Voice AI agent development that answers in under a second and knows when to hand off

1. Problem. A support organisation carried a heavy tier-1 queue of repetitive, well-understood questions. Hold times drove most of the dissatisfaction, the queue peaked exactly when staffing was hardest, and conventional IVR menus just pushed callers to press 0.

2. Solution. A real-time voice layer on GCP: streaming speech recognition, retrieval grounded in the client's knowledge base, and a policy layer deciding what the agent may resolve alone. The loop stays under 1 second at the caller's ear; low confidence or asking for a person triggers a warm transfer with the transcript.

1. Problem. A fast-scaling US e-commerce brand had support infrastructure buckling under volume. Response times were slipping, agents were overwhelmed, and brand content across 5 social platforms was inconsistent. Hiring more people was the expensive fix.

2. Solution. An autonomous support platform across Instagram, TikTok, Facebook, LinkedIn, X, chat and email. Claude handles incoming queries with knowledge-grounded reasoning, processing refunds, routing tickets and resolving most issues without escalation. A sentiment layer escalates only what needs human judgment.

1. Problem. 14 disconnected sales tools, no consistent lead qualification and shaky CRM data. Revenue was slipping through gaps that no single person could track across multiple regions at once.

2. Solution. A round-the-clock revenue layer on n8n and LangGraph. Real-time lead qualification, automatic CRM enrichment, personalized outreach across email and LinkedIn, predictive deal health scoring, and live pipeline reports delivered to leadership with no sales ops in the loop.