In the fast-paced world of startups, the motto is often “grow fast or die.” Launching a minimum viable product, gaining traction, and raising multi-million dollar funding rounds seems to be the obligatory path. But what if there was another way? A patient, almost artisanal strategy, focused on building technology so advanced it creates an insurmountable competitive moat before hitting the commercial accelerator?

This is the story of Graphext, the startup founded by two Spanish computer engineers who dedicated seven years and approximately 7 million euros to perfecting their platform before seeking significant funding. Today, armed with cutting-edge technology and a clear vision centered on Explainable Artificial Intelligence (XAI), they are ready to redefine how companies interact with their data.

Conceptual image of Graphext

The Origin: From Analyzing Twitter to Understanding the World

Graphext’s spark didn’t come from a business plan, but from curiosity. The founders, Victoriano Izquierdo and Miguel Cantón, computer engineers with an entrepreneurial spirit since childhood, started with a tool called contexto.io, focused on analyzing connections on Twitter. They soon realized that the true potential lay in going further, in creating broader information contexts, in visualizing the hidden networks that connect people and organizations in any dataset.

Thus, Graphext was born in 2015, merging ‘graph’ and ‘context’. Their mission: to democratize data science, bridging the gap between coding experts and business analysts who have important questions but lack the tools to answer them directly. They wanted to overcome the limitations of Excel (too basic) and programming notebooks like Jupyter (too complex for non-technical profiles), aspiring to create something new: a tool “as interactive as Figma, but for data science.”

The Technology: A “Formula 1” in Your Browser

What radically differentiates Graphext is its architecture. After years of intensive R&D, they have built what their CEO describes as a “Formula 1”: an incredibly powerful analysis machine.

Their secret lies in leveraging cutting-edge web technologies like WebAssembly (Wasm), WebGL, and Apache Arrow. Thanks to Wasm, a large part of data processing (up to 80-90%!) happens directly in the user’s browser, not on a remote server. The result is astonishing fluidity: exploring and filtering millions of data rows feels instantaneous.

They have developed their own compression libraries and an internal “low-code” language. This deep investment in proprietary technology creates, according to its founders, a very difficult competitive moat to replicate.

Graphext web

The Platform: From Raw Data to Explainable Models

Graphext is not just a visualization tool; it’s a comprehensive “no-code/low-code” platform covering the entire data analysis lifecycle:

  1. Universal Connection: Import from a simple CSV or connect directly to modern data warehouses (Snowflake, BigQuery, Databricks, Redshift).
  2. Interactive Visual Exploration (EDA): The heart of the tool. Filter, group, cross-reference variables, and enrich data on the fly.
  3. Advanced No-Code Modeling: Apply machine learning algorithms (clustering, NLP for text analysis, image analysis) with clicks, not code.
  4. Prediction with Explainability (XAI): Create predictive models (to forecast customer churn or identify promising sales leads) and, crucially, understand why the model makes that prediction. This commitment to Explainable AI is at the core of their future strategy.

The “Formula 1” Dilemma: Power vs. Accessibility

Despite its “no-code” approach, Graphext acknowledges a tension: its tool is so powerful that it requires a skilled “driver” to unlock its full potential. It’s not for absolute beginners, but for business analysts, data scientists, and power users seeking superpowers.

This duality is reflected in its hybrid business model:

  • Self-service (Free and Pro): To attract users and enable organic dissemination (Product-Led Growth).
  • Enterprise: With customized pricing and data engineering and training services, recognizing that large corporations need support.

The company is evolving from selling €1,000 tickets to closing six or seven-figure contracts with corporations like McDonald’s and Roche.

An Atypical and Patient Financial Strategy

Graphext defied venture capital norms. For its first 7 years, it funded itself with a clever combination:

  • Modest Seed Capital: Small rounds, including one led by K Fund.
  • Key Public Grants: Approximately 2 million euros from European funds (Horizon 2020, EIC Fund), crucial for financing R&D without excessive dilution.

This strategy allowed them to patiently build their technological “Formula 1.” Once the product matured and technological risk was significantly reduced, they became highly attractive to top-tier venture capital.

The turning point came in June 2023 with a $4.6 million seed round led by Hoxton Ventures (London), marking the beginning of their commercial scaling phase. The backing of over 80 angel investors, including key figures from Freepik, CARTO, Snowflake, GitHub, and Meta, underscores the industry’s confidence in their vision.

Key Milestone Date Detail
Founding 2015 Graphext is born.
EU Funding 2018-2021 ~€2M in non-dilutive grants.
Key Seed Round Jun 2023 $4.6M led by Hoxton Ventures.
Team Est. 2024/25 ~50 employees (sources vary).

The Future: Explainable and Generative AI as a Competitive Advantage

Graphext’s commitment is clear: to lead the Explainable AI (XAI) space. In a world where AI is increasingly powerful but opaque, the ability to understand the “why” behind a prediction is crucial for trust and business adoption.

Furthermore, they are actively integrating generative AI not just as another feature, but as the potential solution to the “Formula 1” dilemma. They envision a future where a user can ask complex questions in natural language, and AI generates a complete, interactive analysis within Graphext, guiding the user and making the platform’s full power accessible.

Conclusion: From Lab to Commercial Race

Graphext has completed the toughest phase: building differentiated technology with a smart, patient funding strategy. Now, the challenge is commercial. They must scale their sales, especially in the international Enterprise market, and resolve the tension between power and usability.

Their story is a reminder that there’s no single path to success. Sometimes, patience, technical depth, and a clear vision can be more powerful than speed at any cost. Graphext has built its “Formula 1”; now the real race begins to prove it can win in the global market.

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