Featured Stories

Introducing the first Generative CMS: Progress Sitefinity CMS powered by Progress Agentic RAG. This dynamic, hyper-personalized platform learns from organization-approved content to provide smarter experiences.

At Progress, we continue to develop and improve the Progress Flowmon product family. The latest update advances the core Flowmon product to release 13.0, offering significant performance improvements, enhanced security and expanded protocol support.

Developers, product owners and companies searching for a RAG-as-a-Service solution, listen up! The Nuclia Prompt Lab is here to revolutionize the way you test and integrate LLMs with your unstructured data. The Nuclia Prompt Lab is a unique tool that allows you to test how different LLMs behave and answer questions with your own prompts and data. Say goodbye to hours of experiments, and hello to increased product value.

Customer support is about providing answers to people’s questions. But it’s about solving problems. In many cases, the solution is written somewhere in your knowledge base. But it might be hard to find, or it might not be accessible at all. That’s where AI comes in. AI can help you optimize your customer support by making your knowledge base more accessible and easier to use.

Historically, when interacting with machines, humans had to adapt to the machine’s language to ask questions—typically using SQL queries—and then interpret the machine’s response. This response usually comes in a structured data format, such as a table or a JSON string, following a specific schema. This is the purpose of the JavaScript Object Notation (JSON) output option on Nuclia’s "/ask" endpoint.

NucliaDB’s indexing system is the backbone of its Retrieval-Augmented Generation capabilities, organizing extracted text, inferred entities and semantic vectors from customer documents. This design enables lightning-fast, context-aware searches that power Nuclia’s advanced data retrieval features.

Designed for Nuclia’s AI Search platform, NucliaDB is a multilayered, dynamically sharded storage engine that unifies blob storage, key-value metadata, and vector indexing to scale semantic search over unstructured data. Its cloud-native architecture, powered by NATS and gRPC, enables fault-tolerant distributed search while still offering a lightweight standalone mode.

LLM-powered agents (or AI copilots) take generative AI beyond basic Q&A by combining conversational ability with goal-driven behavior, and Nuclia makes it easy to build these agents by pairing RAG-powered context with tools for ingestion, prompting and deployment. This enables highly tailored, domain-specific assistants—from city guides to enterprise copilots—without requiring deep ML expertise.

This article explores how Nuclia streamlines research by transforming scattered AI-related resources into direct, actionable answers—eliminating manual search, reducing noise and ensuring accuracy without hallucinations.