SolarSense Language Data Engineering Platform - Building an Intelligent Multi-Scenario Annotation System

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SolarSense

Three-in-One SolarSense Platform System

A full-modal data collection platform, an all-category corpus engineering platform, and a cross-industry expert collaboration platform. The synergy of these three platforms builds a new generation of AI data infrastructure, enabling the flow and integration of data, intelligent processing, and the maximization of knowledge value.

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Cooperation Consultation

Three-in-One Integrated Platform

Three major platforms collaborate to create a new generation of AI data mining infrastructure,
achieving the circulation and integration of data, intelligent processing, and maximizing the value of knowledge.

Industry-Wide
Expert Collaboration

ChainOn brings together experts and senior labeling talents across multiple fields

· Precise expert collaboration for labeling
· Flexible realization of knowledge value
· Sustainable win-win through closed-loop ecosystem
· Efficient breakthrough of industry bottlenecks

Full Modal
Data Collection

Achieving orderly data flow and multi-dimensional integration

· Support for full-modal data
· Industry-level interface support
· High-efficiency data collection
· Comprehensive security protection

Full Data Types
Language Data Engineering

Multi-source, multi-modal, multi-dimensional data processing

· Comprehensive coverage of all data types
· Intelligent data engine
· High-quality assurance
· Quantitative improvement of quality and efficiency

Language Data Engineering Platform

Platform Features

Annotation Business Process Management

Data Resource and Product Management Platform

Intelligent Body Platform

Model Library

Knowledge Base

Build an efficient, standardized, and traceable annotation operating environment. Enhance annotation efficiency and quality through process-oriented and automated approaches, while reducing management costs.

As a data service portal for external clients, it not only provides the most fundamental data access and management functions, but also supports the use of JLW's ML/AI algorithm models for simple data processing. Clients can entrust JLW with one-click data annotation and processing services through the platform. Through intelligent analysis and knowledge extraction, it helps clients deeply understand and utilize the value of data, forming a personal knowledge base and intelligent system for each client.

Integrate an intelligent body/workflow low-code development engine, by incorporating state-of-the-art (SOTA) AI application frameworks, pre-trained models, and machine learning algorithms, to provide low-code development capabilities and user self-built knowledge base integration abilities, enabling both internal annotators and external clients to rapidly construct and deploy intelligent applications. This module encapsulates complex AI capabilities into easy-to-use components, significantly lowering the barrier to developing AI applications, and greatly improving the quality and efficiency of data annotation and product research and development.

Integrates various SOTA models and provides convenient training and deployment capabilities, enabling users to quickly apply the most advanced AI technologies. Incorporates efficient model fine-tuning features such as QLoRA, allowing users to customize models based on their own data, rapidly implement personalized AI applications, and validate datasets/large model performance on the SolarSense platform through methods like ablation experiments.

By converting structured and unstructured data into (graph) vectorized knowledge, intelligent semantic-based search and question-answering are achieved. The application of data+AI model integration technologies such as RAG and KAG enables various types of AI models to provide more accurate and reliable outputs based on the diverse data products managed by the platform, sourced from both internal and external users.

Technical Advantage

Full Data Mode Support

Supports the collection and processing of multimodal data such as text, images, audio, video, sensor data, etc., achieving comprehensive data coverage

Industry Expert Collaboration

Through a platform-based collaboration model, integrate the knowledge and experience of internal and external domain experts to form a synergistic mechanism of 'professional rules + manual verification,' ensuring the precision of handling complex tasks.

Intelligent Data Engine

Leveraging the intelligent middle platform and low-code development capabilities, integrating AI frameworks and RAG technology, deeply merging data, algorithms, and knowledge bases to drive the rapid construction and precise decision-making of intelligent applications.

Private Knowledge Base

Supports converting customer private data into vectorized knowledge, and combines technologies such as RAG to construct a proprietary knowledge system, providing secure and efficient internal data support for intelligent search, Q&A, and model training.

High-Quality Assurance

Construct a comprehensive quality control system encompassing standardized annotation processes, multi-level quality inspections, and model performance validation to ensure full traceability throughout the data processing workflow and guarantee that output results meet high industry standards.

Quantitative Improvement of Quality and Efficiency

Through process automation, algorithm assistance, and performance dashboards, shorten the data processing cycle to achieve continuous quantitative monitoring and optimization of production efficiency and quality indicators.