Reducto Raises $24.5M Series A Round to Help Enterprises Unlock Unstructured Data

Reducto 获得 2450 万美元 A 轮融资，助力企业解锁非结构化数据

SAN FRANCISCO, April 25, 2025-- Reducto, the most accurate ingestion platform for unlocking unstructured data for AI pipelines, announced today that it has raised a $24.5M series A round of funding led by Benchmark, alongside existing investors First Round Capital, BoxGroup and Y Combinator. This follows the company's October 2024 seed round of $8.4M and brings its total funding to date to $32.9M..

旧金山，2025年4月25日——Reducto，作为最精准的面向AI管道解锁非结构化数据的摄入平台，今日宣布已完成由Benchmark领投的2450万美元A轮融资，现有投资者First Round Capital、BoxGroup和Y Combinator也参与其中。这轮投资紧随公司在2024年10月完成的840万美元种子轮融资，截至目前，其总融资额已达到3290万美元。

“Reducto’s unique technology enables companies of all sizes to leverage LLMs across a variety of unstructured data, regardless of scale or complexity,” said Chetan Puttagunta, General Partner at Benchmark. “The team's incredibly fast execution on product development further underscores their commitment to delivering state-of-the-art software to customers.”.

“Reducto 的独特技术使各种规模的公司都能够利用大型语言模型处理各种非结构化数据，无论其规模或复杂性如何，”Benchmark 的普通合伙人 Chetan Puttagunta 表示。“团队在产品开发上的极快速执行进一步证明了他们为客户提供最先进的软件的决心。”

Reducto turns complex documents into accurate LLM-ready inputs, allowing AI teams to reliably use the vast data that’s locked in PDFs and spreadsheets. Ingestion is a core bottleneck for AI teams today because traditional approaches fail to extract and chunk unstructured data accurately. These input errors lead to inaccurate and hallucinated outputs, making LLM applications unreliable for many real-world use cases such as processing medical records and financial statements..

Reducto 将复杂文档转化为准确的、可供大型语言模型（LLM）使用的输入，使AI团队能够可靠地利用锁定在PDF和电子表格中的海量数据。数据摄入是当今AI团队的核心瓶颈，因为传统方法无法准确提取和分块非结构化数据。这些输入错误会导致输出不准确甚至虚构内容，使得LLM应用程序在处理医疗记录、财务报表等许多实际应用场景中变得不可靠。

In benchmark studies, Reducto has been proven to be significantly more accurate than legacy providers like AWS, Google and Microsoft - in some cases by a margin of 20+ percent, alongside significant processing speed improvements. This is critical for high-stakes, production AI use cases.

在基准研究中，Reducto 已被证明比 AWS、Google 和 Microsoft 等传统供应商的准确度显著更高——在某些情况下超出 20% 以上，同时处理速度也有显著提升。这对于高风险、生产级人工智能应用场景至关重要。

Over the past year, Reducto has processed hundreds of millions of pages of unstructured data for companies like Airtable, Scale, and a Fortune 10 enterprise. Customer Legora reports that with Reducto, its team tripled processing speed and built a pipeline that processes millions of documents per month, all while reducing engineering time spent on chunking by 90%..

在过去的一年中，Reducto为Airtable、Scale以及一家《财富》10强企业等公司处理了数亿页的非结构化数据。客户Legora报告称，通过使用Reducto，其团队的处理速度提高了三倍，并建立了一个每月处理数百万份文档的流水线，同时将工程师用于分块的时间减少了90%。

Reducto's founders Adit Abraham and Raunak Chowdhuri met while at MIT and spent several years building machine learning products at companies like Google and Nvidia before striking out on their own. 'We worked as ML engineers, and learned early on that often, inaccurate output and hallucinations are not necessarily model problems, but ingestion problems - bad inputs lead to bad outputs,' said Abraham, co-founder and CEO of Reducto.

Reducto 的创始人阿迪特·亚伯拉罕 (Adit Abraham) 和劳纳克·乔杜里 (Raunak Chowdhuri) 在麻省理工学院相识，之后在谷歌和英伟达等公司花了数年时间开发机器学习产品，随后才开始自主创业。 “我们曾担任机器学习工程师，早期就认识到，不准确的输出和幻觉问题并不一定是模型问题，而是数据摄取问题——错误的输入导致错误的输出，” Reducto 联合创始人兼首席执行官亚伯拉罕表示。

'Nearly 80% of enterprise data is in unstructured formats like PDFs, making it hard to access and analyze. To overcome this, we developed vision models that read documents the way humans do — breaking down complex layouts visually and contextually parsing each region. When customers see Reducto for the first time, they immediately get the significance.

“近80%的企业数据是以PDF等非结构化格式存在的，这使得访问和分析变得困难。为了克服这一问题，我们开发了能够像人类一样读取文档的视觉模型——通过视觉和上下文方式分解复杂布局并解析每个区域。当客户第一次看到Reducto时，他们立刻意识到了它的重要性。

We're grateful to Benchmark and all our investors for sharing our excitement over this breakthrough.'.

我们感谢Benchmark和所有投资者对我们取得这一突破感到兴奋。

'Having invested in Reducto from day one, I immediately recognized Adit and Raunak's technical brilliance and unique approach to solving the ingestion problem,” said angel investor Kulveer Taggar, who participated in Reducto's seed round. “The fact that leading AI teams are overwhelmingly choosing Reducto over incumbents validates their approach - when your AI's accuracy depends on perfect inputs, there's no room for compromise.'.

“从第一天投资Reducto开始，我就立刻意识到了Adit和Raunak在技术上的卓越才华以及他们解决数据摄取问题的独特方法，”参与了Reducto种子轮融资的天使投资人Kulveer Taggar表示，“领先的AI团队绝大多数选择Reducto而非现有企业，这一事实证明了他们的方法是正确的——当你的AI准确性依赖于完美的输入时，没有任何妥协的余地。”

To learn more about Reducto, visit https://reducto.ai/.

要了解更多关于 Reducto 的信息，请访问 https://reducto.ai/。

About Reducto

关于Reducto

Reducto is the most accurate solution for turning complex documents into AI-ready inputs. The team from MIT built state of the art vision models that read documents like humans do, solving a critical bottleneck for AI teams working with unstructured data. Reducto enables reliable AI processing of sensitive documents like medical records and financial statements with the accuracy and reliability necessary in production environments..

Reducto 是将复杂文档转化为人工智能可用输入的最精确解决方案。这支来自麻省理工学院的团队构建了最先进的视觉模型，能够像人类一样阅读文档，解决了人工智能团队处理非结构化数据时的关键瓶颈。Reducto 能够以生产环境中所需的准确性和可靠性，对医疗记录和财务报表等敏感文档进行可靠的人工智能处理。

Having processed hundreds of millions of pages for clients like Airtable and Scale, and backed by $32.9M in funding, Reducto has quickly become a leading provider of today’s LLM ingestion.

在为像Airtable和Scale这样的客户处理了数亿页的内容，并获得3290万美元的融资支持后，Reducto迅速成为了当今LLM数据摄取领域的领先提供商。

Contact:

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Media contact:

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Michelle Faulkner

米歇尔·福克纳

Big Swing

大挥杆

617-510-6998

617-510-6998

michelle@big-swing.com

米歇尔@大摇摆.com