A retrieval-grounded support agent that answers tier-1 tickets from your docs and ticket history — escalates the rest with full context.
Dental front desks are buried in repeat questions: insurance accepted, copay estimates for procedures, post-op care instructions, hours, location, prescriptions. A RAG support agent grounded in your insurance database, fee schedule, and post-op SOPs can deflect 50-60% of these — letting your team focus on in-chair patient experience.
General dentistry: AI answers 'do you take Delta Dental?' (queries verification API), gives copay estimates for cleanings/fillings, sends post-extraction care instructions on demand. Pediatric: AI handles parent FAQs, scheduling rules around school hours, and behavioral-management questions before the visit.
Help center articles, internal SOPs, past resolved tickets (last 12 months), product docs, FAQ. Quality matters more than volume — a clean 200-doc corpus beats a sloppy 2,000-doc one.
Split each doc into ~500-token chunks with metadata (source, last_updated, category). Embed with text-embedding-3-large. Store in Pinecone, Supabase pgvector, or use Chatbase if no-code.
On each query: retrieve top 5 chunks → pass to GPT-4 with strict instruction: 'Answer using ONLY the provided context. If the context doesn't answer the question, say so and offer to escalate. Cite sources by URL.'
Score the answer's confidence (low retrieval similarity, hedging language, missing entities mentioned in question). Below threshold → auto-escalate to human with the question + retrieved context + the agent's draft attempt.
Start with the help-widget on your site or one specific email alias. Don't start in your main support inbox. Watch resolution rate for 2 weeks before expanding.
Every answer ends with 'Was this helpful? 👍/👎'. Negative responses + escalated tickets feed back into the corpus as 'known gaps' for human reviewers to write new docs.
Schedule a re-embedding job that picks up new docs and resolved tickets. Stale corpus is the #1 reason RAG agents degrade.
Tuned for Dental. Use as-is or adapt to your voice.
You are a patient-services assistant for [Practice Name]. Answer patient questions using ONLY the provided context (insurance database, fee schedule, post-op SOPs, hours/location). NEVER provide clinical advice or diagnoses. For anything requiring clinical judgment, respond: 'That's a great question for our doctor. Want me to message the clinical team?' Cite sources by document name.
Yes, we accept [Plan Name]. Based on your plan, the typical patient copay for [procedure] runs about [estimated range] — but we'll verify your specific benefits and give you an exact figure before any treatment starts. [source: insurance database, last updated YYYY-MM-DD]
You are a support agent for [Company]. Answer the user's question using ONLY the context provided below. If the context does not answer the question or you're less than 90% confident, respond exactly with: 'ESCALATE: <one-sentence reason>'. Cite sources by their URL inline like [source: https://...]. Never invent product features, prices, or policies.
Context:
{{retrieved_chunks}}
Question: {{user_question}}
Answer:Escalate to human if ANY of: (a) top retrieved chunk similarity < 0.75, (b) answer contains 'I think', 'possibly', 'might be', (c) question references a specific account/order/case ID (always human-handled), (d) sentiment classifier scores user message as 'angry' or 'urgent'.
🚨 *Escalated: {{ticket_id}}*
📩 Question: {{user_question}}
🤖 Agent attempted: {{agent_draft}}
📚 Retrieved context: [link to top 5 chunks]
💡 Likely gap: {{detected_gap}}
👤 Assigned to: {{round_robin_agent}}Get one new AI workflow per week, tuned for Dental teams. Real templates, real ROI.
Do not deploy on workflows requiring human judgment, legal advice, medical advice, or financial advice. Do not deploy without a clean knowledge corpus — garbage in produces confidently wrong answers. Do not skip the human-in-loop review during the first month.
One practical AI tip per week. No fluff.
Get the full guide with niche templates and workflow imports.