Connecty AI raises $1.8m to solve enterprise data’s three-dimensional problem
Enterprises today navigate data complexity
With enterprise data systems becoming increasingly fragmented and complex, data teams often become overwhelmed by time-consuming manual processes. Despite a wave of AI-driven tools designed to automate these workflows, many fall short of expectations, leaving organisations to spend millions annually on data management.
Connecty AI emerged from stealth mode on November 11, 2024, with $1.8 million in pre-seed funding, offering a novel solution to this persistent challenge.
Led by Market One Capital, with participation from Notion Capital and data industry experts including Marcin Zukowski, co-founder of Snowflake, and Maciej Zawadzinski, founder of Piwik PRO, Connecty AI has developed a powerful context-aware platform to address the inherent complexity of enterprise data systems.
This innovative platform simplifies the chaotic, multi-layered data workflows that slow down teams and escalate costs. According to the company, enterprises spend an average of $4.6 million annually on manual data analysis, with teams dedicating 87% of their time just to data management rather than deriving actionable insights.
Enterprises today navigate data complexity across three critical dimensions:
- Horizontal data pipelines: Integrating data from multiple sources across cloud platforms and data warehouses like Snowflake and BigQuery.
- Diverse consumption patterns: Data is accessed and used across various systems, such as CRMs, BI dashboards, and machine learning models.
- Distributed human knowledge: Teams of data engineers, analysts, and business managers all rely on the same data but with varying interpretations and needs.
Early AI solutions to automate data workflows struggled because they relied on static schema files that could not adapt to the dynamic nature of real-world data. Even when these models claimed to automate tasks, they failed to provide consistent, reliable results, limiting their value for enterprises with complex data landscapes.
“We realised that effective data management is about more than just technology—it’s about connecting the dots between data sources, business objectives, and the people who use them,” said Aish Agarwal, CEO and co-founder of Connecty AI.
AI tools’ failing
“Many AI tools fall short because they do not build an ongoing, cohesive understanding across all the systems and teams involved. Our platform does just that.”
At the heart of Connecty AI’s platform is its context engine. This engine extracts and connects three-dimensional context from various data sources and use cases while incorporating real-time human feedback. The result is a dynamic, enterprise-specific context graph that continuously evolves with the data landscape.
Using a personalised dynamic semantic system leveraging this context, Connecty AI’s system automates complex data tasks across various roles, such as data engineers, analysts, and business teams.
This system operates continuously in the background, proactively generating recommendations, updating documentation, and uncovering hidden metrics aligned with business goals. The platform can integrate with data warehouses in under five minutes, with no-code deployment options, and works seamlessly with major platforms like Snowflake, BigQuery, Databricks, and Power BI.
Real-world deployments
Connecty AI’s approach has already shown promise in real-world deployments. During its prototype phase, the company partnered with enterprises with annual revenue ranging from $5 million to $2 billion to validate its solution.
For example, Nicolas Heymann, CEO of Kittl, shared that before using Connecty AI, his team would often wait 2-3 weeks to prepare data and extract actionable insights. “Now, it’s a matter of minutes,” he said.
Similarly, Aditya Upadhyay, Director of Analytics at Mindtickle, praised the platform’s accuracy and its ability to generate valuable suggestions for improving schema descriptions and enhancing the semantic layer. “It offers a unified flow from prep to querying, unlike anything we’ve seen before,” he noted.
Connecty AI was founded by Aish Agarwal and Peter Wisniewski, who bring complementary backgrounds in the data value chain. Agarwal’s experience at FL Studio exposed him to the inefficiencies caused by fragmented data systems. Wisniewski’s time building data platforms at Point72 hedge fund and for a significant European e-commerce company highlighted similar challenges from a data engineering perspective.
The timing of their launch aligns with the growing demand for AI solutions that can automate data workflows. The global AI analytics market is projected to grow at a CAGR of 22.6%, reaching $223 billion by 2034. As data complexity increases, so do the costs of maintaining these systems. Data teams already consume 12.5% of IT budgets, with an average of $5.4 million spent annually on platform maintenance alone.
Connecty AI plans to expand its platform’s capabilities by supporting additional data sources and offering the solution as a service via API. The company emphasises that its approach does not replace human data analysts but augments their capabilities.
By automating repetitive tasks and enhancing decision-making with context-driven insights, Connecty AI’s platform empowers teams to work more efficiently and make data-driven decisions faster.
“We are thrilled to back Connecty AI as they redefine enterprise data management with their deep context learning,” said Jacek Łubiński, Partner at Market One Capital.
“The platform’s ability to unify and contextualise data across fragmented systems presents a massive opportunity for businesses looking to automate data workflows using AI. We are excited to support Aish and Peter on this journey.”
With its early traction, robust backing, and ambitious plans for future growth, Connecty AI is positioning itself as a key player in the enterprise data space—helping companies unlock hidden insights and reclaim valuable time from manual data tasks.
Featured image: (L-R) Aish Agarwal and Peter Wisniewski, co-founders of Connecty AI. Credit: Connecty AI
Last Updated on 1 month by Arnold Pinto
