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Welcome to another episode of Category Visionaries — the show that explores GTM stories from tech’s most innovative B2B founders. In today’s episode, we’re speaking with Malte Pietsch, CTO & Co-Founder of Deepset, an enterprise LLM platform that has raised over $45 Million in funding.

Here are the most interesting points from our conversation:

  • Deepset’s Mission: Deepset aims to enable the transformation towards intelligent applications by allowing engineering teams to build, evaluate, and rapidly deploy AI features necessary for their products.
  • Product Offering: Deepset provides two key products: Haystack, an open-source framework for orchestrating AI applications into pipelines for individual devs, and Deepset Cloud, a SaaS platform for enterprise teams to build, deploy, and manage AI features at scale.
  • The Impact of ChatGPT: The release of ChatGPT marked a significant turning point for AI, shifting from niche applications to mainstream awareness and adoption. This brought new challenges and opportunities for Deepset in navigating a market with increased interest and competition.
  • Early Convictions and Challenges: Despite the uncertainties in the early stages of AI’s market acceptance, Deepset’s team held a strong conviction about the potential of AI in transforming interactions with machines. This belief, coupled with their close work with customers, fueled their perseverance through periods of doubt.
  • Rising Above Noise: In a post-ChatGPT world teeming with AI startups and funding, Deepset focuses on demonstrating clear business value by transitioning from prototype to production, highlighting their commitment to solving real-world use cases over merely creating impressive demos.
  • Open Source and Commercial Products: Deepset’s journey included an early focus on open-source projects, leading to the development of their commercial platform, Deepset Cloud. This dual approach has allowed them to build a community, establish credibility, and cater to a broad spectrum of developers and enterprise customers.



Empower Engineering Teams:

Focus on developing tools that enable engineers to efficiently build and deploy AI features, reducing time spent on non-differentiating tasks.

Leverage Open Source for Credibility:

Use open-source products as a strategy to build credibility among developers and create a community around your technology.

Product-Market Fit Exploration:

Actively seek feedback from early users or customers to shape your product strategy, ensuring that your offerings meet real market needs.

Strategic Fundraising:

Choose investors based on alignment with your vision and their potential to add value beyond capital, rather than optimizing for the highest valuation.

Sales Strategy Evolution:

Consider transitioning from founder-led sales to a dedicated sales team earlier to scale customer engagement and streamline the sales process.

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