case-studies.cases.saas-startup-series-b-ai-architecture.subtitle
case-studies.cases.saas-startup-series-b-ai-architecture.client.description
Size: case-studies.cases.saas-startup-series-b-ai-architecture.client.size
case-studies.cases.saas-startup-series-b-ai-architecture.challenge.summary
Architecture built as a monolith wouldn't scale past 1,000 concurrent users — Series B required proof of 10,000+
No model evaluation framework: couldn't demonstrate AI accuracy, reliability, or improvement over time to investors
Critical security vulnerabilities in the RAG pipeline including prompt injection risks and data leakage between tenants
Zero SOC 2 compliance — a hard requirement for enterprise B2B customers and Series B institutional investors
Technical due diligence from three separate firms would examine architecture, security, and AI capabilities
12-month runway remaining: needed Series B closed within 6 months or face a down round
case-studies.cases.saas-startup-series-b-ai-architecture.solution.summary
case-studies.cases.saas-startup-series-b-ai-architecture.solution.approach
Migrated from monolith to event-driven microservices architecture. Implemented production-grade RAG with evaluation harness, vector store optimization, and multi-tenant isolation.
3 weeksBuilt model versioning and A/B testing framework. Implemented prompt injection defenses, data privacy controls, tenant isolation in the RAG pipeline, and comprehensive logging for audit trails.
5 weeksPrepared and achieved SOC 2 Type I certification. Built investor data room with complete technical documentation, architecture decision records, and performance benchmarks for due diligence.
4 weekscase-studies.cases.saas-startup-series-b-ai-architecture.results.summary
“case-studies.cases.saas-startup-series-b-ai-architecture.results.testimonial.quote”