HongKong,China, Nov. 12, 2026 (GLOBE NEWSWIRE) — For forward-deployed engineering (FDE) teams, choosing an AI model is only the beginning. Once a customer workflow is running, the team may need to change models because of latency, capability, cost or policy requirements.

The difficult part is changing the model without losing control of the workflow.

Sidrune AI serves 100+ business customers and has 40,000+ registered users. It provides multi-model access for teams deploying AI into live products and customer operations. Its Model Plaza lists more than 100 model-and-route listings, including GPT, Claude, Gemini, DeepSeek and Kimi.

For FDE teams, the question is: when a model or route no longer fits the customer’s needs, can the team compare another option and switch without rebuilding the entire deployment process?

Sidrune AI’s platform is designed around that multi-model workflow. Teams can evaluate different model routes, monitor usage and billing, and choose another model as the technical or commercial requirements change.

Sidrune AI’s GPT routes

“For FDE teams, model access is only the first step,” said Sean, co-founder of Sidrune AI. “The real challenge is keeping a customer workflow usable when the required model, route or cost conditions change. Our aim is to make multi-model access easier to compare and manage in production.”

The platform states that it processes more than 3 trillion tokens per month on average. The figure refers to aggregate platform usage.

For GPT-6.1 Sol, the Model Plaza lists GPT-Azure at 60% below the displayed base price and GPT-OpenAI Official at 55% below it.

Sidrune AI’s roadmap focuses on more flexible routing, stronger privacy controls and support for integrating AI into existing workflows. These developments are intended to help FDE teams move from an initial model test to a more manageable multi-model production setup.


Axo Wang,axo.wang@fluxiontech.ai

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