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    DataYes

    DataYes

    AI Empowers Investment

    Est 2013|Raised $100M|11 Ref Customers
    LinkedIn 1K|Web traffic 72K|FTEs 213|HQ Shanghai, Shanghai, CN
    MarketsInvestment Research & Market Intelligence PlatformsMarket Data & Reference Data
    DataYes screenshot
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      Published Oct 15, 2026

      01Common complaints

      Consider alternatives when: 1. You require audited, publicly documented security certifications (SOC 2 Type II / ISO 27001) and cannot accept documentation provided only under NDA or in contract. 2. Your primary coverage need is global multi-asset rather than China-centric; vendors such as Bloomberg, Refinitiv, FactSet, or Morningstar may provide broader international coverage. 3. You require a large English-language developer community, extensive public SDKs, and active forum support; DataYes appears oriented toward institutional sales rather than community-driven developer engagement in English channels. 4. You require publicly posted, straightforward pricing for small teams; DataYes appears to be sold via enterprise quotation. 5. You require independently validated performance documentation for AI forecasts or alternative-data-derived signals; public methodology validation was not identified in the reviewed materials.

      Deal disqualifiers (likely)

      • Requirement for publicly documented SOC 2 / ISO certifications as a strict onboarding requirement
      • Requirement for transparent, self-serve published pricing
      • Predominantly non-China investment universe needs (global-first needs may be better served by competitors with broader global coverage)

      Vendor-acknowledged limitations

      The reviewed pages did not include an explicit public list of known issues or a public product roadmap in English.

      Practical limitations inferred from available evidence

      - Security and compliance transparency gap: certifications and detailed controls are not publicly documented in English on the vendor site. - Pricing opacity: no public pricing tiers were identified on English pages. - Limited independent coverage in English-language press and analyst outlets: few analyst articles surfaced in the materials reviewed. - Review visibility constraints: Gartner Peer Insights summary indicates positive ratings, but full review text was not retrieved for analysis.

      02Why they buy

      Potential unique selling points (vendor-stated)

      • China A-share forecasting and monitoring focus: vendor materials reference a library of forecasting models oriented to China A-share stocks.
      • Knowledge graph–based search and monitoring: the vendor highlights a knowledge-graph-based approach to data relationships and discovery.
      • Vendor-stated scale metrics: the vendor reports a large institutional and retail user base.

      Important caveat

      These points are primarily vendor-provided. Public third-party validation of forecasting accuracy, latency, or return on investment was not identified in the materials reviewed.

      03Field reports

      Review platform coverage

      • Gartner Peer Insights shows a very highly rated summary for Datayes.
      • Capterra listing exists but shows limited review presence.
      • No clear product review page for DataYes was identified on G2 in the initial searches.

      Vendor-published testimonials (marketing site)

      Vendor-published testimonials on the marketing site are generally anonymized. The vendor presents short customer-attributed statements that indicate customers selected the vendor after market evaluation, report satisfaction with certain datasets (including alternative data like news sentiment), and reference recognition of components such as UQER's optimizer and risk models. These testimonials are vendor-curated and anonymized, which limits independent verification.

      Community/social sentiment (Reddit, Hacker News)

      Searches for "DataYes reddit" and "DataYes site:news.ycombinator.com" did not surface substantive discussions about the product in the results reviewed. English-language community discourse appears limited for this product.

      Balanced view: what can be concluded

      • There is some third-party review presence in major review platforms.
      • Public, independent, and quotable end-user reviews in English were limited in the materials retrieved.

      Note: The review and testimonial visibility limitation is a data-availability constraint rather than an evaluative conclusion about service quality.

      Public case studies

      No detailed, named public case studies with quantified ROI and methodology were found on the vendor's English pages reviewed.

      Vendor customer feedback snippets (partial evidence)

      The vendor's site contains outcome-style statements implying capabilities such as enabling faster opportunity capture or supporting factor construction using sentiment data. These items are anonymized and typically lack disclosed metrics or methodology. Treat such statements as directional indicators rather than independently verified evidence.

      04Best fit

      Company sizes

      Best fit appears to be mid-market to enterprise financial institutions (for example, teams in the 50–5,000+ employee range) with dedicated investment research and quant staff.

