Prompt engineering for enterprise chatbots
LLMs such as GPT-4 are like magic.
Prompt Engineering: How to Write the Perfect Prompt (with examples)
Engineering a good LLM prompt is a variable process, and it often takes repetition and fine-tuning to get the desired outcome from the model. While there isn’t any definite...
How to build a scalable ingestion pipeline for enterprise generative AI applications
Why it’s not as simple as the hello-world guides make it look
Choose the best embedding model for your Retrieval-augmented generation (RAG) system
Retrieval-augmented generation (RAG) systems augment an LLM's inherent knowledge with external data such as company knowledge bases, up-to-date web pages, and other data sources...
Enterprise Bot vs. Microsoft Copilot Studio
Businesses are increasingly relying on AI-powered chatbot solutions to streamline operations and customer service. Enterprise chatbots that can be trained on your company's data...
Comparing Enterprise Bot and Cognigy
A head-to-head comparison looking at features, ease-of-use, and how to set up a basic RAG and LLM bot on each platform.
Enterprise Bot vs. Copilot Studio vs. Cognigy vs. Kore.ai
Back to BASICs: A Generative AI benchmark for Enterprise
Existing AI benchmarks are too academic to easily use in enterprise settings which need more context of enterprise data and LLM's ability to correctly ingest, read, understand and...
Enterprise Generative AI: Build vs. Buy
Generative AI (GenAI) is poised to catalyze innovation and revolutionize customer experience across all business sectors. The question is not whether you should implement a GenAI...