Inference

Inference is an advanced infrastructure platform designed specifically for engineering teams developing AI-native applications. Its primary function is to facilitate the deployment, monitoring, and training of large language models (LLMs) that are open-source, custom, or fine-tuned to operate at scale. This tool enables organizations to migrate from closed-source providers to an optimized infrastructure that drastically reduces latency and operational costs without sacrificing quality.

Model deployment capabilities are one of its fundamental pillars. Inference offers a high-performance hosting environment that allows for running models such as GLM-5, MiniMax, or GPT-OSS on public, private, or hybrid cloud infrastructures. Thanks to its technical architecture, teams can achieve 99.99% availability and significantly reduce production response times, ensuring that any server or machine processing requests maintains constant and reliable inference speeds.

To ensure optimal performance, the tool integrates a production-grade LLM observability system. This functionality enables tracking of every request, analyzing prompts, tool calls, and responses in real-time. Developers can monitor critical metrics such as p90 latency, token usage, and error rates. Key capabilities include:

• Production monitoring: Detailed tracking of every request path to identify provider behaviors and usage patterns.
• Automated fine-tuning: Workflows for fine-tuning custom models in minutes, adapting them to domain-specific tasks.
• Continuous evaluation: Comparing model variants against real production traces to detect regressions before deployment.
• Data curation: Automatically transforming production traces into high-signal training datasets.

Inference stands out for its focus on a private data flywheel, allowing the model to improve with every cycle by learning from end-user data. This is particularly useful for data extraction, classification, and AI agent applications that require higher precision than generic models.

Security is another key aspect, as the platform is SOC 2 Type II certified, guaranteeing full control and operational oversight across the entire tech stack. This makes it a robust solution for companies that need to scale their inference infrastructure while maintaining data privacy and sovereignty. With a focus on efficiency, it helps product teams achieve frontier-level performance with lower compute consumption.