Connecty AI, an enterprise AI solutions platform has raised $1.8 million in its pre-seed funding round led by Market One Capital. The round also saw participation from Notion Capital and data industry experts including Marcin Zukowski, co-founder of Snowflake and Maciej Zawadzinski, Founder of Piwik PRO.
The funds raised will be used to expand its context engine’s capabilities across additional data sources and offer it as a service via API.
“Our experience has shown us 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. Any ad-hoc ‘guerrilla style experimentation’ with LLM data agents can lead to a pilot application but it’s a lot harder to build a production-level application that is reliable,” said Aish Agarwal, CEO of Connecty AI.
“Our data complexity is growing fast, and it takes longer to data prep and analyze metrics. We would wait 2-3 weeks on average to prepare data and extract actionable insights from our product usage data and merge with transactional and marketing data. Now with Connecty AI, it’s a matter of minutes!” said Nicolas Heymann, CEO Kittl.
“We were impressed with the accuracy of responses from day one. Additionally, Connecty AI generated excellent suggestions to improve the schema descriptions and enhanced our semantic layer. It offers a unified flow from prep to querying, nothing like that we’ve seen anywhere else,” added Aditya Upadhyay, Director Analytics, Mindtickle.
“We are thrilled to back Connecty AI as they redefine enterprise data management with their deep context learning. The platform’s ability to unify and contextualize data across fragmented systems presents a massive opportunity for businesses looking to use LLMs for data workflow automation. The vision Aish and Peter have resonates with us and we’re excited to support them on the journey,” said Jacek Łubiński, Partner at Market One Capital.
Founded by Aish Agarwal and Peter Wisniewski, Connecty AI connects to data warehouses like Snowflake or BigQuery in less than five minutes with no-code deployment.
At its core, Connecty AI does two things: first, it extracts and connects three-dimensional context from diverse data sources and use-cases while integrating real-time human feedback, creating an enterprise-specific context graph. Second, it leverages this context to automate data tasks across various roles, using a personalized dynamic semantic system. The engine operates continuously in the background, proactively generating recommendations within data pipelines, updating documentation, and uncovering hidden metrics aligned with business goals.
During prototype development, Connecty AI has partnered with enterprises ranging from $5 million to $2 billion ARR, validating its approach on real-world data rather than public datasets like Spider.
