Surge AI

Surge AI is a platform designed for building and refining large language models (LLMs) using rich, human-annotated data. It offers end-to-end solutions for data collection, labeling, and fine-tuning through supervised methods and reinforcement learning from human feedback (RLHF). The platform is aimed at enterprises and research institutions that require private, secure, and scalable data workflows to train and improve AI systems.

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What Surge AI Provides

• A governance-first RLHF and SFT (Supervised Fine-Tuning) workflow to optimize model performance with human-guided data.
• Rich data pipelines for annotation, evaluation, and feedback, enabling high-quality supervision across diverse use cases.
• Managed services and expert data teams that collaborate with you throughout the entire lifecycle—from data labeling to model evaluation.
• API & SDK support for direct integration with your existing infrastructure and pipelines.
• 24/7 global support and enterprise-grade security (SOC II) to ensure private, secure, and trusted operations.
• A robust ecosystem of customers and partners across tech, academia, and industry, showcasing real-world deployments and results.

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How Surge AI Helps Businesses

• Accelerates the creation of high-quality training data for LLMs and other AI models.
• Enables rigorous human evaluation and benchmarking to validate model behavior and safety.
• Supports post-training reinforcement learning workflows to continually improve models with human feedback.
• Provides managed services to handle complex data projects, reducing time-to-market and operational risk.
• Delivers privacy and security assurances suitable for large enterprises and sensitive domains.

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Use Cases

• Adversarial Data Labeling
• Content Moderation
• Search Ranking
• Reinforcement Learning with Human Feedback Training
• Next-Gen Command LLMs
• Case studies across customers like Microsoft, Nvidia, NYU, Hugging Face, Reddit, and many more.

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How It Works

1. Integrate Surge AI via API or SDK into your data and model training pipelines.
2. Define tasks, labels, and evaluation criteria; deploy human-in-the-loop workflows for supervision.
3. Collect annotated data, perform supervised fine-tuning (SFT), and apply RLHF to optimize model behavior.
4. Run evaluations, monitor benchmarks, and iterate with your expert data team.

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Core Features

• Private, secure, SOC II-compliant enterprise platform
• API & SDK for seamless integration with existing workflows
• Managed service with expert data teams guiding the process
• Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF)
• Rich human evaluation, custom benchmarks, and case studies
• Large-scale, multi-use-case data labeling and annotation capabilities
• 24/7 global support and enterprise-grade reliability
• Proven impact across leading organizations and research institutions