Engineering

Why We Bet on the Google Unified Stack

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Luke Needham
8 min read
QFA // ENGINEERING

When building enterprise-grade AI, you need infrastructure that doesn't blink. That's why we chose Google.

Gemini offers an industry-leading context window. That's not just a spec; it's a fundamental change in capability. It means an agent can read your entire codebase, your entire customer history, or your entire legal archive in a single prompt.

The Unified Advantage

Google's stack isn't just about one model. It's about how everything connects:

  • Vertex AI — Model hosting, fine-tuning, and serving at scale
  • Cloud Run — Serverless compute that scales to zero
  • BigQuery — Petabyte-scale analytics with built-in ML
  • Firebase — Real-time databases and authentication

When your entire stack speaks the same language, you eliminate the integration tax that kills most AI projects.

Why Not OpenAI?

OpenAI builds incredible models. But models are just one piece of the puzzle. When you need to deploy agents at enterprise scale, you need:

  • Reliable, low-latency infrastructure
  • Data residency and compliance controls
  • Seamless integration with databases, storage, and compute
  • Monitoring, logging, and observability built in

Google provides all of this in a single, unified platform. That's the difference between a demo and a production system.

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Written by Luke Needham

Founder at Quantum Flow Automation — building AI systems that work.

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