Integrating GPT-4 into a business product is not the same as adding a chat widget. Production systems need retrieval, guardrails, evaluation, and observability. These are the patterns we deploy for clients — and on our own products.
Four integration patterns that ship
1. RAG over private documents
Ground answers in your PDFs, tickets, policies, or product catalog. Used for internal copilots, support assistants, and sales enablement.
2. Structured extraction
Turn unstructured inputs into JSON for downstream workflows — invoices, contracts, intake forms, and CRM updates.
3. Agentic workflows
Multi-step tasks with tool calls — book meetings, update records, trigger approvals — with human checkpoints.
4. Embedded copilots in existing UX
Context-aware assistance inside dashboards, editors, and CRMs — not a separate chat page users forget exists.
Guardrails every production integration needs
- Prompt versioning and evaluation harness
- PII redaction and access control
- Fallback when model or retrieval fails
- Per-request logging and cost caps
Real examples from the field
Support deflection copilot: 40% tier-1 reduction when grounded in help center + ticket history. Sales proposal assistant: draft SOW sections from CRM + past deals. Document intake: extract fields from uploaded PDFs into ERP with human review queue.