Omni — AI Integration Architecture
AI integration architecture for Omni, LgMAR's maritime CRM and communication platform. This case study is intentionally sanitized: it covers architecture and approach only, with abstract diagrams in place of company material.
What we were solving
Context & problem
Maritime communication workflows contain unstructured operational information — vessels, cargo, ports, statuses, follow-ups, counterparties. That meaning lives inside free-form messages, where it stays invisible to the operational systems teams rely on.
The goal: a modular AI integration foundation for extracting operational meaning from communication workflows, without coupling domain logic to any single model or provider.
How we approached it
Solution
AI integration pipelines for classification, entity extraction, workflow automation, and structured prompt-action execution. AI outputs are structured and validated before any tool execution, so automation stays inside clear trust boundaries.
The architecture separates domain logic from orchestration and provider concerns, with observability and structured logging throughout, operator-trust UI surfaces for review, and modular provider flexibility as models evolve.
Impact
Outcomes
- - A scalable AI integration direction for operational CRM workflows.
- - Domain logic separated from orchestration and provider concerns.
- - AI outputs structured before tool execution.
- - Observability and structured logging for AI-assisted workflows.
- - Operator-trust UI surfaces for reviewing AI-driven actions.
