy, and costs for your specific needs with the vendor.

About Kadoa

Kadoa is an AI web-data extraction platform built around self-healing agents that adapt to site changes so scrapers do not break. Users declare the data they want and Kadoa retrieves it, with a 2026 positioning focused on finance teams needing reliable feeds. It is an early-stage, seed-funded vendor with consumption-based pricing, best evaluated for reliability-critical extraction after confirming coverage for your sources.

Kadoa uses LLM-based agents to extract structured data from websites without users writing or maintaining selectors. Its central pitch is zero-maintenance, self-healing scrapers: when a target site changes layout, the agents adapt automatically rather than breaking, which is the biggest pain point of traditional scraping. Users specify the data they want, and Kadoa figures out how to retrieve it. By 2026, Kadoa narrowed its positioning from a general-purpose scraper to the Web Data Layer for Finance, with case studies centered on hedge funds, asset managers, and enterprise data teams that need dependable, ongoing data pipelines. It emphasizes reliability, monitoring, and delivering clean structured output at scale. Kadoa is an early-stage company founded in 2023 (associated with Zurich and Toronto) by Johannes Engler, Adrian Krebs, and Tavis Lochhead, backed by a seed investment from VI Partners. As a younger vendor with a finance-focused pivot, it is worth evaluating for reliability-critical extraction, while confirming coverage and pricing for your specific sources directly.

TL;DR

Kadoa is an AI web-data extraction platform with self-healing agents that adapt to site changes, so scrapers do not break. Founded in 2023 and seed-funded by VI Partners, it pivoted by 2026 to focus on finance teams needing reliable feeds. Users declare the data they want rather than writing selectors. Pricing is consumption-based with an evaluation period; it is best for reliability-critical extraction.

Company overview

Kadoa is an early-stage company founded in 2023 by Johannes Engler, Adrian Krebs, and Tavis Lochhead, associated with Zurich and Toronto. It launched as a general-purpose AI scraping platform and by 2026 narrowed its positioning to the Web Data Layer for Finance.

The company raised a seed round (amount not publicly disclosed) from VI Partners, with its most recent disclosed round dated early 2025. As a young vendor, its public track record is still developing.

Product features

Kadoa's core is declarative, LLM-driven extraction: users define a target schema and self-healing agents build and maintain the extraction, adapting when sites change. It emphasizes reliability, monitoring, and delivery of clean structured data via API and webhooks.

Its finance orientation shows in case studies around investment research and enterprise data pipelines, prioritizing dependable ongoing feeds over ad hoc scraping.

Target market

Finance and investment data teams (hedge funds, asset managers) and enterprise data teams that need reliable, low-maintenance web-data feeds, plus other teams frustrated by brittle traditional scrapers.

Buyer personas

End users

Data analysts, quant researchers, and engineers consuming Kadoa's structured feeds.

Buyers

Heads of data, research leads, and technical decision-makers at funds and enterprises.

Key influencers

Finance data practitioners and technical evaluators comparing scraping reliability.

Ideal customer profile

A finance or enterprise data team needing dependable, self-maintaining extraction from many web sources, valuing reliability over the lowest possible cost.

Funding & performance

Kadoa raised a seed round from VI Partners; the amount was not publicly disclosed, with the most recent disclosed round dated early 2025. Treat funding details as limited and verify with the company.

Pros & cons

Pros

Self-healing agents reduce breakage
Declarative: define data, not selectors
Strong fit for reliability-critical feeds
Finance-focused expertise and case studies
API and webhook delivery
Handles ongoing monitoring at scale

Cons

Early-stage vendor with limited public track record
Consumption-based pricing needs volume estimation
LLM extraction still benefits from validation
Narrowing focus to finance may de-prioritize other verticals
No self-hosted option
Coverage for niche sources should be verified

Pricing plans

Flex (self-service)

Consumption-based

Self-service onboarding
No-commitment evaluation period
Usage-based pricing
For small teams trialing the platform

Enterprise

Custom

Higher volume and reliability
Dedicated support
Custom integrations
Finance-focused use cases

Key features

API

Team collaboration

Multi-language

Integrations

REST API, Webhooks, Data warehouse/export, Workflow tools

Input types

url, text

Output types

json, structured data, csv

Best For

Low-maintenance recurring extraction, Finance and investment research data, Sites that change layout often, Teams wanting to define data, not selectors

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Frequently asked questions

What does self-healing extraction mean?+

Kadoa's agents adapt automatically when a target website changes its layout, so extractions keep working instead of breaking, reducing ongoing maintenance.

Who is Kadoa aimed at in 2026?+

It has positioned itself as a web data layer for finance, focusing on hedge funds, asset managers, and enterprise data teams needing reliable feeds, though it can be used more broadly.

Do I write scraping code with Kadoa?+

No. You define the data you want, and Kadoa's AI agents determine how to extract it, which is the core of its declarative approach.

How is Kadoa priced?+

Pricing is consumption-based with a self-service Flex plan and a no-commitment evaluation period, plus custom enterprise options. Confirm specifics with the vendor.

Is Kadoa a mature, established company?+

No. Kadoa is an early-stage company founded in 2023 and seed-funded, so evaluate its reliability and source coverage for your specific needs.