Project 10 — Production insurance AI platform
Words made simple
A few useful meanings before you read the explanation.
- AI
- Software techniques for tasks such as recognizing patterns, understanding language or generating content.
- API
- A way for one piece of software to ask another for data or an action. A claims API might return the current status of a claim.
- Token
- A small piece of text processed by a model. It may be a whole word, part of a word, or punctuation.
More words from this lesson
- Vector
- An ordered list of numbers. An embedding is a vector used to represent content for tasks such as similarity search.
- RAG
- Find relevant information first, then give it to a model to help answer the question. The answer is only as reliable as the information and checks used.
- Grounding
- Connecting an answer to supplied evidence, such as a policy document or a verified database result.
- Durable
- Able to retain progress and recover across interruptions. Durable workflows require appropriate storage and retry behavior.
- Authorization
- Checking what that identity is allowed to read or do. Being logged in does not grant access to every record.
Requirements
- Combine policy RAG, claim status, guided intake, document processing, reviewed communication, staff escalation, and multi-tenant operations.
- Define supported tasks and explicit exclusions.
Architecture
Use section 27; start with one assistant plus controlled routes and add specialists only after evidence of benefit.
Technologies
Next.js, Node, MongoDB or PostgreSQL, chosen vector search, Redis/queue, approved models, LangGraph where needed, optional MCP/Python, eval/tracing platform.
Database design
Canonical customers/policies/claims, versioned documents/chunks, scoped conversations/memory, drafts/approvals, runs/receipts, outbox/audit.
API design
Authenticated conversational APIs, secure uploads/source reads, draft review/submit, durable run status/resume, and staff escalation.
AI design
Evaluated routing, grounded policy explanations, exact status tools, bounded information gathering, and meaningful abstention.
Security
Tenant/object isolation, prompt-injection defense through limited authority, minimized PII, exact approval, safe egress, and deletion propagation.
Evaluation
End-to-end customer tasks plus security, unknown evidence, OCR ambiguity, failure recovery, policy change, stale consent, and concurrent submissions.
Observability
Task success, review/escalation, latency/tokens/cost, source freshness, queue/approval age, tool denials, and operation reconciliation.
Deployment
Staging fixtures, limited rollout, region/data policy, capacity/quota testing, prompt/model/graph versioning, rollback, and operational runbooks.
Interview questions
- “Which steps are agentic?” Answer: interpretation and bounded information gathering.
- “Who decides claim approval?” Answer: authoritative rules and authorized review.
- “How do you prove completion?” Answer: a canonical receipt and audit trail.
Acceptance: Demonstrate a complete customer journey, a safe denied request, no-evidence abstention, a restarted approval workflow, and a duplicate/uncertain submission without duplicate claims. Explain every architecture component and why simpler alternatives were insufficient.
Can you explain it without the notes?
Project 10 — Production insurance AI platform
Use your own words. Explain an example and one limitation before checking the explanation.
Check your explanation
Requirements: Combine policy RAG, claim status, guided intake, document processing, reviewed communication, staff escalation, and multi-tenant operations. Define supported tasks and explicit exclusions.
Turn this concept into a clear answer.
Practice this conceptAdapted from 13_AI.MD · “Project 10 — Production insurance AI platform”. Examples are study fragments; framework behavior can depend on your version.