Hilbert Secures Series A for AI Growth Agents - StartupHub.ai

2026-04-15 · Source: Series A" OR "Series B" OR "Series C" AI startup via Google News · Field: Business & Management — Marketing, Branding & Advertising, E-commerce & Digital Commerce, Operations & Process Management · Depth: Fundamental Awareness, quick

Summary

Hilbert, a startup focused on automating data infrastructure for consumer company growth, has secured Series A funding led by Andreessen Horowitz (a16z). The investment targets the complex data challenges that hinder growth initiatives, specifically the "plumbing" of data schemas, event taxonomies, and attribution logic essential for effective experimentation and campaign optimization. Hilbert's technology utilizes AI to autonomously learn, structure, and label a company's data, creating reliable data foundations that adapt with business evolution. These AI growth agents aim to transform manual growth operations into data-informed, automated functions, reducing deployment times from months to weeks and saving on headcount. The company's founders, Naz and Ceyda, previously scaled growth functions at Getir, bringing relevant experience to the venture.

Key takeaway

For consumer companies struggling with complex data infrastructure, Hilbert's AI growth agents offer a solution to automate data organization and optimization. You can significantly reduce the time and cost associated with building and maintaining data foundations, allowing your teams to deploy growth initiatives in weeks instead of months. Consider how AI-driven data automation could enhance your growth investments and experiments.

Key insights

AI growth agents automate complex data infrastructure, accelerating consumer company growth and optimizing campaigns.

Principles

• Reliable data foundations are critical for growth.
• AI can autonomously structure and label data.
• Automating data plumbing reduces operational overhead.

Method

Hilbert organizes and labels essential data schemas using AI, then layers analytics, operations, and execution capabilities on top to create a robust, evolving data infrastructure for growth.

In practice

• Automate data schema organization.
• Implement AI for event taxonomy.
• Streamline attribution logic.

Topics

• Hilbert
• a16z
• AI Growth Agents
• Data Infrastructure Automation
• Consumer Company Growth

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Investor, Entrepreneur, Marketing Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Series A" OR "Series B" OR "Series C" AI startup via Google News.