Our Services
End-to-end AI content generation solutions, from prompt optimization to model training, covering the full pipeline.
Agent Prompt Self-Tuning
Traditional prompt engineering relies on manual experience — slow and hard to converge. Our self-tuning system uses automated evaluation and multi-round iteration to bring Agent prompts to production quality fast.
Automated Quality Assessment
Multiple Judge Agents score from different dimensions (expertise, readability, style consistency), replacing manual review.
Closed-Loop Iteration
Evaluation results feed back into prompt generation automatically. The system keeps optimizing until convergence criteria are met.
Traceable Versioning
Every iteration's prompts, generation results, and scores are fully recorded. Any version can be traced and compared.
Ideal for: Teams that need to quickly build high-quality writing Agents, especially brands and media with strict content style requirements.
Agent Distillation
Extract writing styles and patterns from existing high-quality content, distilled into lightweight Agent definition files. No model retraining needed — get AI writers with highly consistent style.
Multi-Dimension Analysis
Deep analysis of reference articles across 9 dimensions — headlines, structure, tone, vocabulary — to extract reusable writing patterns.
Portable Delivery
Distillation results are self-contained JSON files, loadable across different platforms and systems with zero conversion.
RAG Material Enhancement
Combined with knowledge base retrieval, inject real-time materials into Agents, solving the core problem of 'style matches but content is empty'.
Ideal for: Content teams and MCN agencies that own quality content assets and want to scale author styles.
LLM SFT / LoRA Training
AdvancedWhen prompt-level optimization isn't enough, we offer professional model fine-tuning services. Deep customization through domain data for precise capability control.
Domain Data Construction
Build high-quality training datasets from existing content assets and industry knowledge, ensuring fine-tuning effectiveness.
Full SFT Fine-Tuning
Full-parameter supervised fine-tuning for best domain adaptation. Ideal for scenarios with the highest quality requirements.
Lightweight LoRA Adaptation
Low-rank adaptation with minimal training cost and zero inference overhead. Optimal balance between effectiveness and cost.
Ideal for: Enterprise clients with ultimate quality requirements who need deep model capability customization.