LōD Technologies offers a smarter, safer way to run AI.

Vancouver startup LōD Technologies launched CLōD, an inference-layer platform that routes AI requests to balance cost, latency and governance; the company plans to roll out an energy-optimization feature and took part in Google’s AI for Energy accelerator.

Canada has low business adoption of AI despite large projected gains, and energy and governance concerns are commonly cited as barriers. Vancouver-based LōD Technologies started in 2021 optimizing data centre energy in deregulated markets and has since adapted that expertise to AI workloads. The company launched CLōD earlier this year to act at the inference layer as a gateway between organisations and AI models. LōD positions the platform to give users rules-based control over routing, cost, latency, model behaviour and governance. What is known: - CLōD operates at the inference layer and can route requests to third-party hosted models (reported examples include OpenAI, Anthropic and Google) or to on-premises models. - LōD began in 2021 with tools for data centre energy management and reports serving more than 100 sites in Texas and internationally. - The platform lets users define rules about where data can be routed, blocks restricted information, logs activity for audits, and offers private, isolated environments for sensitive workloads. - An energy-optimization capability, built on the company’s data centre expertise and designed to respond to real-time energy pricing, is reported to be coming online soon. - LōD was selected for Google’s inaugural AI for Energy accelerator and worked with Google teams over a four-month program. - The company says it undergoes annual SOC 2 Type 2 audits, grew from eight to 18 employees in the past year, and has a funding round planned for 2026. Summary: CLōD aims to give organisations predictable control over AI requests by combining cost, latency and governance controls with logging and isolated environments, which is presented as particularly relevant for regulated sectors. The company plans to deploy its energy-optimization feature in the near term and has recently completed a collaboration through Google’s AI for Energy accelerator.