01
Chatbot Strategy and Design
Scope which conversations a bot should own, which it should route to people, and which it should never touch at all. Intent maps, tone rules, and escalation paths get set before any platform pick or AI chatbot development starts. Support deflection targets come with baselines your own team accepts first.
02
Ground your assistant in approved content with retrieval augmented generation. The LLM answers from your own files rather than its imagination. Knowledge sources get versioned and audited as they change. Hallucination testing runs against your hardest real transcripts well before launch day.
03
Voice AI and IVR Consulting
Replace old phone trees with voice assistants and NLU that get callers the first time. IVR redesign covers routing, identity checks, and a smooth human handoff path. Containment and abandonment metrics decide the design, and callers stop hitting zero in frustration.
04
Extend assistants past answers into action: order changes, claim intakes, appointment moves. Agents work under hard limits with human-in-the-loop checkpoints on money and account changes. Each action lands in an audit trail your compliance team can replay at will.
05
Conversational AI Governance
Set the guardrails, evaluation layer, and review pace before customers meet the bot. Policies cover data handling, topic limits, escalation triggers, and incident response plans. Governance rides along the whole life of the bot, keeping it defensible as traffic and rules change.
06
Wire each chat into Salesforce, ServiceNow, and your contact center stack through API integration. Context follows the customer between the bot, the agent, MS Teams, and WhatsApp channels. Tickets, transcripts, and outcomes land right where your teams already work, with nothing retyped by hand.