Blog

Implementing OpenAI's powerful models in customer-facing roles comes with risks. This guide breaks down the essential OpenAI safety best practices for moderation, accuracy, and data security, and shows you how to implement them without a dedicated engineering team.

Thinking of building with OpenAI SDKs? This guide covers everything you need to know, from basic setup and key features to the hidden costs of building a production-ready AI solution yourself. Discover a faster, more efficient alternative.

The OpenAI Threads API offers powerful tools for building conversational AI, but managing persistent conversations can be complex. This guide breaks down how threads work, their limitations, and why a managed platform might be a better solution for your support team.

OpenAI Trace Grading offers deep insights for developers building AI agents, but it's complex. Learn what it is and explore a more practical, business-friendly alternative for evaluating your support AI with confidence.

Building an AI assistant? This guide breaks down the OpenAI Vector Stores API Reference, covering everything from creating stores to managing files and running searches.

Thinking about using OpenAI Vector Stores for your AI support agent? This guide breaks down the pros, cons, and hidden complexities of building with them directly. Learn about the challenges of latency, cost, and control, and discover how a self-serve platform can provide a more powerful, integrated solution in minutes.

Thinking about implementing Ada? This guide breaks down the complete Ada chat installation process, from embedding scripts to configuring complex helpdesk handoffs, and explores a more streamlined alternative for modern support teams.

Thinking about using Ada for AI chat onboarding? This guide covers everything you need to know about Ada's features, setup complexity, and enterprise pricing model before you commit.

Thinking about using the Ada Coaching Feature? Our 2025 overview breaks down its four-step process, reveals the potential drawbacks in setup time and cost, and shows why a simpler, more transparent AI platform might be a better fit for your team.