--- title: "About Kordy and its founder Ziv Kaspersky" description: "Kordy is an AI visibility tracker for vendors of technical products, founded in 2026 in the USA by Ziv Kaspersky. It grew out of a study of how coding agents such as Claude Code, Codex, Antigravity and Cursor choose vendors. Here is who builds it and how it measures." url: https://kordy.io/about/ --- about # Kordy measures what the agents say, so you can change it Kordy is an AI visibility tracker for vendors of technical products (developer tools, infrastructure, security, DevOps, data and AI tooling), founded in 2026 in the USA by Ziv Kaspersky. It replays a category's buying prompts every week inside four coding agents (Claude Code, Codex, Antigravity, Cursor; Starter and Growth plans pick 3) and five chat models, records which vendor each one names and which page it cites, and turns the gap into a ranked fix list. The dashboard lives at app.kordy.io. Kordy started as a measurement harness built for consulting clients, not as a product. The product exists because the measurements kept surprising the people who saw them. ## Why Kordy exists In July 2026 we ran more than 500 sessions across 11 product categories and put the same buying questions to coding agents and to the chat apps from the same makers. Claude Code and the Claude.ai chat app named a different number one pick on 48% of them. The three coding agents agreed with each other on the top pick 69% of the time. That meant a chat-assistant dashboard could not tell a vendor of a technical product what a coding agent says about them. When someone asks the agent in their terminal which cache, queue or auth provider to use, the answer comes from a different surface, drawing on different sources: across our sessions through September 2026, 59% of the sites the chat assistants cited never showed up in any coding agent's sources on the same question. The signals differ too. In our data, project maturity was the strongest signal correlated with being recommended by Claude Code, and presence in MCP registries was the strongest one a vendor can change; both were statistically significant. Shipping an MCP server was correlated too, though that link fell just short of statistical significance. GitHub stars were not correlated at all. We also watched the answers change. When Claude Code moved to a new model version, its number one pick changed on 50% of the emerging-category questions, against 13% of the mature ones. That points to visibility being model-versioned. A one-off audit goes stale on the next release, so Kordy measures weekly and re-runs on every model launch. [The research is written up here](https://kordy.io/blog/coding-agents-vs-chat-assistants/). None of the four tools we compare reported this surface. They track ChatGPT, Perplexity and Gemini for marketing teams, which is useful, and we [compare them honestly here](https://kordy.io/compare/). Kordy covers the coding-agent half of the funnel that those tools leave out. ## Ziv Kaspersky Founder, Kordy. USA. Ziv is an independent consultant who helps companies that sell technical products adopt coding agents and get recommended by them. He built the probe harness behind Kordy while doing that work and wrote the July 2026 study that this page draws on. Kordy is operated by Ziv Kaspersky, the same operator named in our [privacy policy](https://kordy.io/privacy-policy/) and [terms](https://kordy.io/terms-of-service/). [LinkedIn](https://www.linkedin.com/in/ziv-kaspersky/) [GitHub](https://github.com/KasperskyZiv) [hello@kordy.io](mailto:hello@kordy.io) ## How we measure Every number in a Kordy report follows the same four rules. They are what separate a measurement from a screenshot. ### Real agents, not the bare API We drive the actual Claude Code, Codex and other CLIs and capture chat sessions through the browser. The raw API strips the system prompt and the tools, so it answers differently from what your prospect sees. ### Every claim gets a source check Each session is asked which pages support each claim it made. That is how the fix list points at a real page instead of a guess. ### Per agent, per prompt, per model version Coding agents do not agree with each other: in our data the three we compared named the same top pick on 69% of questions, and each one draws on a different mix of sites. We never pool them into one "AI score", and we keep the model version on every row so a change is attributable. ### Honest limits on every report Sample sizes are printed next to every rate. Thin cells get confidence intervals. Correlations are labelled as correlations. If the answer is "your category is locked for now", the report says that. ## Facts about Kordy - **Product**Kordy, formerly Kordi. Site kordy.io, dashboard app.kordy.io. - **Founded**2026, USA, by Ziv Kaspersky. - **What it tracks**Four coding agents (Claude Code, Codex, Antigravity, Cursor; Starter and Growth pick 3), five chat models, plus npm, docs and MCP registries. - **Who it is for**Vendors of technical products and the agencies that serve them. - **Cadence**Weekly replays, re-run on every major model release. - **Plans**Starter $495 per month, Growth $995 per month, Enterprise and Agency plans. Details on the [pricing page](https://kordy.io/pricing/). - **Free start**A 60-prompt visibility report, delivered within 24 hours. [Request one](https://kordy.io/request/). - **Contact**[hello@kordy.io](mailto:hello@kordy.io) free play ## See who the agents name in your category 60 prompts across five models and four coding agents. Report in your inbox within 24 hours. [Get your visibility report](https://kordy.io/request/)