Elastic Observability customers saw 243% ROI and $1.2 million in savings over 3 years For government and education organizations around the world, facilitating an efficient, reliable customer experience is essential when providing critical services and building trust with stakeholders. As technology infrastructure expands and the IT landscape becomes a complex mix of private cloud, public cloud, and air-gapped environments, the ability to see across all systems and data is challenging yet critical.
For the past few months, we’ve been working closely with the LangChain team as they made progress on launching LangServe and LangChain Templates! LangChain Templates is a set of reference architectures to build production-ready generative AI applications. You can read more about the launch here.
Generative AI has already shown its huge potential, but there are many applications that out-of-the-box large language model (LLM) solutions aren’t suitable for. These include enterprise-level applications like summarizing your own internal notes and answering questions about internal data and documents, as well as applications like running queries on your own data to equip the AI with known facts (reducing “hallucinations” and improving outcomes).