Bloop is an AI-based platform that offers natural language search, regex matching, and precise code navigation for private codebases. It was founded by Igor Susmelj and Leif Walsh and is designed to help developers understand code more efficiently.
Bloop's natural language search feature uses Semantic Code Search and Large Language Models like GPT-4 to support natural language searches. It allows users to ask conversational questions, making it ideal for exploring and locating unfamiliar codebases. Bloop's easy-to-use interface encourages users to refine their search queries with little to no hassle, and they can refine their initial search by adding filters to help narrow down search requests.
The platform is integrated with various software like GitHub, Git, Atlassian, and OpenAI, improving the overall productivity of development teams and streamlining their workflow.
TLDR
Bloop is an AI-based platform designed to help developers understand code more efficiently. It offers natural language search, regex matching, and precise code navigation for private codebases. Users can refine their search queries with little to no hassle and can add filters to help narrow down search requests.
The platform is integrated with various software, improving the overall productivity of development teams and streamlining their workflow.
Company Overview
Bloop is a platform that offers natural language search, regex matching, and precise code navigation for private codebases. It is the only tool that provides these features, along with the ability to answer in over 20+ languages. Bloop's natural language search can surface internal libraries and existing patterns, allowing developers to understand codebases more efficiently.
It helps prevent stale code, dependency bloat, and frees up time to work on unsolved problems.
The platform was founded by Igor Susmelj and Leif Walsh. Igor Susmelj is an entrepreneur with experience in machine learning and blockchain technology. Leif Walsh is a software engineer who has previously worked at GitHub and Dropbox.
Together, they created Bloop to help developers understand code more easily.
Bloop's natural language search returns accurate results in less time, making it a powerful alternative to slow keyword searches and asking colleagues for help. The platform understands complex concepts and summarises code intentions when responding to natural language search queries. This summarisation helps close the development loop by speeding up code review, planning, and other tasks.
Bloop offers precise code navigation for private codebases. It allows developers to follow up a natural language search with a codebase change that is ideal for small changes and can be initiated by anyone on the team, regardless of coding ability.
Built in Rust, Bloop is the fastest way to find code, identifiers, paths, and repos with regex. Its semantic code search and natural language search make it easier to discover internal APIs, improve adoption, and reduce duplication.
The co-founder of Bloop, Hamel Husain, was the former GitHub Code Search Lead. His experience contributed significantly to the development of the platform. Bloop offers a complete solution for developers who are looking for an efficient way to manage their codebase.
It is a powerful tool that enhances the code management process, saves time, and improves the overall productivity of development teams.
Features
Natural Language Search
Advanced Codebase Exploration
Docsbloop's Natural Language Search feature is developed from the ground up to support natural language searches. With Semantic Code Search and Large Language Models like GPT-4, Bloop allows users to ask conversational questions, making it ideal for exploring and locating unfamiliar codebases. This feature is designed to assist developers in summarizing, explaining, reasoning, and even suggesting improvements to complex coding structure easily.
Dropdown Menu Selection
Bloop has intuitively created a dropdown menu selection feature to initiate natural language searches. Users can start by selecting the search type from the dropdown menu to the left of the search bar in the header, enabling the natural language search option. It allows users to navigate to this feature faster and reduces the time spent searching for the right tab or button.
Conversational Dialogue Sidebar
As the semantic code search results load, a conversational dialogue sidebar pops out on the right-hand side of the screen to provide real-time responses to the user's search. The natural language response to the search query will start streaming shortly after. Users can refine their query or make a related search by entering their response in the textbox within the conversational dialogue, helping refine their search even more.
Refine Search
Multiple Search Methods
Docsbloop's powerful search algorithm allows users to refine their search in multiple ways. Users can use natural language queries to ask conversational questions, and the search algorithm will return results based on keyword relevance. Users can also make use of the lang and repo filters to refine their search further.
For example, adding lang:ts or repo:bloop to the end of the search query can filter search requests by language or code repository.
Easy-to-Use Interface
Bloop's easy-to-use interface encourages users to refine their search queries with little to no hassle. Users can easily refine their initial search by adding these filters to help narrow down search requests, reducing search time and yielding results faster than other AI-powered search tools.
Frame Questions Like You Would With Colleagues
Docsbloop encourages users to frame their questions as if they were speaking to colleagues, rather than simply entering keywords. This is to ensure that the results returned by the search algorithm fit the user's needs and are truly relevant to the query. If users do not get a great result from their initial search, they can try asking the question in a different way using conversational language, which helps refine the search query.
Cautious but Accurate Search Results
LLM-Powered Experience
As with most LLM-powered experiences, there is a possibility of encountering incorrect information or harmful content. However, Docsbloop's search algorithm has been fine-tuned to minimize these errors and display accurate results. It is a cautious but effective system, providing users with accurate and relevant results to their search queries.
