TE
科技回声
首页24小时热榜最新最佳问答展示工作
GitHubTwitter
首页

科技回声

基于 Next.js 构建的科技新闻平台,提供全球科技新闻和讨论内容。

GitHubTwitter

首页

首页最新最佳问答展示工作

资源链接

HackerNews API原版 HackerNewsNext.js

© 2025 科技回声. 版权所有。

Launch HN: CodeComplete (YC W23) – Copilot for Enterprise

138 点作者 dingliqing53大约 2 年前
Hello HN! We’re Max and Lydia, co-founders at CodeComplete AI (<a href="https:&#x2F;&#x2F;codecomplete.ai">https:&#x2F;&#x2F;codecomplete.ai</a>), an AI-powered coding assistant for enterprise companies. Many large companies can’t use products like GitHub Copilot because of the security and privacy risks, so we’re building a self-hosted version that’s fine tuned to the company’s codebase.<p>We love Copilot and believe that AI will change the way developers work. Max wanted to use Copilot when he was an ML engineer at Meta, but leadership blocked him because Copilot requires sending company code to GitHub and OpenAI. We built CodeComplete because lots of other companies are in the same boat, and we want to offer a secure way for these companies to leverage the latest AI-powered dev tools.<p>To that end, our product is really meant for large engineering teams at enterprise companies who can’t use GitHub Copilot. This generally means teams with more than 200 developers that have strict practices against sending their code or other IP externally.<p>CodeComplete offers an experience similar to Copilot; we serve AI code completions as developers type in their IDEs. However, instead of sending private code snippets to GitHub or OpenAI, we use a self-hosted LLM to serve code completions. Another advantage with self-hosting is that it’s more straightforward to securely fine-tune to the company’s codebase. Copilot suggestions aren’t always tailored to a company’s coding patterns or internal libraries, so this can help make our completions more relevant and avoid adding tech debt.<p>To serve code completions, we start with open source foundation models and augment them with additional (permissively-licensed) datasets. Our models live behind your firewall, either in your cloud or on-premises. For cloud deployments, we have terraform scripts that set up our infrastructure and pull in our containers. On-prem deployments are a bit more complicated; we work with the customer to design a custom solution. Once everything’s set up, we train on your codebase and then start serving code completions.<p>To use our product, developers simply download our extension in their IDE (VS Code currently supported, Jetbrains coming soon). After authentication, the extensions provide in-line code completion suggestions to developers as they type.<p>Since we’re a self-hosted enterprise product, we don’t have an online version you can just try out, but here are two quick demos: (1): Python completion, fine-tuned on a mock Twitter-like codebase: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;YqkqtGY4qmc" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;YqkqtGY4qmc</a>. (2) Java completion for &quot;leetcode&quot;-style problems, like converting integers to roman numerals: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;H4tGoFNC8oI" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;H4tGoFNC8oI</a>.<p>We take privacy and security seriously. By default, our deployments only send back heartbeat messages to our servers. Our product logs usage data and code snippets to the company’s own internal database so that they can evaluate our performance and improve their models over time. Companies have the option to share a subset of that data with us (e.g. completion acceptance rate, model probabilities output, latencies, etc), but we don’t require it. We never see your code or any other intellectual property.<p>We charge based on seat licenses. For enterprise companies, these contracts often demand custom scoping and requirements. In general though, our pricing will be at a premium to GitHub Copilot since there is significant technical and operational overhead with offering a self-hosted product like this.<p>Having access to these types of tools would have saved us a bunch of time in our previous jobs, so we’re really excited to show this to everyone. If you are having similar issues with security and privacy at your current company, please reach out to us at founders@codecomplete.ai! We’d love to hear your feedback.

