Core Engine vs AI Cortex: when to add AI
Not every startup needs RAG on day one. This guide explains when serverless SaaS is enough and when owned Bedrock AI becomes the moat.
Last updated: 2026-06-13
Core Engine vs AI Cortex
The Core Engine is fixed-price serverless SaaS: auth, APIs, payments, admin in your AWS account. The AI Cortex adds Bedrock RAG, document ingestion, and guardrails in the same account. Smart Trady uses both on one live B2B product.
Start with Core Engine when
Your milestone is first paying customers and standard web workflows without document-grounded answers.
You need Stripe, Cognito, and admin before you need vector search.
AI is a roadmap item, not the investor thesis today.
Add AI Cortex when
Proprietary documents, SOPs, or curriculum are the product moat.
Customers ask how answers are grounded and where data is stored.
Wrapper APIs create compliance blockers in enterprise pilots.
Buying both together
Full AI SaaS tier builds backend and RAG from greenfield.
AI Drop-In tier adds RAG plus React component to an existing Core Engine app.
See the AI startups founder page for positioning language.
Sequencing Core Engine before AI
Most teams need stable auth, billing, and APIs before document-grounded answers matter to customers. Ship the revenue path first unless RAG is the entire thesis.
AI Drop-In exists when Core Engine is already live and you are adding copilot or search without a greenfield rewrite.
Budgeting two products in one round
Full AI SaaS tier covers greenfield backend plus RAG when both are gating risks. Otherwise split across fundraising and post-close budgets with clear milestones.
Published tiers on product pages help you model spend before the demo call. We confirm EUR price on scope follow-up.