<aside> <img src="notion://custom_emoji/7e749044-a174-8198-bf5c-000356645683/27d49044-a174-80ec-9e24-007a08125399" alt="notion://custom_emoji/7e749044-a174-8198-bf5c-000356645683/27d49044-a174-80ec-9e24-007a08125399" width="40px" /> Under Embargo until 9:00 AM CET Paris, 2nd of December 2025
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Paris and San Francisco, December 2nd 2025 - Today, Basalt announces a $5M fundraising round to restore trust in AI agents. While launching an AI agent is easy, scaling it with consistent, production-grade performance remains a major challenge and most AI implementations fail in large companies today. Basalt is using this new funding to accelerate its mission to become the platform companies rely on to reach 99% quality in their AI applications. The company is already proving the demand, working with clients such as Swan, HealthHero and backed by leading investors including Entourage, Peak, Alpha Star, Kima Ventures, and Hexa.
AI agents are rapidly spreading across industries, promising major productivity gains. But in large companies, most deployments still fail, because of a lack of reliability. When an agent delivers inconsistent or mediocre results, trust disappears, and organizations hesitate to scale it across critical operations.
Why is it hard to create a reliable AI Agent ?
AI agents today struggle with reliability for two main reasons. First, achieving high-quality performance requires continuous iteration on prompts, a workflow that differs significantly from traditional software development. Second, the tools available to assess AI quality are largely built for engineers, limiting the input needed to define and validate “good” outcomes. Basalt solves this with the first collaborative AI engineering platform, designed to help companies reach 99% quality on their AI apps.
“Anyone can ship an AI prototype, but getting from 80% quality to true production grade remains painfully hard. The last 20% requires constant iteration on prompts and learning from edge cases - much like a child learning to walk, taking a step, stumbling, understanding why, and adjusting. AI systems need that same repeated exposure and correction to become dependable.” Guillaume, cofounder of Basalt.
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Basalt is solving this with the first collaborative AI Engineering Platform, designed to help companies reach 99% quality on their AI apps.
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Basalt is building the platform teams use to bring their AI agents from early prototype to production-grade quality. Getting it reliable requires fast iteration across the whole team, not just engineers.
“Prompts are the new building blocks of AI agents, the way code is the building block of software,” says François de Fitte, cofounder of Basalt with Guillaume. “The difference is that prompts don’t require you to speak JavaScript, just English. That’s why reliability can and should be owned by everyone, from PMs to operators and domain experts…
Three core capabilities for reaching production grade
Basalt focuses on the three essentials every AI team needs to deliver trustworthy agents:
Experiment – Try new prompts or chain them together, compare LLMs and validate improvements before anything goes live. Move fast without breaking your user experience.
Evaluate – Run structured tests across hundred or thousands of scenarios, score outputs automatically and catch errors instantly. Bring rigor to what used to be vibe checking.
