启动 HN:Inconvo(YC S23)——面向客户的分析 AI 代理

1作者: ogham18 天前原帖
嗨,HN,我们是Inconvo的Liam和Eoghan(<a href="https://inconvo.com">https://inconvo.com</a>),我们的平台使得在您的SaaS产品中构建和部署AI分析代理变得简单,从而让您的客户能够快速与他们的数据进行互动。 您可以在<a href="https://www.youtube.com/watch?v=4wlZL3XGWTQ" rel="nofollow">https://www.youtube.com/watch?v=4wlZL3XGWTQ</a>观看演示视频,并在<a href="https://demo.inconvo.ai/" rel="nofollow">https://demo.inconvo.ai/</a>进行实时演示(无需注册)。文档可以在<a href="https://inconvo.com/docs">https://inconvo.com/docs</a>找到。 SaaS产品通常提供仪表板和报告,这些工具适合高层次的指标,但在深入分析和处理临时问题时显得笨重且反应缓慢。现代用户受到像ChatGPT这样的工具的影响,现在期望在获取数据洞察时能够享有类似的速度和灵活性。为了满足这些期望,您需要一个AI分析代理,但开发和管理这些代理是一个痛苦的过程。 Inconvo是一个从零开始为开发者构建客户面向分析的AI代理的平台。我们通过连接SQL数据库,使得将数据暴露给Inconvo变得简单。我们提供一个语义模型,创建一个管理数据访问和定义业务逻辑的层,提供会话日志以跟踪用户交互,并提供一个开发者友好的API以便于集成。为了可观察性,我们为每个代理响应展示跟踪信息,使得代理行为易于调试。 我们最初并不是为了构建Inconvo而开始的,最初我们开发了一个开发者生产力SaaS,后来进行了转型。我们那个产品中最喜欢的功能是其分析代理,我们知道构建一个这样的代理是一个足够大的问题,因此决定开发一个工具来实现这一目标。 我们的API设计用于多租户数据库,允许您将会话信息作为上下文传递。这指示代理仅分析与特定请求租户相关的数据。 我们大多数竞争对手是主要为内部分析设计的BI工具,嵌入选项有限,通常通过iFrame或不直观的API实现。 如果您对AI SQL生成感到担忧,我们也是。我们认为,面向客户的分析的AI代理不应该生成和运行未经验证的原始SQL。相反,我们的代理生成结构化查询对象,这些对象经过程序验证,以确保它们仅请求在请求上下文中允许的数据。然后,我们将经过验证的对象发送到我们的QueryEngine,它将对象转换为SQL。通过这种方法,我们确保生成的SQL集合是有限的,从而防止代理产生幻觉并运行不当查询。 我们的定价是透明的,并在我们的网站上提供。您可以在没有信用卡的情况下免费试用该平台。 如果您想尝试完整的产品,可以在<a href="https://auth.inconvo.ai/en/signup" rel="nofollow">https://auth.inconvo.ai/en/signup</a>免费注册。如前所述,我们的沙盒演示在<a href="https://demo.inconvo.ai/" rel="nofollow">https://demo.inconvo.ai/</a>,还有一个视频在<a href="https://youtu.be/4wlZL3XGWTQ" rel="nofollow">https://youtu.be/4wlZL3XGWTQ</a>。 我们非常希望听到您对我们的反馈,因此请在评论中分享您的想法和建议,我们的目标是使这个工具尽可能友好地服务于开发者。谢谢!
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Hi HN, we are Liam and Eoghan of Inconvo (<a href="https:&#x2F;&#x2F;inconvo.com">https:&#x2F;&#x2F;inconvo.com</a>), a platform that makes it easy to build and deploy AI analytics agents into your SaaS products, so your customers can quickly interact with their data.<p>There’s a demo video at <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=4wlZL3XGWTQ" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=4wlZL3XGWTQ</a> and a live demo at <a href="https:&#x2F;&#x2F;demo.inconvo.ai&#x2F;" rel="nofollow">https:&#x2F;&#x2F;demo.inconvo.ai&#x2F;</a> (no signup required). Docs are at <a href="https:&#x2F;&#x2F;inconvo.com&#x2F;docs">https:&#x2F;&#x2F;inconvo.com&#x2F;docs</a>.<p>SaaS products typically offer dashboards and reports, which work for high-level metrics but are clunky for drill-downs and slow for ad-hoc questions. Modern users, shaped by tools like ChatGPT, now expect a similar degree of speed and flexibility when getting insights from their data. To meet these expectations, you need an AI analytics agent, but these are painful to develop and manage.<p>Inconvo is a platform built from the ground up for developers building AI agents for customer-facing analytics. We make it simple to expose data to Inconvo by connecting to SQL databases. We offer a semantic model to create a layer that governs data access and defines business logic, conversation logs to track user interactions, and a developer-friendly API for easy integration. For observability we show a trace for each agent response to make agent behaviour easily debuggable.<p>We didn’t start out building Inconvo, initially we built a developer productivity SaaS from which we pivoted. Our favourite feature of that product was its analytics agent, and we knew that building one was a big enough problem to solve on its own so we decided to build a developer tool to do so.<p>Our API is designed for multi-tenant databases, allowing you to pass session information as context. This instructs the agent to only analyse data relevant to the specific tenant making the request.<p>Most of our competitors are BI tools primarily designed for internal analytics with limited embedding options through iFrame or unintuitive APIs.<p>If you’re concerned about AI SQL generation, we are too. In our opinion, AI agents for customer-facing analytics shouldn’t generate and run raw SQL without validation. Instead, our agents generate structured query objects that are programmatically validated to guarantee they request only the data allowed within the context of the request. Then we send validated objects to our QueryEngine which converts the object to SQL. With this approach we ensure a bounded set of possible SQL that can be generated, which stops the agent from hallucinating and running rouge queries.<p>Our pricing is upfront and available on our website. You can try the platform for free without a credit card.<p>If you want to try out the full product, you can sign up for free at <a href="https:&#x2F;&#x2F;auth.inconvo.ai&#x2F;en&#x2F;signup" rel="nofollow">https:&#x2F;&#x2F;auth.inconvo.ai&#x2F;en&#x2F;signup</a>. As mentioned, our sandbox demo is at <a href="https:&#x2F;&#x2F;demo.inconvo.ai&#x2F;" rel="nofollow">https:&#x2F;&#x2F;demo.inconvo.ai&#x2F;</a>, and there’s a video at <a href="https:&#x2F;&#x2F;youtu.be&#x2F;4wlZL3XGWTQ" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;4wlZL3XGWTQ</a>.<p>We&#x27;re really interested in any feedback you have so please share your thoughts and ideas in the comments, as we aim to make this tool as developer-friendly as possible. Thanks!