- GPT-4, Claude or open-source models per use case
- Retrieval-augmented generation (RAG) against your knowledge base
- Multi-channel: web, WhatsApp, Slack, Teams, SMS
- Human handoff with full context
- Real-time analytics and prompt tuning
Where AI chatbots ship real ROI
Best-fit use cases: 24/7 lead qualification (30–60 percent higher inbound conversion), Tier-1 support deflection (40–70 percent ticket reduction), booking/scheduling assistants, and onboarding new customers.
RAG vs fine-tuning — how we advise
For 90 percent of business chatbots, retrieval-augmented generation (RAG) beats fine-tuning. It's faster to deploy, easier to update, and cheaper to run. We only recommend fine-tuning for very specific voice or format requirements.
What's included
Frequently asked questions
Yes — HubSpot, Salesforce, Pipedrive, Zoho and custom CRMs. Chat data flows in as structured lead objects with full conversation transcripts.
Strict RAG grounding (never let the model answer without retrieved context), confidence thresholds, and human-review triggers on low-confidence responses.
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