Story of MindsDB: Founder and CEO - Jorge Torres
Story of MindsDB:
Vision to Democratize AI
MindsDB was founded in 2017 in Berkeley, California, by
Jorge Torres and Adam Carrigan with a bold vision: to make artificial
intelligence and machine learning accessible not just to specialists, but to
everyone. They wanted to empower businesses and developers to use AI to solve
complex data problems without needing deep expertise in machine learning or
writing complex code. By 2018, the founding team made the initial code open
source, cementing their commitment to broad accessibility and community-driven innovation.
Simplifying Machine Learning with Automation
The core strength of MindsDB lies in its automated machine
learning (AutoML) platform that handles the hard parts for users—such as data
preparation, algorithm selection, and hyperparameter tuning. This automation
means that users can train predictive models quickly and accurately with
minimal manual effort, saving time and reducing errors. The platform supports
many data types and formats, making it versatile for a wide range of predictive
analytics tasks.
Bringing AI Directly to the Data
A key breakthrough was MindsDB’s approach to embedding
machine learning directly within existing databases rather than forcing users
to move data or adopt new complex tools. MindsDB integrates seamlessly with
popular databases like MySQL, PostgreSQL, MongoDB, and Snowflake. This allows
data teams to build, train, and deploy models using familiar SQL commands,
removing the need for complicated data pipelines or new workflows.
Connecting Multiple Data Sources
MindsDB offers over 200 data connectors for both structured
and unstructured data, enabling users to pull data from numerous platforms
without moving or duplicating it. This flexibility enhances data accessibility
and accelerates predictive analytics, allowing businesses to combine different
datasets effortlessly for richer insights.
Real-Time AI Insights for Better Decision-Making
Traditionally, data analysts spend days building dashboards
and extracting insights from varied sources. MindsDB disrupts this with the
ability to generate complex, accurate analytics in minutes by querying data
conversationally with natural language. This empowers non-technical users and
decision-makers to ask questions and get actionable answers instantly,
fostering faster, data-driven decisions across the enterprise.
Explainable and Trustworthy AI
MindsDB prioritizes transparency by providing explainable AI
features that show users how and why the model made specific predictions. This
interpretability builds trust, especially for industries where regulatory
compliance and accountability are critical, helping businesses confidently
implement AI-driven strategies.
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Automating AI Workflows
To simplify ongoing AI operations, MindsDB introduced
features like Jobs, which automate repetitive tasks such as regular model
retraining and evaluation. This ensures models stay up-to-date and accurate
without manual intervention, further lowering the barrier to maintaining
effective predictive analytics.
Growing Adoption and Community Support
Since its inception, MindsDB has accumulated over 400,000
deployments and a strong open-source community with more than 35,000 GitHub
stars. Tens of thousands of developers and data teams globally rely on MindsDB
to embed AI in their data infrastructure, reducing the need for dedicated AI
teams and expensive infrastructure changes.
Strong Backing and Market Position
MindsDB has raised over $54 million in funding, supported by
top investors like Benchmark, Mayfield, Y Combinator, and NVIDIA. These
resources help the company scale its platform, optimize performance, and expand
its offerings while maintaining its open-source roots. It stands strong amidst
competitive players such as Weights & Biases and DataRobot by focusing on
ease of use and direct database integration.
The Future of AI Embedded in Data
Looking ahead, MindsDB aims to continue revolutionizing the
way businesses approach AI by unifying AI access to enterprise data through
federated engines and natural language interfaces. The goal remains to empower
every team to skip complex BI bottlenecks and generate trustworthy, real-time
insights using conversational queries, thereby democratizing AI and making
data-driven success a reality for all.
Timeline
- 2017: MindsDB
founded in Berkeley by Jorge Torres and Adam Carrigan.
- 2018: Initial
open-source MindsDB code released, vision for accessible AI launched.
- 2019–2020: Expanded
data connectors and database integrations to reach more users.
- 2021–2022: Introduced
real-time conversational analytics and automation features.
- 2023: Raised
$54 million in funding, expanded platform capabilities.
- 2024–2025: Enhanced
automation workflows and explainable AI; gained wide adoption among
developers and enterprises.
