Distyl embeds engineering and research teams into enterprise customers to design and operationalize AI systems at scale. The stack spans three cloud providers (AWS, GCP, Azure) plus Kubernetes, Python, and heavy use of LLM tooling (OpenAI, LoRA, ReAct), with active adoption of ReAct reasoning frameworks. The hiring mix is engineering and research-heavy (29 of 47 roles), reflecting a services-first model where technical depth drives customer outcomes—not a typical product SaaS trajectory.
Distyl partners with large enterprises on AI transformation, deploying forward-positioned teams of engineers and researchers alongside custom-built products tailored to each client's business. Founded in 2022 and based in San Francisco with 51–200 employees, the company operates across the United States and United Kingdom. Active project work spans evaluation frameworks, multi-agent system architecture, foundation model adaptation, and healthcare-specific proof-of-concept deployments. The core challenge surfaces repeatedly: operationalizing AI at scale while reducing human bottlenecks in complex system creation and ensuring reliable execution across diverse, mission-critical environments.
AWS, GCP, Azure, Kubernetes, Python, FastAPI, OpenAI, React, TypeScript, Terraform, Datadog, Prometheus, and Okta. The stack reflects multi-cloud infrastructure, LLM-heavy development, and observability at scale.
Multi-agent AI system architecture, evaluation frameworks, foundation model adaptation, AI integration into customer data platforms, and healthcare workflow automation through proof-of-concept deployments.
Distyl's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.