diff --git a/content/services/ai-agents.mdx b/content/services/ai-agents.mdx index 5510768..0aed5ad 100644 --- a/content/services/ai-agents.mdx +++ b/content/services/ai-agents.mdx @@ -38,7 +38,7 @@ relatedExpertise: - backend-development - ai-security faqs: - - question: "What's the difference between an AI agent and a chatbot?" + - question: "What is the difference between an AI agent and a chatbot?" answer: "Chatbots respond to queries. Agents take action. An AI agent can research information, update databases, send emails, schedule meetings, and execute multi-step workflows autonomously—not just suggest what you should do." - question: "How do you ensure AI agents are safe in production?" answer: "We implement multiple safety layers: action constraints that limit what agents can do, sandboxed execution environments, approval workflows for sensitive actions, comprehensive logging, and rollback capabilities when things go wrong." @@ -46,6 +46,8 @@ faqs: answer: "Yes. Our engineers specialize in building integration layers that connect modern AI capabilities with existing enterprise systems—even those without modern APIs." - question: "How long until we have a working agent?" answer: "Most clients see a working prototype within the first week. Production deployment typically takes 2-4 weeks, depending on the complexity of your workflows and integration requirements." + - question: "What kind of tasks are best suited for AI agents?" + answer: "AI agents excel at tasks that are repetitive but require judgment—research and data gathering, document processing, customer inquiry routing, lead qualification, and multi-system workflows. If a task involves multiple steps, uses several tools, and currently requires human decision-making at each stage, it's a strong candidate for an AI agent." cta: title: "Ready to Deploy AI Agents?" description: "Talk to our team about automating your complex workflows with AI agents. We'll show you what's possible—and what's production-ready today."