Companies that use Claude by Anthropic

Source: Analysis of 100 job postings that mention Claude by Anthropic

My analysis reveals that individual contributor Software Engineers (30%) and AI/ML Engineers (25%) make up the majority of roles, while Directors of Engineering (15%) and Data Scientists (10%) represent significant decision-making positions. The buying process appears distributed, with VPs and Directors evaluating platforms while hands-on engineers select specific tools. These organizations prioritize building agentic AI systems, RAG pipelines, and LLM orchestration at scale.

The day-to-day users are technical practitioners building production AI features. I noticed they work extensively with multi-agent frameworks, prompt engineering, and model evaluation. Common tasks include integrating Claude with other LLMs like OpenAI and Gemini, developing conversational assistants, implementing document analysis workflows, and creating intelligent automation for customer-facing applications. These teams operate in fast-paced environments where AI augments rather than replaces human expertise.

The pain points center on scaling AI capabilities efficiently and bridging business value with technical implementation. One posting seeks someone to "translate innovative AI research into real-world use cases," while another emphasizes "reducing hallucinations" and ensuring "production-grade AI features." A third describes the need to "accelerate automation" and "improve compliance accuracy." These companies want reliable, enterprise-ready AI that delivers measurable ROI while maintaining quality and governance standards.

Source: Analysis of tech stacks from 5,156 companies that use Claude by Anthropic

I noticed that companies using Anthropic Claude are deeply committed to building at the cutting edge of AI-powered work. The combination of Cursor (an AI-first code editor), ChatGPT for Teams, and Claude itself tells me these are organizations treating AI as core infrastructure, not a side experiment. They're running multiple AI platforms simultaneously, which suggests they're sophisticated enough to choose the right tool for each job rather than standardizing on one vendor.

The pairing of Cursor with Claude is particularly revealing. These companies have developers who are already coding with AI assistance, so they understand LLM capabilities intimately. Adding Golinks and Zapier Enterprise to the mix shows they're obsessed with operational efficiency and eliminating friction. They're automating workflows and creating internal shortcuts because every saved minute matters at their pace. The presence of Lucidchart and Figma Organization Plan indicates cross-functional collaboration is central to how they work. They're not just engineering shops but organizations where designers, product managers, and developers need to stay aligned on complex projects.

Looking at the full picture, these are product-led companies in high growth mode. The emphasis on developer tools and design platforms over traditional sales software suggests they're building products, not services. They're likely Series A to C startups or innovation teams within larger tech companies. They move fast, ship regularly, and invest in tools that multiply individual productivity rather than adding headcount.

Source: Analysis of Linkedin bios of 5,156 companies that use Claude by Anthropic

I noticed that Anthropic Claude users span an incredibly diverse range of industries, but they share a common thread: they're building complex systems that require sophisticated data management, automation, or customer engagement. These aren't simple businesses. I see companies developing AI-powered intelligence platforms, managing multi-location operations at scale, building enterprise software infrastructure, and delivering specialized services in highly regulated industries like healthcare, finance, and biotechnology. Many are in the business of transformation, whether that's digital transformation consulting, infrastructure automation, or reimagining traditional industries through technology.

The stage distribution is surprisingly balanced. I see early-stage startups with seed funding alongside publicly traded companies and mature enterprises with thousands of employees. However, even the larger organizations describe themselves with startup-like energy, emphasizing innovation and agility. The mid-market growth companies are particularly well-represented, those in that critical scaling phase between 50-500 employees where operational complexity explodes.