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The Birth of AskTable

Hello, We Are AskTable.​

As a startup team in the technology sector, we have been pondering: Why can't we search our structured data like Excel and databases as simply and quickly as searching web pages?

Data Challenges Across Industries​

In our interactions with numerous enterprises and institutions, we have deeply understood their struggles when handling structured data:

  • A human resources service company in Hunan (with daily active users in the millions): They receive over a thousand Excel files with inconsistent formats every day, such as mismatched headers and merged cells. Currently, all processing is done manually, and they urgently need automation.
  • A leading accounting firm in Beijing: They obtain large amounts of structured data from clients' financial systems and ERP systems, stored in Excel. They hope to quickly query numbers to improve efficiency.
  • A high school in Tianjin: Student information and teacher schedules are scattered across numerous Excel files. Manually processing these data is cumbersome and inefficient. For example, when compiling data for the entire school, they need to manually consolidate Excel files submitted by each grade.
  • A new energy listed company in Jiangsu: They provide integrated software and hardware solutions and plan to integrate AI queries into their self-developed SaaS platform to reduce repetitive code writing and save manpower.
  • A global Fortune 500 company in Shandong: Business managers frequently query data, although there is a data center and dashboard, only a few people have the capability to use them because it requires writing complex SQL and understanding data warehouse fields. Creating a dashboard usually takes several days, significantly affecting decision-making efficiency, especially when secondary queries are needed. This group plans to solve this problem using AI over the next three years.
  • A financial services company in Beijing: They offer advance funding services to merchants, with some operational data stored in Alibaba Cloud RDS database. They expect to directly retrieve data through AI to support business decisions and customer inquiries.

Searching and utilizing structured data has become an unavoidable "must-take path" for accelerating operational efficiency across industries.

Where Is the Solution?​

Facing such challenges, we believe that AI is the key we are seeking. However, common AI knowledge bases or AI searches primarily target natural language text, excelling at processing natural language documents like Word, PDFs, web pages, and emails, such as legal documents and product manuals. But when it comes to structured data like Excel or databases, they often fall short.

Users' expectations are straightforward: whether it's a Word document or an Excel file, they want it to be equally user-friendly. And this gap between ideal and reality is exactly what we aim to bridge.

We firmly believe that enabling AI to understand structured data is the critical turning point from "interesting" to "useful."

The Birth of AskTable​

To fill this gap, I and my team founded AskTable.

  • "Ask" represents the iconic interaction method in the new AI era—asking questions.
  • "Table" stands for structured data, such as Feishu Sheets, Excel, MySQL, ClickHouse data warehouses, etc.

Our mission is: to make it easy for everyone to search and utilize their structured data just like using Baidu or Google.

Our Positioning​

Through the latest AI search technology, AskTable can understand natural language queries from users, automatically generate data query commands, and directly provide results. This not only lowers the usage threshold but also significantly boosts work efficiency. AskTable extends the boundaries of search from web pages, documents, images, videos to Excel and databases, which are strongly structured data.

For example, based on AskTable, we are designing an AI archive for Excel users—0Excel.com, which, with AskTable's technology, can find the required data from thousands of Excel files in just 10 seconds.

In our development process, we consistently adhere to the principle of "focusing on core capabilities without reinventing the wheel":

  • We do not provide AI models but will integrate or fine-tune suitable large models to provide the best experience for users.
  • We do not build AI agent platforms but can embed our database access capabilities within partner platforms.
  • We do not provide general-purpose bots, but we can make partners' bots smarter, recognize user identities, and provide personalized responses.
  • We do not provide databases but empower users and developers with the ability to access and utilize their own data.
  • We do not provide BI suites, but we can embed our AI conversation capabilities within partner data platforms.

Outlook​

As enterprises delve deeper into AI applications, they must face a vast amount of structured data. There is a huge market demand for convenient and efficient structured data search. We believe that the future of work will be transformed by AskTable. Making it easy and equitable for everyone to access the data and insights they need is always our goal.

Welcome to Join Us​

  • ALL in LLM: We are devout believers in LLMs, avoiding complex system designs and maximizing the potential of LLMs.
  • Business First: We focus on the implementation of LLMs in specific business scenarios, concentrating on the deployment of upper-layer applications.
  • Security: We trust the capabilities of open-source models and seek the best local deployment solutions.

We sincerely invite you, who are passionate and creative in the AI field, to contact us for mutual exchange or to join us in shaping the future of artificial intelligence!

You can reach us by submitting your information on our website (AskTable.com).