Coryant: Coordinated research agents. Running on your Claude.

Coryant is a set of Claude agents packs for people who don't touch a terminal. Ask a question and 10 coordinated research agents pull market, competitor, pricing, and signal data then hand you one sourced verdict instead of ten browser tabs. GTM, product, career, CA and pack for non technical AI users, built entirely for Claude code and chat interface. No CLI, no GitHub, no setup. Just describe what you need to know.

Hey Product Hunt 👋 I'm Saurabh, solo builder of Coryant. Here's the problem I kept running into: Claude Code has an incredible ecosystem of skill packs marketing research, job search automation, product management workflows but almost all of them assume you're comfortable in a terminal, editing YAML, or forking a GitHub repo. If you're a founder doing your own growth research, a job seeker, or a CA who just wants a client-ready answer, that's a wall before you even get to the value. So I built Coryant: the same idea coordinated multi-agent research pipelines but running entirely inside the Claude chat interface you already use. No CLI, no setup, no GitHub account. You ask a question, 10 specialized agents research it in parallel (market, competitor, pricing, signals, and more), and you get one sourced, evidence-graded answer instead of a dozen browser tabs that don't agree with each other. Right now there are four packs GTM, Product, Career, CA, Real estate, Content, Founder's associate, Sales, Supply Chain and Tutor each ₹1,999 one time, no subscription. I built this solo, and I'd genuinely love your feedback: What would make this more useful for you? What's missing? Happy to answer anything in the comments today. Thanks for taking a look 🙏

how do the 10 agents decide when to dig deeper versus just returning the first solid source they find

How does it actually pull the signal data behind the verdict, like is it scraping live sources or pulling from a fixed knowledge base that you update on your end?

Tried the GTM pack on a small launch and the sourced verdict actually saved me a couple hours of tab juggling, which I did not expect. Clean answer, no setup, felt like having a junior analyst on call.

how do the 10 agents decide when to dig deeper versus just returning the first solid source they find

How does it actually pull the signal data behind the verdict, like is it scraping live sources or pulling from a fixed knowledge base that you update on your end?