Lutra AI Launches to Simplify Building AI Workflows

Founded by former Google and Coursera employees including Jiquan Ngiam, Lutra focuses on a code-first approach to integrating AI.

Lutra AI Launches to Simplify Building AI Workflows
Image Credit: Maginative

A new startup called Lutra AI has emerged from stealth mode with $3.8 million in seed funding, aiming to make it easier for anyone to create customized AI-powered workflows.

Founded by former Google and Coursera employees including Jiquan Ngiam, Lutra focuses on a code-first approach to integrating AI. While other no-code AI workflow tools often have limits, Lutra leverages the latest natural language AI models to generate production-ready code. This allows the creation of workflows that connect across tools like Gmail, Slack, and more.

As Ngiam explained, the inspiration came from seeing manual engineering functions at previous employers that could have been automated to boost productivity. But resources were never prioritized to make that happen.

With recent advances in AI reasoning, planning, and coding, the Lutra founders saw an opportunity to enable non-technical users to build their own AI assistants. These specialized workflows automate repetitive tasks like email organization, customer communication, and even extracting data from documents.

Lutra enters an increasingly crowded AI workflow market, but its unique approach could help to set it apart. The startup's key advantage is its focus on reliability and security amidst wide AI adoption. By putting code first rather than just no-code interfaces, Lutra bakes in practices like credential management, testing, and permissions. This provides control as AI takes more actions.

Early potential customers span industries where connecting web services to boost efficiency is valuable. The platform is currently in private beta as the team focuses on product-market fit.

The $3.8 million funding round was led by Coatue Ventures, with participation from Hustle Fund, Maven Ventures, and notable angel investors.

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