Enterprise AI Tooling

Ozzie: AI Assistant SaaS Engineered for Streaming Latency and Multi-Model Reliability

Streaming LLM infrastructure with multi-model routing and 99.97% uptime

Client: Ozzie

Ozzie: AI Assistant SaaS Engineered for Streaming Latency and Multi-Model Reliability

The Challenge

What Ozzie Was Facing

Ozzie is a conversational AI assistant embedded in US enterprise workflows. The hard engineering problem was not calling an LLM — it was building the infrastructure layer that made the product reliable and cost-efficient at scale: streaming responses without connection timeouts, intelligent routing between model providers by cost and latency, conversation context storage that did not blow up database spend, and budget guardrails that did not break user experience.

The Solution

What We Built

We built an API-first platform on AWS Lambda and API Gateway with WebSocket support for streaming. A model router service selected providers in real time based on latency and per-token cost metrics logged to DynamoDB. Conversation history was compressed to S3 with a retrieval index in Redis, keeping context retrieval under 40ms. The full infrastructure was defined in CDK with blue-green deployments for zero-downtime model integration updates.

Ozzie: AI Assistant SaaS Engineered for Streaming Latency and Multi-Model Reliability – solution

Results

Measurable Outcomes

✓First-token streaming latency under 320ms from API call to client-side render

✓Model routing cut per-conversation inference cost by 38% with no quality degradation

✓99.97% uptime across 6 months post-launch including model provider outage incidents

Let's build something great together — get in touch

Ready for Similar Results?

Start Your SaaS Journey