DotData
DotData was founded in February 2018 by Ryohei Fujimaki, PhD, a machine learning researcher and the youngest research fellow in NEC Corporation's 119-year history.
Profile
An AI-powered data science automation platform that automates feature engineering, model development, and deployment across complex datasets.
DotData was founded in February 2018 by Ryohei Fujimaki, PhD, a machine learning researcher and the youngest research fellow in NEC Corporation's 119-year history. The San Mateo-based company has raised $74.6 million across three rounds—Series A in November 2019 and Series B in April 2022, led by Japanese financial institutions Sumitomo Mitsui Banking Corporation and Otsuka Corporation. As of April 2026, the company employs approximately 88 people.
The company operates a full-cycle data science automation platform, anchored by proprietary feature engineering technology. Its product suite includes dotData Enterprise (a no-code predictive AI platform), dotData Feature Factory (automated feature engineering), dotData Insight (KPI driver discovery), dotData Ops (model orchestration and monitoring), dotData Cloud (managed infrastructure), dotData Stream (real-time processing), and the recently launched dotData TextSense (AI-powered text feature engineering). Throughout 2025 and early 2026, dotData released Enterprise 4.0 and 4.1, featuring redesigned interfaces and tighter product-suite integration. In January 2026, it announced native Snowflake integration for dotData Insight 2.1, enabling zero-copy analysis while inheriting Snowflake's governance framework. Most recently, in March 2026, the company introduced dotData Cloud Private—Self-Managed, allowing enterprises with strict data governance requirements to deploy and operate the platform independently.
The company serves financial services, insurance, manufacturing, retail, telecom, and healthcare sectors. Named customers include Exeter Finance (which achieved 90-day ML ROI), Yokohama Rubber, Sumitomo Mitsui Trust Bank, and Otsuka Corporation (which increased business proposals from automated feature discovery to over 70,000 in six months). DotData positions itself against established competitors like Databricks, H2O, and DataRobot, though it remains less widely recognized than larger rivals. The platform is designed for both technical teams (data scientists, BI analysts) and business users seeking to accelerate data science cycles from months to days.
Products by DotData
- D dotData Cloud Private—Self-Managed dotData Cloud Private—Self-Managed is a self-hosted AI platform designed for enterprises seeking full control over their AI discovery Be the first to review →
- D dotData Feature Factory dotData Feature Factory is an AI-powered feature engineering platform designed for data science teams in enterprises, particularly financial Be the first to review →
- D dotData Stream dotData Stream is a containerized AI/ML engine designed for enterprises needing real-time predictive analytics in scenarios like fraud Be the first to review →
- D dotData TextSense dotData TextSense is an AI-powered text analysis platform designed for enterprises needing to extract actionable insights from unstructured Be the first to review →
Who buys this
- Financial services and lending firms building credit risk and fraud models
- Insurance underwriters automating premium pricing and claims analysis
- Manufacturing companies optimizing supply chain and equipment maintenance predictions
- Retail and sales teams discovering drivers behind churn and customer lifetime value
- Mid-to-large enterprises on Snowflake, Databricks, or AWS requiring governed, multi-user AI workflows
Publicly disclosed clients
- Exeter Finance
- Yokohama Rubber
- Otsuka Corporation
- Sumitomo Mitsui Trust Bank
- Sumitomo Mitsui Banking Corporation
- Sticky.io
Strengths and what to watch
Strengths
- Proprietary Feature Factory technology that automates feature engineering at scale, reducing manual data science work by weeks
- Deep Snowflake and Databricks integrations that leverage native cloud compute without data movement, enabling governed multi-tenant deployments
- Product velocity: shipped four major product releases between April 2025 and March 2026 (Enterprise 4.0/4.1, Insight 1.4/2.1, TextSense, Cloud Private)
Watch for
- No Series C announced since April 2022; growth trajectory and runway unclear without recent funding or public revenue disclosure
- Customer concentration: notable wins in Japan (Otsuka, Sumitomo, JAL) suggest geographic bias; penetration in North America and Europe not well documented
- Market visibility: Forrester as of recent reports characterized dotData as a 'dark horse' with solid capabilities but limited market recognition relative to Databricks, H2O, and DataRobot
Recent moves
- 6mo ago dotData Expands AI Accessibility with Self-Managed Deployment and Next-Gen Text Analytics Capabilities
- 8mo ago dotData Announces dotData Insight 2.1, Natively Integrated with Snowflake
- 10mo ago dotData Launches dotData TextSense, an AI-Powered Text Feature Engineering Tool
- 10mo ago dotData Announces dotData Enterprise 4.1 with Enhanced UI/UX and Deeper Product Suite Integration
- 1y ago dotData Announces dotData Insight 1.4 with AI Driver Stacking, Snowflake and Salesforce Connectors, and Amazon Bedrock Support
Key Information
- Industry
- Enterprise ML Platforms
- Founded
- 2018
- Headquarters
- San Mateo
Frequently Asked Questions
What is DotData?
DotData is an AI-powered data science automation platform that automates feature engineering, model development, and deployment. Founded in 2018 by machine learning researcher Ryohei Fujimaki, it serves financial services, insurance, manufacturing, retail, and healthcare sectors with a suite of no-code and code tools.
