Connecty AI funding news – Connecty AI Secures $1.8 Million in Pre-Seed Funding

In recent years, many AI-powered tools have claimed they can replace data analysts, but these tools often fail to meet expectations. They struggle to understand the messy, fragmented data in large enterprise systems.

Earlier AI solutions tried to automate data workflows by interpreting static data schemas. However, these models don’t work well in complex enterprise environments. To be effective, AI needs more than just fixed data files—it needs a constantly updated, cohesive understanding of data across different systems and teams.

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Connecty AI Offering

Connecty AI helps teams find valuable insights and save up to 80% of the time usually spent on manual data analysis. It gathers and links important context from various data sources and situations, while also including real-time feedback from users, to create a custom context map for each business.

Aish Agarwal, CEO of Connecty AI said, "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 reliable production level application."

Investor of the round

Market One Capital led the funding round, with support from Notion Capital and data experts like Marcin Zukowski, co-founder of Snowflake, and Maciej Zawadzinski, founder of Piwik PRO.

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 use LLMs for data workflow automation.”

Connecty AI plans to expand its context engine to work with more data sources and offer it as an API service.

About Connecty AI

Connecty AI helps data teams work faster by using advanced learning tools to understand complex data. This can save them up to 80% of the time they usually spend on manual tasks.