Choosing an LLM for a Customer-Facing Messaging Agent
Learn how to evaluate an LLM for a customer-facing messaging agent based on response quality, speed, cost, safety, tools, memory and escalation needs.
Connecting LLMs to a real blue-bubble number, and what it takes to run a conversational agent in production.
Learn how to evaluate an LLM for a customer-facing messaging agent based on response quality, speed, cost, safety, tools, memory and escalation needs.
Learn how to prepare, structure, test and maintain business knowledge so an iMessage AI agent gives accurate answers and knows when not to guess.
Design a reliable human handoff for an iMessage AI agent with clear triggers, ownership, context transfer, CRM routing and safe conversation recovery.
Learn how to plan, configure, test and launch a no-code iMessage AI agent using business knowledge, clear boundaries and reliable human handoff.
Build an AI agent for iMessage without code. Choose a model, add instructions and business knowledge, then deploy the agent on an iMessage number.
Learn how to send and receive iMessages programmatically using an API, webhooks and reliable event handling, from the first outbound message to reply automation.
Learn how an iMessage API works, how it differs from Apple Messages tools and SMS APIs, and what to evaluate before building two-way messaging.
Grab an API key and spin up a sandbox number in minutes, or talk to us about isolated, enterprise-grade infrastructure for agents at scale.