About
Launch Control, a US real estate text-messaging and lead-engagement platform, modernized its core infrastructure by introducing a Python microservice AI layer alongside a containerized and security-hardened legacy C# backend.
Challenge, approach, and impact
Modular AI Microservices Monorepo
Designed and architected three specialized FastAPI microservices to sit beside the C# stack: AIReply, AITemplates, FOMO Tracker for various functionalities such as lead classification, generating compliant batch outreach copy, and providing geospatial analytics.
Hard Integration & Low-Churn Architecture
Implemented seamless bridge interfaces for Python services to interact with the legacy C# backend via Cloud Pub/Sub and async API boundaries with minimal modification to the existing C# codebase.
Security Hardening & Containerization
Fully containerized the C# platform with Docker, refactored configuration handling to extract all secrets out of git into dynamic environment variables and Google Secret Manager to enhance security.
Cloud-Native CI/CD Pipeline
Established an automated deployment agreement using Cloud Build, Skaffold, and Terraform for infrastructure and triggers on Google Cloud Run, backed by PR checks in GitHub Actions to streamline deployment processes.
How we built
Testimonials
Lead Engineer, CTO @ DataDrill
DataDrill
“By decoupling AI innovation into a dedicated Python microservices monorepo and hardening the existing C# core platform, we brought cutting-edge LLM and geospatial capabilities to production without disrupting existing operations. Securing secrets, containerizing legacy debt, and establishing clean Cloud Run pipelines turned a fragile setup into a scalable, enterprise-grade messaging ecosystem.“
Team structure
Client team
Peter
CEO
Project stakeholder
The client stakeholders were working closely with the team at DataDrill
Agency team
1 x System Architect
Governance