How does DotData automate feature engineering?
DotData's proprietary Feature Factory technology automates feature engineering at scale, reducing manual data science work by weeks. The platform generates thousands of candidate features automatically, enabling data scientists to focus on model development and business validation rather than time-consuming manual feature creation.
What is DotData Insight?
DotData Insight is a KPI driver discovery tool that identifies which factors most influence business outcomes. Version 2.1 integrates natively with Snowflake, enabling zero-copy analysis while inheriting Snowflake's governance framework, allowing enterprises to discover drivers behind metrics like churn and customer lifetime value.
Does DotData integrate with Snowflake?
Yes. DotData Insight 2.1, released in January 2026, offers native Snowflake integration enabling zero-copy analysis. DotData also integrates deeply with Databricks and AWS. Both integrations leverage native cloud compute without moving data, enabling governed multi-tenant deployments on existing enterprise data platforms.
What results have DotData customers achieved?
Exeter Finance reduced ML model ROI to 90 days. Otsuka Corporation increased automated business proposals from feature discovery to over 70,000 in six months. Customers across financial services, insurance, manufacturing, and retail have accelerated data science cycles from months to days using the platform.
How is DotData positioned against competitors?
DotData competes with Databricks, H2O, and DataRobot, though it remains less widely recognized. Forrester characterizes it as a 'dark horse' with solid capabilities but limited market visibility. Its proprietary Feature Factory and deep Snowflake integration differentiate it among mid-to-large enterprises requiring governed AI workflows.
How DotData compares
Direct head-to-head against 3 competitors. Picked by 7wData.
DotData
- Positioning
- An AI-powered data science automation platform that automates feature engineering, model development, and deployment across complex datasets.
- Customer segments
- Financial services and lending firms building credit risk and fraud models
- Strengths
- Proprietary Feature Factory technology that automates feature engineering at scale, reducing manual data science work by weeks
- Watch for
- No Series C announced since April 2022; growth trajectory and runway unclear without recent funding or public revenue disclosure
- Recent moves
- dotData Expands AI Accessibility with Self-Managed Deployment and Next-Gen Text Analytics Capabilities
DataRobot
- Positioning
- Gartner-recognized enterprise AutoML and MLOps platform, pivoting to agentic AI orchestration for regulated industries.
- Customer segments
- Large enterprises in financial services, insurance, healthcare, and manufacturing. Buyers are AI/ML platform leads and data science directors.
- Strengths
- Automated feature engineering and model explainability at enterprise scale, with documented deployments at Capital One, Pfizer, and Travelers Insurance.
- Watch for
- Contracts run $150K to $500K per year. Multiple reviewers on Gartner Peer Insights cited cost as the reason they dropped the platform.
- Recent moves
- July 2025: launched Agent Workforce Platform with NVIDIA, repositioning the product around multi-agent enterprise AI orchestration.
H2O.ai
- Positioning
- Enterprise AutoML platform, Gartner Visionary, targeting regulated industries with sovereign and on-prem predictive AI deployments.
- Customer segments
- Large enterprises in financial services, insurance, healthcare, and US federal agencies with compliance and data privacy requirements.
- Strengths
- Automated feature engineering in Driverless AI, cited by analysts as a concrete differentiator versus DataRobot and Azure AutoML.
- Watch for
- Pricing prohibitive for mid-market: documented 3-year enterprise license runs approximately $390,000, blocking non-Fortune 500 buyers.
- Recent moves
- May 2025: FedRAMP high-impact designation achieved, opening US federal agency sales for Driverless AI and h2oGPTe.
Dataiku
- Positioning
- Enterprise AI/ML platform recognized four consecutive years as a Gartner Magic Quadrant Leader for data science and ML platforms.
- Customer segments
- Large enterprises (10,000+ employees) in financial services, pharma, logistics. Buyers are AI platform owners and data science team leads.
- Strengths
- Ranked number one for the Product Owner use case in the 2025 Gartner Critical Capabilities report, covering governed AI workflow delivery.
- Watch for
- Enterprise-only pricing with no public tiers is a documented friction point, blocking smaller internal teams from expanding adoption.
- Recent moves
- March 2026: repositioned as Platform for AI Success, launching Agent Management, Reasoning Systems, and Cobuild as three bundled new products.
Sources
- dotdata.com — Company overview, product suite, core mission
- dotdata.com — Founding date (February 2018), founder Ryohei Fujimaki, company milestones, funding history
- tracxn.com — Current employee count (88 as of April 2026), Series B funding details, funding stage, competitors
- dotdata.com — Series B funding $31.6M in April 2022, total funding $74.6M, lead investors (Otsuka, Sumitomo Mitsui)
- dotdata.com — Named customers and case studies (Exeter Finance, Yokohama Rubber, Sticky.io, Sumitomo Mitsui Trust Bank, Otsuka)
- dotdata.com — Snowflake native integration in Insight 2.1, January 2026 release, AI drill-down analysis capabilities
- dotdata.com — Enterprise 4.1 release November 2025, pivot-table drill-down analysis, product suite integration