Problem

Sana addresses the fragmentation and inefficiency of enterprise knowledge work. Employees must search across company apps, reconstruct context, and complete repetitive multi-step tasks manually; conventional tools can find information, but do not synthesize a company’s knowledge or turn it into completed work. The economic pain is lost employee time and slow execution, particularly in workflows such as meeting follow-up, RFP preparation, customer support, reporting, research, and CRM updates. Sana’s core or “killer” use case is an AI agent that understands a company’s proprietary context and reduces complex, 20-step processes to a single action. Industrial customers using Sana’s custom agents report average time savings of 50%, while customer testimony describes operational efficiency and rapid payback.

The same underlying problem appears in corporate learning: static course catalogs, manual administration, and disconnected content make it difficult to deliver timely, personalized knowledge at scale. Sana therefore targets both productivity and learning pain, helping companies make internal knowledge immediately usable rather than leaving it trapped in documents, systems, and training repositories.

Product / Service

Sana is an enterprise AI platform centered on search, knowledge access, and configurable AI agents. Users can create expert agents without coding, ground them in company data, and connect them to more than 100 business applications. The platform is model-agnostic, supports enterprise security controls, and is delivered with implementation and adoption services including a dedicated deployment lead, tailored onboarding, AI strategy, change management, and priority support. In practice, teams can ask questions in tools such as Slack, synthesize documents and data, prepare client deliverables, analyze calls, draft responses, and automate recurring operational work.

Sana also offers Sana Learn, an AI-native learning product combining an LMS, learning-experience platform, authoring tool, and virtual classroom. Its benefit is to replace one-size-fits-all learning and manual content operations with personalized, AI-assisted knowledge delivery. Reported customer outcomes include Polestar increasing monthly users from about 400 on its former LMS systems to 1,500 on Sana Learn, and boosting engagement by 275% while creating and translating training content in-house.

Market

Sana competes in the enterprise AI and AI-agent market for knowledge work, with an adjacent position in corporate learning technology. In AI knowledge and workflow automation, alternative solutions cited for Sana include Zapier, n8n, Flowise, Langflow, Dify, Microsoft Copilot Studio, and Dynamiq; its broader enterprise-AI comparison set also includes platforms such as Writer. For Sana Learn, the more direct LMS competitors are Docebo, 360Learning, and Absorb LMS. Sana’s differentiation is the combination of company-grounded AI agents, cross-application context, enterprise controls, and an integrated learning platform rather than a conventional standalone chatbot or static LMS.

Sana is a commercial company, not pre-revenue. Its own materials cite 7x year-over-year ARR growth and customers including Svea Solar, Kry, Polestar, Talabat, Spotify, and others. It raised a $55 million round led by NEA, taking total funding above $130 million, and Workday completed its acquisition of Sana in November 2025 after announcing an approximately $1.1 billion all-cash transaction. Sana now operates within Workday’s broader strategy to combine AI-powered search, agents, and learning with Workday’s enterprise data and applications.