FLORA needed to provide professional creative teams with fast, reliable AI workflows for text, image, and video while protecting clients' proprietary branding and unreleased assets. Third-party model aggregators struggled with peak traffic, and the team required real-time image prototyping, flexible capacity, and enterprise data controls.
Reported impact
FLORA reduced image-generation latency and model operating expenses, improved reliability, doubled visual-generation volume in three months, and secured enterprise deals with strict compliance requirements.
FLORA moved its AI workloads from third-party model aggregators directly to Google after aggregators struggled with peak traffic, latency, and reliability. Its node-based creative canvas brings text, image, and video work into one professional workflow, and an intent-based router selects the model for each task. Agents built with Gemini 3.7 Flash balance output quality, cost, and latency; Gemini models power most workflows, with Nano Banana supporting image generation and 4K upscaling, Gemini Omni supporting video generation and editing, and Flash Lite also used in creative workflows. Google Cloud enterprise data controls address privacy and compliance requirements for proprietary client assets. The story names BigQuery as a Google Data Cloud service, but its role and the platform's ingestion, storage, or external interfaces are not described, so no data pipeline is inferred. Direct access to Google reduced latency and operating costs.
Creative tasks spanning text, images, and video enter FLORA's node-based canvas. Its intent-based routing system selects a model, and agents built with Gemini 3.7 Flash balance quality, cost, and latency; outputs are generated through Gemini models such as Nano Banana, Gemini Omni, and Flash Lite and returned to creative workflows. The page mentions BigQuery but does not establish its role in this path or describe storage.
Decreases image generation latency by 26%
Doubles total visual generation volume in just three months
Google AI models are now involved in more than 70% of assets generated on FLORA.
Reduces model operational expenses by 38%
The FLORA platform uses an intelligent routing system that automatically assigns the optimal model based on user intent.
agents built with Gemini 3.7 Flash balance quality, cost, and latency for the specific task
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