ZhenFund angel project "Teable" announces completion of several-million-dollar angel round, launches world's first multidimensional spreadsheet agent | Z News

Teable, a new entrant in the AI Agent space, recently announced the completion of a multi-million-dollar angel round led by ZhenFund, Baidu Ventures (BV), and Vertex Ventures China.

On September 16, North American time, Teable unveiled the world's first multidimensional-database agent — AI Database Agent (Teable 2.0) — on social media platform X, integrating "conversational database building, app generation, workflow automation, data analysis, and batch content creation" into a unified capability that lets users complete complex data tasks through natural language, drawing significant industry attention.

Founder Jiabei Chen was a founding member of Lark's multidimensional-table product and co-founder & CTO of Vika. The new funding will accelerate global expansion and continued investment in the underlying engine and product R&D.

Yuan Liu, partner at ZhenFund, commented: "Jiabei Chen and his team have spent nearly their entire careers as innovation leaders in the multidimensional-table space. In building the early Lark multidimensional-table product and pioneering Vika's data products, they developed a keen understanding of real enterprise needs and the engineering capability to deeply integrate AI with databases. Bootstrapping without prior funding, they built an outstanding open-source product that attracted users from over 100 countries — proving tremendous entrepreneurial spirit and international product competitiveness. We look forward to Teable further leveraging its reliable engineering capabilities and innovative spirit to drive deeper enterprise adoption and become another world-class product from a Chinese startup."

Over the past two years, AI progress has been exhilarating, yet for many frontline teams, implementation still feels like hitting an invisible wall: tools that need piecing together, fragmented data, and scarce development resources.

Teable's approach is to make AI a native database capability from the ground up, so non-technical team members can "just talk and get to work." Starting from a plain description of business goals, the system automatically generates the required table structures and relationships. You can then converse directly with your data tables, one-click generate production-ready business applications or landing pages, all sitting on the same technical foundation with unified permissions, audit trails, and automation. Invoices, contracts, resumes — documents can be conversationally extracted into structured data and written back to the database. For analysis, no SQL needed: ask a question and get metrics and visualizations. In short: make everything around data radically simple, with data flowing straight to results — no more hand-crafting spreadsheets or juggling multiple tools.

In China, multidimensional tables have proven to be the most accessible business vehicle inside enterprises. Riding this trend, Teable's newly launched "multidimensional-table agent" aims, as founder Jiabei Chen puts it, to let ordinary people easily access "industrial-grade" AI capabilities.

Non-technical users can rapidly build runnable business scenarios through natural language — actionable, immediately problem-solving, making real productivity gains visible, usable, and reusable in daily work.

In overseas markets, Airtable is regarded as the most creative database/spreadsheet tool beyond Excel, yet the handoff between AI and business workflows remains less than seamless. Teable's answer is "AI-native, generate-to-produce." Unlike the typical vibe-coding path of "generate frontend first, then patch in database and permissions," Teable grows applications directly from the database: read/write, permissions, audit, and automation all wired through a single foundation — generate and you're connected, generate and you're live, avoiding the "can generate but can't operate"二次搬运 problem.

The most vivid example: one-sentence generation of a CRM consultation landing page — describe your intent in natural language within the data table, and the system immediately produces a deployable page; visitor submissions flow into the database in real-time with automatic lead tagging and reply suggestions, triggering sales follow-up. This closed loop significantly reduces integration and trial-and-error costs for go-to-market teams on advertising and conversion.

One of Teable 2.0's six core features: conversational app-building from data tables

Against entrenched competitors and massive ecosystems (industry estimates put Airtable's 2024 revenue above $400 million), Teable is betting on engineering strength and community validation to deliver on "world-class": trending on Hacker News during launch, hitting #1 on GitHub Trending daily, accumulating 20k Stars and 500k+ precompiled downloads, and making Runa Capital's "Global OSS Top 20 Growth." This sustained endorsement from global developers means Teable's "AI-native database agent" isn't merely "first to do it," but approaches industry benchmarks on usability, manageability, and scalability.

Teable open-source edition: 20,000 GitHub stars in under a year

Few would rebuild something from scratch three times. Teable not only did — it broke through category-wide technical barriers.

In China, multidimensional tables have proven to be the most accessible business vehicle inside enterprises, with major domestic tech companies all investing heavily in this category. Yet to date, every multidimensional-table product globally has been trapped in a "category impossible triangle" technical dilemma: "large data volume × real-time multi-user collaboration × ease of use" cannot simultaneously hold — something always gives, whether scale, collaboration smoothness, or learning curve.

Teable confronted this trilemma from day one. From Lark multidimensional tables to Vika to Teable, founder Jiabei Chen spent eight years rebuilding multidimensional tables three times, ultimately creating the world's only multidimensional-table foundation that fully opens million-row datasets in its cloud version from the start — earning broad recognition from overseas users and developers.

Teable: million-row datasets, millisecond response

No skyscraper without its foundation. On this basis emerged the world's first multidimensional-table agent, AI Database Agent, pushing AI-native to the extreme so ordinary people no longer fear technology. Even white-collar workers with no coding background can use natural language for conversational database and app building, with automation and analysis协同 on the same foundation; extract structured data from invoices/contracts/resumes conversationally and write back to ledgers; analyze without SQL, getting metrics and charts from a single question.

This isn't merely "better experience" — it's enabling what previously didn't exist across numerous scenarios — making radical ease-of-use and data autonomy coexist in one product, translating real productivity gains into teams' daily operations.

One of Teable 2.0's six core features: conversational batch document organization

For enterprise customers, Jiabei Chen has observed that "data sovereignty / data residency / compliance and control" have become hard requirements in procurement decisions. Born open-source and sharing the same stack as its cloud version, Teable offers license-based private deployment: enterprises need only obtain a license key to deploy in their own environments, with identical user experience to cloud, "same stack, same source" architecture and capabilities — usage limits determined by the organization's own compute and storage resources, avoiding public-cloud quota constraints.

Teable: strong support for cloud, private deployment, and enterprise editions

On the engineering side, Teable is built around "Easy · Reliable · Fast", strengthened for high concurrency, complex permissions, and full-chain audit scenarios; on the governance side, it provides enterprise capabilities including SSO/SAML single sign-on, RBAC fine-grained permissions, audit logs, and organization/space management, ensuring controllability, traceability, and compliance. This allows industries with higher data autonomy and compliance requirements — finance, manufacturing, cross-border operations — to scale smoothly from small teams to group level, achieving both radical ease-of-use and security trustworthiness on a single product foundation.

Going forward, Teable will open direct connection to enterprises' existing databases, serving as a unified bridge layer between data and business: without altering existing data stacks, driving modeling, querying, and workflow orchestration through natural language, eliminating communication gaps between database teams and business teams in medium-to-large enterprises, and translating data capabilities into business outcomes faster and more securely.

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