AI Engineering

AI Engineering on Azure & Google Cloud

Build useful AI systems that fit into your existing cloud environment, data and security model.

Discuss an AI Project

Practical AI, built to operate

Opsvane focuses on useful business applications and the engineering required to deploy them. The work goes beyond a demo: cloud infrastructure, access control, integration, monitoring and operating cost are part of the design.

Knowledge & Search

  • RAG systems
  • Enterprise knowledge assistants
  • Semantic search
  • Document Q&A

Workflow Automation

  • Document extraction and classification
  • Summarization
  • AI assisted workflows
  • Agent based automation

AI Application Infrastructure

  • Azure AI and Microsoft Foundry
  • Google Vertex AI
  • Model integrations and APIs
  • Containerized AI workloads

Production Architecture

  • IAM, network design and secrets
  • Observability and deployment
  • Scaling and cost controls
  • Secure cloud integration

AI Prototype Sprint

A focused engagement to validate a worthwhile use case and build the first working version. Scope and production readiness depend on the problem.

1. Clarify

Understand the use case, data and constraints.

2. Build

Design the architecture and develop a working prototype.

3. Plan

Deploy appropriately and define the production roadmap and operating cost.

Validate an AI idea