Predis.ai

Solution

Securing research-grade GPUs required enduring long approval queues, forcing the lean engineering team to rely on consumer-grade hardware. Securing research-grade GPUs required enduring long approval queues, forcing the lean engineering team to rely on consumer-grade hardware. This created major latency bottlenecks and challenging generation queues. The team had to manually over-provision their… At the core of Predis.ai architecture is a sophisticated ‘agentic swarm’ orchestrated on the , wherein models communicate dynamically instead of running in silos. Gemini 3.1 Pro acts as the baseline reasoning engine, generating context that passes to Nano… Key components include GPUs supports a core part of the deployed AI and data workflow described in the customer story; Gemini Enterprise Agent Platform coordinates multi-agent workflows, tool calling, and governed automation across the application; Gemini 3.1 Pro provides the reasoning or generation layer used for classification.

Data flow

Securing research-grade GPUs required enduring long approval queues, forcing the lean engineering team to rely on consumer-grade hardware. This created major latency bottlenecks and challenging generation queues. The team had to manually over-provision their architecture to survive unpredictable traffic spikes. This defensive strategy burned through two to three times their current server budget and diverted critical engineering focus away from product development.