YC-backed AI Startup – AI Infrastructure & Tooling

YC-backed AI Startup – AI Infrastructure & Tooling

A YC-backed AI startup in Hong Kong needed to turn a fast-moving set of AI ideas and experiments into reliable, observable production infrastructure. Webomage helped connect multiple AI tools and LLM providers into a cohesive, debuggable platform the team could safely evolve.

Context & Challenges

• Multiple AI services and LLM providers in play, each with different APIs and operational characteristics.
• Rapid iteration on features, but limited time to keep infrastructure, observability, and deployment practices in sync.
• Need for advanced debugging and experimentation without breaking production traffic.
• Early-stage team requiring patterns they could own going forward, not a black-box setup.

What We Did

• Designed and implemented a production-ready AI infrastructure around existing tools and code.
• Integrated several LLM providers and AI tools behind clear interfaces for easier routing and experimentation.
• Introduced orchestration patterns (e.g. LangChain-style flows) that made it easier to plug in new tools and prompts.
• Set up CI/CD and environment separation, so experiments could be rolled out gradually and safely.
• Improved logging and tracing around AI calls to make debugging and performance tuning much faster.

Outcomes

• A more stable, observable AI platform that could support both experiments and production traffic.
• Faster iteration cycles, with the ability to test and compare different tools and providers.
• Reduced operational risk by standardising deployment and rollback patterns.
• Clear documentation and handover so the startup’s own team could extend the system.

Relevant Capabilities

• Multi-provider LLM integrations and routing.
• AI/LLM orchestration and evaluation patterns.
• CI/CD, environments, and gradual rollout strategies for AI services.
• Observability and debugging for AI-heavy systems.

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