Datagrand 达观数据
Document AI specialist behind the Caozhi domain LLM
Overview
Datagrand (达观数据) is a Chinese document-AI vendor founded in 2015, serving finance, legal, and government clients with OCR/NLP document extraction, its own Caozhi LLM, and RPA execution for office-agent workflows.
What you can produce with Datagrand 达观数据
- IDP engine: NLP + deep learning + computer vision document extraction
- Document comparison and audit-risk flagging
- Table parsing from unstructured documents
- Caozhi (曹植) proprietary long-context LLM (2023)
- RPA execution layered on extracted document data
- Named enterprise clients incl. UnionPay and Shenzhen Stock Exchange affiliates
ASEAN Perspective
Datagrand 达观数据 in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Datagrand's specialty is genuinely narrow in a good way: extracting and auditing structured data out of messy documents — contracts, filings, financial statements — for industries that live and die by paperwork accuracy, namely finance, legal, and government. It's been at this since 2015, raised through at least a Series C (roughly 580 million yuan in 2022) from investors including Shenzhen Capital Group, and built Caozhi, its own long-context, multi-language LLM unveiled in 2023, to pair with the IDP and RPA stack rather than depend entirely on third-party models. The customer roster is credible — UnionPay, People's Daily Online, and several major banks are named in company materials. What's thin is independent validation: no G2, Capterra, or Gartner Peer Insights presence turned up in research, so most of what's known about Datagrand comes from the company's own disclosures and funding-round press coverage rather than user reviews.
What people say
Datagrand is harder to independently verify than the other four vendors in this batch — it doesn't show up on G2, Capterra, or Gartner Peer Insights, so there's no user-review layer to check the company's own claims against. That's a real gap for a vendor otherwise well documented on the funding and product side.
What is verifiable: Datagrand has raised money across several rounds tracked by 36Kr and other Chinese tech press — a 10 million yuan angel round from ZhenFund in 2015, a roughly 50 million yuan Series A from SBCVC and Fangguang Capital in 2017, a B+ round led by Shenzhen Capital Group, and a 580 million yuan (roughly $85M) Series C in 2022. That funding trail points to a company that's been through multiple institutional due-diligence cycles, even without a public review footprint to independently cross-check.
The named client list is specific rather than vague: UnionPay, People's Daily Online (人民网), and several major banks appear in the company's own case-study materials, concentrated in finance, legal, media, telecom, manufacturing, and government. Headcount was reported at roughly 400 people, with more than half in R&D, and offices in Beijing, Chengdu, Shenzhen, and Zhengzhou beyond its home base.
On the product itself, Datagrand's core IDP engine combines NLP, deep learning, and computer vision to pull key fields out of documents, compare document versions, flag audit risk, and parse tables — tedious, error-prone work when done by hand in compliance-heavy industries. In 2023 the company added Caozhi (曹植), its own large language model built for long-document handling and multi-language text tasks, positioning it as a domestic alternative to relying on third-party foundation models for document-heavy enterprise work. RPA execution sits alongside the IDP layer so extracted data can trigger downstream automated actions rather than just populate a database.
Net: a specialist vendor with real institutional backing and a credible client list, but one where 'what real users say' can't currently be answered from independent review platforms — only from the company's own material and funding-round press coverage.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Datagrand 达观数据's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Datagrand 达观数据 unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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