Search engine to find code & code context across all your repositories quickly. Search using keywords, exact code & more.
The extensive search engine capabilities of QuodAI speeds up the resolution of Bugs, the understanding we have of our own codebase, and the onboarding of new employees. We implemented the product on all the microservices our development team maintains. It also helps the different FrontEnd-BackEnd-Data-Consultants teams to explore easily and get a quick overview of other teams' codebase, even if they don't know the stack language! Roles and permissions are seamlessly integrated to give tailored access to resources to different stakeholders.
Eventually, I made it all the way from a beta user to a customer & big fan. Our team loves the product and enjoy the magic to search a codebase independently of the code syntax! Good job QuodAI! We use it in our daily operations.
Based on our record, bloop should be more popular than Quod AI. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you want to give it a try, go to http://quod.ai/, the extension is free to install. Source: about 3 years ago
In this blog post, I’ll be comparing 3 distinct AI-first code search tools I recently came across: Cody (developed by late-stage startup, Sourcegraph), SeaGOAT (an open-source project that was trending on HN last week), and Bloop (an early-stage YC startup). I’ll be evaluating them along the dimensions of user-friendliness as well as their accuracy. - Source: dev.to / 7 months ago
If you're confused about any of the code snippets above, you can check out bloop.ai and phind.com (along with its VSCode extension) to answer any of your questions about the repository, noting that both have free plans. - Source: dev.to / 7 months ago
Bro let me turn your life inside out: https://bloop.ai. Source: 10 months ago
GPT4: Ok, here you go - https://bloop.ai/. Source: about 1 year ago
We've invested a lot into helping LLMs reason and explain large codebases. We use a hybrid approach of local models for semantic search and a mix of OpenAI and Anthropic's models for language output and summarisation. We're two years in but everything still feels super early given how quickly the fundamentals are improving. Would love your feedback - https://bloop.ai. - Source: Hacker News / about 1 year ago
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