General Solutions

Flexible, scalable AI storage solutions for general-purpose technical scenarios.

Accelerate AI model training

AI Large Model Training Acceleration Solution Based on Hecun Vector Database: Enables efficient retrieval and management of training data, significantly reducing training time and costs.

Core Features

  • Millisecond-level search across billions of vectors
  • Efficient Training Data Management
  • Incremental model weight management
  • Fine-tuning Data Precise Location

Use Cases

  • Large Language Model Training
  • Multimodal Model Training
  • Recommendation System Training
  • Computer Vision Models
Accelerate AI Model Training

Custom AI System Solutions

Delivers end-to-end customized services—from hardware selection and software configuration to system optimization—tailored to your specific business scenarios, helping enterprises rapidly build dedicated AI infrastructure.

Core Features

  • In-depth Requirements Analysis
  • Architecture Customization Design
  • Performance Optimization
  • Ongoing Technical Support

Use Cases

  • On-premises deployment
  • Hybrid Cloud Architecture
  • Edge computing scenarios
  • Special Industry Requirements
Custom AI System Solutions

Penglai RAG System

A one-stop RAG platform built on our self-developed vector database, HetuVDB. It connects enterprise knowledge bases with large language models to solve key deployment challenges: reducing hallucinations in general models and addressing concerns about uploading sensitive corporate data to the cloud. This delivers a secure, sovereign AI core capability for enterprises.

Core Features

  • Built on the proprietary HetuVDB, ensuring full data sovereignty.
  • Upload multi-format documents with zero setup; automatically chunk and vectorize.
  • Answer citation traceability with millisecond-level response speed
  • Deeply optimized for domestic GPUs such as MetaX

Use Cases

  • Financial Compliance Q&A
  • Government Data Security Search
  • Military Private Deployment
  • Enterprise Intelligent Customer Service
Penglai RAG System

Token Cost Reduction Strategy

Introduce HetuVDB vector cache between the business agent and large language models, implementing an intelligent routing strategy with multi-level semantic confidence scoring to prioritize caching with model fallback. This reduces token consumption by approximately 50% and transforms one-time computation costs into reusable knowledge assets.

Core Features

  • Zero-cost duplicate requests: reuse cached answers directly.
  • Similar requirements cost down by 50%+
  • Automatically capture new requirements and evolve the knowledge base on its own.
  • Multi-level confidence routing for intelligent compute allocation

Use Cases

  • High-Frequency Intelligent Customer Service
  • Scalable Agent Deployment
  • Enterprise Knowledge Reuse
  • Real-time interactive scenarios
Token Cost Reduction Strategy

Token Platform

The Penglai Data Store Token Production Platform operates around proprietary GPU computing power and large model inference capabilities. It unifies model services based on inference engines like vLLM into metered, billable APIs, using tokens as the billing and settlement unit to establish a complete operational loop from inference cost accounting to automatic deductions.

Core Features

  • Configure once to connect with OpenAI, vLLM, Claude, and more upstream providers.
  • Pay-per-token or fixed per-call pricing, with support for group-based pricing.
  • User self-registration, top-up, and API key creation
  • All top-ups and transactions are fully logged; both administrators and users can view detailed records.

Use Cases

  • Computing Power Operator
  • Model Service Commercialization
  • Enterprise API Gateway
  • AI Capability Open Platform
Token Platform

High-Performance Key-Value SSD Solution

Combines a proprietary key-value database with NVMe SSD hardware to deliver end-to-end performance optimization, unlocking flash potential and enabling low-latency, high-throughput storage for high-frequency data access scenarios.

Core Features

  • Hardware-software co-optimization
  • Unleash peak performance
  • Low latency, high throughput
  • Long-life design

Use Cases

  • High-frequency trading scenarios
  • Real-time Recommendation System
  • Cache Acceleration Layer
  • Hot data storage
High-performance key-value storage SSD solution