AI automation platform for enterprise workflow deflection and transaction processing
Emplay builds an AI-driven automation platform (Zinger) designed to deflect high-volume support requests and accelerate transaction processing for enterprises. The tech stack reveals a mature RAG + LLM pipeline (OpenAI, LangChain, pgvector, Elasticsearch) deployed across GCP and Azure, with engineering-heavy hiring (7 roles vs. 1 sales) and an active shift toward agentic workflows — signaling a product evolution from static chatbots toward autonomous decision-support systems. Recent adopts of LangGraph and migration away from FastAPI suggest architectural rework for more complex orchestration.
Emplay, incubated by SAP.io and founded in 2013, operates an enterprise automation platform called Zinger that integrates AI-powered inquiry resolution, transaction automation, and decision support. The company targets large organizations seeking to reduce support volume and accelerate internal processes — typical use cases include customer service deflection and employee productivity tools. Headquartered in Dublin, California, with 51–200 employees, Emplay serves Fortune 500 customers and is actively scaling multi-tenant infrastructure and microservices architecture to support growing deployment complexity.
Emplay runs RAG + Python + SQL on GCP (Cloud Run, Cloud Logging) and Azure (Container Apps, Pipelines, Blob Storage). LLM backend includes OpenAI and Azure OpenAI. Orchestration uses LangChain, with Postgres + pgvector + Elasticsearch for vector search, and Celery for async task processing.
Current projects include AI copilot development, agentic AI workflow automation, LangChain RAG capabilities, FastAPI microservices migration, and multi-tenant architecture scaling — reflecting a focus on autonomous decision-support and infrastructure modernization.
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