AI agent platformPrimustech, 2026 · Case study
Running an agentic AI platform
Infrastructure for the company's two AI products: an operations agent that answers from live building data, and a document assistant.
- AI products: an operations agent and a document assistant
- 2
- environments deployed the same way: dev, staging and production
- 3
- BMS devices in the demo building I built for the agents to query
- 2,014
A small working model of the real system. Press the buttons.
Question
from a facility manager
Agent team
Agno on Cloud Run
Data
live readings, documents
Gemini
Vertex AI, OpenRouter
Answer
traced with tokens and cost
- Load and latency tests on the agent API
- Token cost tracked per request
- Models compared on latency and cost
The problem
The agent and RAG services needed repeatable deploys, locked-down secrets and numbers on speed and cost.
What I did
- 1
Deployed and operated the multi-agent API and the RAG services on Cloud Run, with models on Vertex AI and OpenRouter.
- 2
Set up per-environment Cloud Build CI/CD, IAM service accounts, Secret Manager and shared-VPC networking for dev, staging and production.
- 3
Benchmarked the stack: load and latency tests of the agent API, per-request token cost tracking, and model comparisons on latency and cost.
Three environments deployed the same way, with building telemetry from the IoT platform feeding the agents.
Stack
- Cloud Run
- Vertex AI
- Cloud Build
- Secret Manager
- IAM
- VPC