      The vendor appears to be a large organization.

      Industries / verticals

      • Asset management (mutual funds, hedge funds, quant funds)
      • Securities firms / broker-dealers
      • Banks and insurance investment divisions
      • Wealth management platforms with China product exposure

      Roles and personas

      • Portfolio managers
      • Fundamental research analysts
      • Quantitative researchers
      • Risk managers
      • Investment operations / performance attribution teams
      • Data engineering and analytics teams integrating data feeds

      Pain points addressed

      • Faster discovery of company and industry signals (search and monitoring)
      • Access to alternative datasets (for example, sentiment data)
      • Portfolio construction, tracking, and regulatory-oriented risk monitoring

      05The pitch

      What the product does (objective value proposition)

      DataYes (also presented by the vendor as "Datayes") is a financial data and investment platform provider with a focus on China capital markets. The company offers: - Investment research tooling (search across data/news/reports; monitoring/alerts; knowledge-graph-based discovery tools) - Portfolio management and risk monitoring capabilities for institutional workflows - Financial data services spanning traditional and alternative datasets, described by the vendor as low-latency and with a focus on data quality - A quantitative research environment (UQER) with APIs/SDKs for quantitative workflows The vendor describes the product as a unified platform supporting investment research, portfolio management, and risk control, and emphasizes use of AI, large datasets, and knowledge graph technologies in its marketing.

      Target market and positioning

      Primary target: China-focused asset managers, securities firms, banks, insurers, and other institutional investment organizations requiring A-share coverage and China-specific datasets. Secondary target: Individual investors via a Datayes mobile app (per vendor description). The English marketing site is oriented toward institutional buyers (demo requests, data catalog downloads, positioning as a consolidated asset management offering). Positioning theme: use of AI to support investment processes combined with depth on China market coverage (A-share forecasting models, alternative data, monitoring).

      Get a comprehensive analysis of DataYes including market position, competitive landscape, adoption trends, and peer benchmarks.

      Download full report →

      Consider alternatives when:

      1. You require audited, publicly documented security certifications (SOC 2 Type II / ISO 27001) and cannot accept documentation provided only under NDA or in contract.
      2. Your primary coverage need is global multi-asset rather than China-centric; vendors such as Bloomberg, Refinitiv, FactSet, or Morningstar may provide broader international coverage.
      3. You require a large English-language developer community, extensive public SDKs, and active forum support; DataYes appears oriented toward institutional sales rather than community-driven developer engagement in English channels.
      4. You require publicly posted, straightforward pricing for small teams; DataYes appears to be sold via enterprise quotation.
      5. You require independently validated performance documentation for AI forecasts or alternative-data-derived signals; public methodology validation was not identified in the reviewed materials.
      • Security and compliance transparency gap: certifications and detailed controls are not publicly documented in English on the vendor site.
      • Pricing opacity: no public pricing tiers were identified on English pages.
      • Limited independent coverage in English-language press and analyst outlets: few analyst articles surfaced in the materials reviewed.
      • Review visibility constraints: Gartner Peer Insights summary indicates positive ratings, but full review text was not retrieved for analysis.

      DataYes (also presented by the vendor as "Datayes") is a financial data and investment platform provider with a focus on China capital markets. The company offers:

      • Investment research tooling (search across data/news/reports; monitoring/alerts; knowledge-graph-based discovery tools)
      • Portfolio management and risk monitoring capabilities for institutional workflows
      • Financial data services spanning traditional and alternative datasets, described by the vendor as low-latency and with a focus on data quality
      • A quantitative research environment (UQER) with APIs/SDKs for quantitative workflows

      The vendor describes the product as a unified platform supporting investment research, portfolio management, and risk control, and emphasizes use of AI, large datasets, and knowledge graph technologies in its marketing.

      Primary target: China-focused asset managers, securities firms, banks, insurers, and other institutional investment organizations requiring A-share coverage and China-specific datasets.

      Secondary target: Individual investors via a Datayes mobile app (per vendor description). The English marketing site is oriented toward institutional buyers (demo requests, data catalog downloads, positioning as a consolidated asset management offering).

      Positioning theme: use of AI to support investment processes combined with depth on China market coverage (A-share forecasting models, alternative data, monitoring).