23 条评论

phkahler大约 2 年前
Not to be confused with the software development book by the same name: <a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Code_Complete" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Code_Complete</a><p>Taking that name would not fly under trademark rules, but fortunately books are copyrighted. But then again it&#x27;s published by Microsoft Press - the publishing arm of your biggest competitor.
评论 #35179429 未加载
alsodumb大约 2 年前
GitHub and other companies like Amazon have the advantage of the scale in terms of dataset. What’s the guarantee that the pre trained model you have that you’ll fine tune on a company’s code base is as good as say Copilot? It makes it even hard to evaluate when you don’t have a demo to try - it’s not that hard to setup a pipeline to run your model in cloud and send invites to potential customers if you want to.
评论 #35153466 未加载
评论 #35153431 未加载
anxtyinmgmt大约 2 年前
So if Microsoft&#x2F;Github ever offers an on-prem version, what will be the advantage of using your product?
评论 #35153371 未加载
评论 #35153530 未加载
评论 #35154193 未加载
saurabh20n大约 2 年前
Congrats on the launch. I think you should share some technical details for a more substantial pitch. You are using the OSS BigCode effort and &quot;The Stack&quot; [1, 2] (as you say in another comment), which is great.<p>A few questions that might help an enterprise customer: How big is your base model? Where did you find more datasets (maybe just a hint would be sufficient)? Are you using SantaCoder [3]? Anything you can say about your fine-tuning that makes it special? Totally on board with you that HumanEval&#x2F;MBPP are not great benchmarks for real world, and do you have a suggested alternative to help me see the value?<p>The calculus for an enterprise customer might be: &quot;We could fine tune a 6B model on our internal code and internal benchmarks (say with a month of work, a few thousand in compute, 2 people on task), but I&#x27;d rather buy an off-the-shelf solution like codecomplete.ai. They give us XYZ benefits.&quot; Articulate the XYZ for a technical decision maker who will be your target audience.<p>* [1] <a href="https:&#x2F;&#x2F;huggingface.co&#x2F;datasets&#x2F;bigcode&#x2F;the-stack" rel="nofollow">https:&#x2F;&#x2F;huggingface.co&#x2F;datasets&#x2F;bigcode&#x2F;the-stack</a><p>* [2] <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2211.15533" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2211.15533</a><p>* [3] <a href="https:&#x2F;&#x2F;huggingface.co&#x2F;bigcode&#x2F;santacoder" rel="nofollow">https:&#x2F;&#x2F;huggingface.co&#x2F;bigcode&#x2F;santacoder</a>
评论 #35156233 未加载
kanyethegreat大约 2 年前
&gt; Permissively Licensed: Trained only on permissively-licensed repos to avoid legal risks<p>You’re fine-tuning the model. What model are you fine-tuning? I can’t imagine you trained your own LLM from scratch, so how can you possibly guarantee the core model wasn’t trained on non-permissively licensed code?
评论 #35153945 未加载
enono大约 2 年前
Always astonishes me how negative hacker news can be whenever people try to launch stuff. This is cool!
评论 #35157370 未加载
评论 #35156020 未加载
评论 #35156411 未加载
评论 #35165849 未加载
评论 #35158552 未加载
评论 #35154216 未加载
digdugdirk大约 2 年前
Any thoughts on an individual &quot;Here you go, but you&#x27;re on your own&quot; license? Something like this would be <i>massively</i> beneficial to small IT teams who have the same inability to send code to OpenAI, but could use the benefit of a smart auto-complete style system like Copilot. They wouldn&#x27;t necessarily need the custom integration - even small benefits would be seen from an initial core model. Additional integrations could be sold as piecemeal consulting engagements after the fact if need be.<p>Just a thought - there&#x27;s a vast market out there for organizations with dev teams in the 1-10 person range.
评论 #35153961 未加载
评论 #35153862 未加载
sqs大约 2 年前
