Hi everyone! 👋
We're the Developer Relations team at Querit, where we're building a Web Search API for AI agents and LLM-powered applications.
Over the past few months, we've talked with developers building AI agents, RAG applications, research assistants, monitoring tools, and browser automation workflows. One thing quickly became clear:
Building the API isn't the hardest part. Collecting meaningful developer feedback is.
We've launched a Discord-based onboarding and testing program for developers building AI applications that rely on fresh web information.
All developers are welcome to join and help us improve the product.
Getting started
If you want to poke at it, here is the simple work flow: Verified developers get access to:
What We're Actually Looking For
We're not simply looking for people to tell us whether the API is "good" or "bad."
We're interested in understanding how developers evaluate search quality in real AI applications.
For each testing round, we encourage contributors to share: Sometimes a "failed" search teaches us far more than a successful one.
That's exactly the kind of feedback we're hoping to collect.
Developers who consistently contribute useful reports can receive additional API credits, and improvements inspired by community feedback may be acknowledged in future product updates.
We'd love your input
This program is still evolving, and we're learning as we go.
If you've built AI agents or applications that rely on web search, we'd love to hear your thoughts: Useful reports can earn additional API request credits. Findings that lead to an actual product fix may also receive credit in the Querit Changelog.
If you'd like to participate, you can join our Discord community here:
[https://discord.gg/sYQaFSHxyU](https://discord.gg/sYQaFSHxyU)
We're looking forward to building this program together with the developer community—and we'd love to hear how you'd improve it