Ema builds a multi-agent AI orchestration platform for enterprises, with proprietary LLM blending (EmaFusion), workflow orchestration (GWE), and a permissioned context graph across connected systems. The stack is modern and distributed—JavaScript/React frontend, Python/FastAPI backend, Kubernetes/GCP/AWS infrastructure—and the hiring mix is heavily skewed toward senior engineers (11 of 20 roles) alongside aggressive sales and GTM expansion, signaling a post-product-market-fit push into enterprise deployment and compliance-heavy verticals (healthcare, financial services, legal).
Notable leadership hires: Chief of Staff
Ema is an agentic AI platform that lets enterprises build and deploy autonomous AI agents across functions—HR, Finance, Sales, Support, Legal—without vendor lock-in or point-solution fragmentation. The platform connects to 200+ enterprise systems and is built on three components: an LLM fusion layer that optimizes across 100+ models, a workflow orchestration engine with human-in-the-loop audit trails, and a context graph that gives agents permissioned access to org data and processes. The company is backed by Accel, Section 32, and a strategic investment from KPMG. It supports on-premises and air-gapped deployment and holds ISO 42001, SOC 2 Type II, ISO 27001, and HIPAA certifications.
Frontend: JavaScript, React, Angular, Vue, Next.js on Vercel. Backend: Python, FastAPI, Go. Data: PostgreSQL, Redshift, Elasticsearch, Redis. Infrastructure: GCP, AWS, Azure, Kubernetes, Docker, Terraform, Helm. APIs: GraphQL, gRPC, OAuth.
Core product: retrieval systems and multi-agent AI workflow improvements. Go-to-market: partner enablement, global sales acceleration, sponsored programs, industry events, and executive roundtables. Internal: strategic planning and M&A/partnership evaluation.
Ema'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.