Multi-Modal AI Search Platform

AWS-native multi-modal search implementation

What it is

Reference architecture + implementation services on foundation models + vector retrieval, with hybrid retrieval as the production default.

Make money for the customer

  1. 15-50% conversion lift on discovery-driven SaaS/e-comm (Bain, McKinsey, Algolia benchmarks)
  2. Revenue from previously-unfindable long-tail inventory now reachable
  3. Premium tier and pricing power from “AI-powered search” as a customer-facing feature

Save money for the customer

  1. Avoided $1-2M/year DIY search team vs $60K-$150K implementation engagement
  2. Reduced support load + self-service rate uplift
  3. AWS spend efficiency built in (hybrid retrieval, smart foundation-model and retrieval routing); no third-party vendor fees

Customer proofs

Yaapt, Legal-tech, Real-estate intelligence

AWS service surface

Capability: foundation models, embeddings, knowledge bases, vector retrieval, document intelligence, serverless compute, object storage

AWS strategic angle

Drives foundation-model + vector-retrieval + knowledge-base consumption