DataFocus
Search-style NLQ analytics on its own lakehouse; claims sub-3s answers
Overview
DataFocus is a search-based BI platform from Hangzhou (founded 2014) that lets users query an integrated lakehouse in natural language instead of dragging and dropping. It ships cloud and on-premise, keeps raw data out of the LLM by sending only query text and schema, and serves 5,000+ customers.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
What you can produce with DataFocus
- Natural-language search-to-dashboard (Focus Search engine)
- Integrated lakehouse + ELT pipeline
- Cluster-scaled querying for large datasets
- Privacy-preserving LLM calls (schema only, not raw data)
- Cloud and on-premise deployment options
- Sub-3-second full-chain query response (vendor-claimed)
ASEAN Perspective
DataFocus 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).
One of the first Chinese vendors to build a genuinely search-driven BI product, DataFocus let users type a question and get a chart years before "ChatBI" became a marketing category. It bundles its own lakehouse and ELT rather than bolting search onto someone else's warehouse, and its privacy pitch — only query text and schema reach the model, never raw rows — is a real differentiator for regulated industries.
DataFocus's own numbers claim a 0% SQL-error rate on matched keywords and sub-3-second response across large datasets, plus a client citing a 10% shorter marketing-campaign cycle; worth treating as marketing until independently verified, since there's no G2 or Capterra presence to cross-check. Multi-turn conversational depth is reportedly weaker than newer LLM-native competitors. Its English site and cloud signup make it more accessible to ASEAN evaluators than most peers in this category, but pricing is sales-led with no public tiers.
What people say
Founded at the end of 2014 by a team with backgrounds from the Chinese Academy of Sciences, Beihang University and Huazhong University of Science and Technology, DataFocus built its pitch around natural-language search predating the current wave of LLM-powered "ChatBI" tools — its own marketing calls it the first Chinese-language natural-language big-data analysis system, citing tens of millions of processed searches before most competitors had a product. The company, registered as Hangzhou Huishu Zhitong Technology, is based in Hangzhou's Qiantang district.
The platform bundles an integrated lakehouse, an ELT pipeline and its "Focus Search" relational-parsing engine so a natural-language question resolves into a dashboard — DataFocus claims about seven minutes from question to finished dashboard — with cluster scaling meant to keep response times flat as data volume grows. Its stated privacy model only sends query text and table schema to the underlying LLM, not raw records, which the company positions as the reason regulated customers can use it without a full on-prem deployment.
DataFocus's own case studies report a 0% error rate on keyword-matched SQL generation, full-chain response times under three seconds, and roughly a 1,000x efficiency gain over manual query-writing on its benchmark workload; one retail client is cited as shortening marketing-campaign cycles by about 10% after several months of iterating with the tool. The company says it has 5,000+ individual and enterprise users, naming State Grid and COFCO among its clients, and it hosted a 2025 webinar specifically on Text2SQL reliability for enterprise ChatBI deployments — an implicit acknowledgment that Text2SQL accuracy is the central trust problem the whole category has to solve.
None of these figures come from an independent benchmark; DataFocus has no meaningful footprint on G2, Capterra or PeerSpot, so there's no third-party review data to weigh against the company's own claims. Coverage that does exist describes DataFocus's natural-language understanding as comparatively weaker on multi-turn, follow-up-heavy conversations than some newer competitors, even though its single-shot search-to-chart experience is well regarded. Pricing is sales-led — DataFocus asks prospective customers to talk to an account rep rather than publishing tiers — though it does offer both cloud and on-premise deployment, unlike some purely on-prem Chinese BI vendors.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including DataFocus's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with DataFocus 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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