SOC 2 compliance and SSO are the two security foundations enterprises expect before they will trust an AI platform with sensitive data. SOC 2 Type II is an independent attestation that a vendor’s security controls operate effectively over time, and […]
A configured OpenAI GPT is designed to run inside ChatGPT; it is not a reusable API endpoint for an external application. GPT Actions let that GPT call an external REST API, while developers building their own website, SaaS product, or […]
To create a custom GPT with your own data, define the assistant’s purpose, write clear instructions, add approved knowledge sources, enable any necessary tools, test representative questions, and select the appropriate access settings. The best platform depends on whether the […]
For the companion implementation view, read the components of a RAG system technical deep dive. For implementation details after the concept overview, use this step-by-step RAG implementation guide to connect retrieval, generation, and evaluation. For buyer-side evaluation, compare enterprise search […]
A RAG system does not retrieve whole documents. It retrieves chunks. That single fact makes chunking one of the highest-leverage decisions in the entire pipeline, because the way you split content decides what the retriever can find, what the model […]
Most teams that want an AI assistant do not have a spare AI engineering team. They have content: help articles, product manuals, policies, onboarding guides, member resources. The gap is turning that content into accurate, cited answers without building retrieval […]
A large language model is a strong writer and a quick thinker. It can draft, summarize, reason, and hold a natural conversation. What it cannot do on its own is know your latest policy, your current pricing, or the exact […]
RAG is not a single design. It is a family of RAG architecture patterns that combine retrieval, grounding, generation, evaluation, citations, permissions, and deployment into working systems. Many teams start with a simple retrieve-and-generate pipeline, then discover that production needs […]
Last Updated: August 4, 2026 Direct Answer: Are Open-Source LLMs Better Than Closed LLMs? Open-source LLMs are not universally better than closed LLMs, but they are often better when an organization needs deployment control, customization, data residency, lower vendor lock-in, […]
Direct Answer: What Are the Biggest RAG Challenges? The biggest RAG challenges are messy data ingestion, poor chunking, weak retrieval quality, hallucinations, missing citations, context window limits, security concerns, latency, and lack of reliable evaluation. Most RAG systems fail not […]