Congrats on the launch. This seems very compelling. For anyone asking &quot;Why can&#x27;t GitHub just do this?&quot;, (1) never underestimate an extremely smart and motivated team, and (2) competition is critical and valuable.<p>Let&#x27;s celebrate when teams build products to fill big needs, instead of dismissing things because of a potential threat from a big company. If we dismiss new things, then we&#x27;ll just end up in a world where big companies get complacent and devs get less new stuff. (I know many GitHubbers, and they love seeing new stuff and are cheering for it because they can&#x27;t do everything.)
评论 #35167616 未加载
评论 #35153972 未加载
blintz大约 2 年前
Love the idea of running this stuff on-prem &#x2F; in house. Just not being beholden to random updates in the rules or logging policies seems like a big value add. +1 to the other commenter who mentioned they&#x27;d love to see a version for smaller teams - there might be more privacy-oriented teams out there than you&#x27;d expect. I think even a version that can run in public clouds would be meaningful.<p>Have you gotten feedback from folks using it on how it compares to Copilot in terms of usefulness? What&#x27;s the &#x27;order of magnitude&#x27; difference?
8note大约 2 年前
This seems really cool for a company that has enough surface area of software where chances are somebody has already built the thing you need and instead of building a copy yourself, you can integrate with the existing system
评论 #35160785 未加载
clbrmbr大约 2 年前
Will you train on accepted&#x2F;regected and other responses from devs rather than just the final code, so that clients lose something when moving to a similar tool which will pop up tomorrow?
评论 #35153481 未加载
DeathArrow大约 2 年前
Have you benchmarked it against Copilot?<p>Training data is only your own data, because that might not achieve a great accuracy?<p>Does it work with any programming language?
评论 #35154203 未加载
nikaspran大约 2 年前
How does this compare with <a href="https:&#x2F;&#x2F;www.tabnine.com&#x2F;enterprise" rel="nofollow">https:&#x2F;&#x2F;www.tabnine.com&#x2F;enterprise</a>, which is also self-hosted, trained on permissively licensed repositories and supports training on private repos?
s-xyz大约 2 年前
This is definitely the case in our company:<p>&quot;Many large companies can’t use products like GitHub Copilot because of the security and privacy risks, so we’re building a self-hosted version that’s fine tuned to the company’s codebase.&quot;
评论 #35167542 未加载
precompute大约 2 年前
&gt; Trained only on permissively-licensed repos to avoid legal risks<p>Nice.<p>Slightly unrelated, but are there any languages that use mostly non-permissive licenses that might have gimped your dataset for that language?
bastardoperator大约 2 年前
Actual Copilot for Enterprise:<p><a href="https:&#x2F;&#x2F;github.blog&#x2F;2023-02-14-github-copilot-for-business-is-now-available&#x2F;" rel="nofollow">https:&#x2F;&#x2F;github.blog&#x2F;2023-02-14-github-copilot-for-business-i...</a>
评论 #35154619 未加载
codemakerai大约 2 年前
I think this a problem that is worth solving as not only the biggest companies are concerned with security, many SaaS and tech companies are concerned about source code of product become compromised.
apetuskey大约 2 年前
Excited to try this looks really good! Been looking for something like this for our Pynecone code base!
评论 #35160828 未加载
Double_a_92大约 2 年前
Does the &quot;fine-tuning&quot; also happen on-premise or do you need to access the Code?
doctoboggan大约 2 年前
Can you let us know which &quot;open source foundation model&quot; you use?
ninjaa大约 2 年前
Congrats Lydia &amp; Max! Great demo videos
评论 #35154282 未加载
teddyh大约 2 年前
&gt; <i>Trained only on permissively-licensed repos to avoid legal risks</i><p>Do any of those “permissive” licences require attribution? Do they all grant a patent license?
aunch大约 2 年前
Codeium already has this enterprise option, with self-hosting, fine-tuning, and even things like search on top of autocomplete and way more IDEs: <a href="https:&#x2F;&#x2F;codeium.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;codeium.com&#x2F;</a><p>How are you different?
评论 #35156188 未加载