Safe Searching
Bloop recognizes the need for safety in searches, especially when searching for new information about complex codebases. As a result, this feature is designed to deliver cautious results that prevent users from encountering harmful content as the search results load. The safety of users is a priority, and Docsbloop's cautious but accurate search results are provided with that priority in mind.
Effective Research
This feature is designed to provide users with meaningful and relevant search results. It is effective research tool that helps users navigate unfamiliar code bases while providing them with in-depth explanations, suggestions for improvements, and a better understanding of the codebase. The results returned are reliable, providing developers with accurate and dependable resources for the codebase being searched.
Integrations
Bloop is a powerful AI tool that can integrate with a variety of software to streamline your workflow and improve your productivity. Here are the current Bloop integrations:
GitHub
Bloop has integrated seamlessly with GitHub, allowing users to access their repositories and data from a single platform. With this integration, users can easily manage their code repositories and track changes using Bloop's advanced AI tools. Whether you’re working on a personal project or collaborating with a team, integrating GitHub with Bloop can help you stay organized and productive.
Git
Another integration that Bloop offers is Git, a powerful version control system for software development. By integrating Git with Bloop, users can take advantage of advanced AI tools and streamline their workflows, making it easier to track changes, collaborate with team members, and manage complex projects.
Atlassian
For teams that rely on Atlassian products like Jira, Confluence, and Bitbucket, Bloop offers a powerful integration that can help you stay on top of your projects and increase your productivity. With this integration, users can easily access information about their projects, track changes, and collaborate with team members, all from a single platform.
OpenAI
Bloop offers an integration with OpenAI, one of the most powerful artificial intelligence platforms available today. With this integration, users can take advantage of OpenAI's advanced machine learning tools, including natural language processing and computer vision, to build more powerful, effective AI models.
OpenAI
Bloop offers an additional integration with OpenAI that provides access to powerful APIs for natural language processing, text generation, and more. With this integration, users can easily build AI models that can analyze and interpret large amounts of unstructured data, improving their ability to make data-driven decisions and generate meaningful insights.
FAQ
What is Bloop?
Bloop is a platform that offers natural language search, regex matching, and precise code navigation for private codebases. It is designed to help developers understand code more efficiently. The platform offers features like natural language search, precise code navigation, and regex matching, making it a powerful tool that enhances the code management process, saves time, and improves the overall productivity of development teams.
Who are the co-founders of Bloop?
Bloop was founded by Igor Susmelj and Leif Walsh. Igor Susmelj is an entrepreneur with experience in machine learning and blockchain technology, while Leif Walsh is a software engineer who has previously worked at GitHub and Dropbox. Together, they created Bloop to help developers understand code more easily.
What sets Bloop apart from similar tools?
Bloop is the only tool that provides natural language search, regex matching, and precise code navigation for private codebases. It is the fastest way to find code, identifiers, paths, and repos with regex. Bloop's natural language search can surface internal libraries and existing patterns, allowing developers to understand codebases more easily.
It helps prevent stale code, dependency bloat, and frees up time to work on unsolved problems.
What is natural language search, and how does it work?
Natural language search is a feature that allows users to search a codebase using plain language instead of complex queries or keywords. Bloop's natural language search returns accurate results in less time than slow keyword searches and asking colleagues for help. It understands complex concepts and summarises code intentions when responding to natural language search queries.
This summarisation helps close the development loop by speeding up code review, planning, and other tasks.
What is regex matching, and how does it work?
Bloop offers precise code navigation with regex matching. Regular expressions, or regex, are a powerful tool that allows users to find and manipulate text using patterns. Bloop's regex matching feature allows developers to follow up a natural language search with a codebase change that is ideal for small changes and can be initiated by anyone on the team, regardless of coding ability.
Built in Rust, Bloop is the fastest way to find code, identifiers, paths, and repos with regex.
Alternatives
If you're looking for an alternative to Bloop, here are a few other AI-powered code search tools to consider:
Kite
Kite is a robust code search tool that uses machine learning to provide real-time code completions, documentation, and error-checking right in your favorite IDE. The AI model behind Kite learns from the millions of code examples available on the web and can provide intelligent suggestions based on context. It supports multiple languages and platforms, including Python, Java, C++, and JavaScript, and offers intelligent refactoring tools to make your code more readable and efficient.
TabNine
TabNine is an AI-powered code editor plugin that uses deep learning to generate intelligent code completions, snippets, and documentation. It works with most popular IDEs and editors, including Visual Studio Code, Atom, and Sublime Text, and supports over 30 programming languages. TabNine is known for its robust and reliable code analysis, making it a popular choice among developers looking for an AI-powered code helper.
Sourcegraph
Sourcegraph is a code search and browsing platform that uses intelligent search and indexing tools to help developers quickly find and understand code across their entire organization. It offers a wide array of language support, including Go, Python, Java, and JavaScript, and can integrate with popular code hosting platforms like GitHub, GitLab, and Bitbucket. In addition to code search, Sourcegraph also provides code reviews, code intelligence, and other development tools to help teams work more efficiently.
