Post by Devoteam | Google Cloud Partner

Traditional ML still beats agents at the actual math. The system works because it accepts that." That's Siddhesh Sreedar, AI Engineer at Devoteam in Stockholm, on the automated financial intelligence engine he built for Swedish markets. Instead of pretending agents can do everything, he designed around what they're actually good at. The pipelines do the heavy math. The agents interpret and explain. Five of them, orchestrated with Google's Agent Development Kit: research, quant, writer, critique, executive analyst. One exists purely to audit the others against the database before anything ships. Hallucination control built into the architecture, not bolted on. The whole thing runs serverless on Google Cloud. Cloud Scheduler kicks it off every Friday evening, Cloud Workflows coordinates the sequence, Cloud Run handles the ETL and agent jobs, and the finished report lands version-controlled in Cloud Storage. Nobody touches anything. Here's the part worth sitting with: institutions spend millions every year on market data feeds. This runs on public APIs. GDELT geopolitical signals, Sveriges riksbank monetary policy, Swedish macro data, market pricing. Output: a weekly intelligence brief on the OMXS30 that used to take an analyst days to assemble. It's a long read, and the paragraphs above are the skim version. The full write-up, architecture diagram included, is for when you're ready to build one yourself:https://lnkd.in/d9BWVbuq This is the same engineering Devoteam | Google Cloud Partner brings to clients deploying agentic AI at scale on Google Cloud.

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