AI Private Domain Large Model
Data/Security/Intelligence
Committed to providing innovative AI large model solutions for enterprises, helping them improve efficiency, reduce costs, and achieve sustainable development. We focus on private deployment and personalized functionality customization for enterprises. Our solutions prevent corporate data from leaking to the cloud, ensuring data security. These solutions are suitable for various business scenarios, including government agencies, corporate offices, telecom operators, and media, effectively preventing the leakage of internal sensitive data.
Helping enterprises enter the AI era
Gesner provides a one-stop AI service for enterprises and employees, including efficiency improvement, lead generation, marketing promotion, internal collaboration, business growth, and private domain operations. Qizhibao can be applied across various domains such as internal knowledge bases, customer service, sales consulting, marketing expertise, training, legal advice, and industry expertise.
Gesner is dedicated to your intelligent transformation
A one-stop AI solution, dedicated to enhancing all aspects of enterprise capabilities through AI.
Understanding enterprise knowledge
Connecting with business information
Executing user operations
Boost sales performance
Large model services
Private deployment
Business requirements analysis
Clarify business requirements and objectives to provide clear guidance for model selection and deployment. This includes an in-depth understanding of the business needs and how large model technology can be applied to specific business scenarios.
Model selection and adaptation
A large model doesn’t necessarily perform better just because it has more parameters. Analyze and compare the available models, and based on the specific circumstances of the enterprise, recommend a cost-effective model along with the matching server.
Data preparation and processing
Training and applying large models require extensive data support, including data collection, cleaning, labeling, and preprocessing, to ensure data quality and effectiveness. Pay attention to data privacy and security issues, ensuring that data is used in compliance with regulations.
Technical architecture and deployment
Enterprises need to build a technical architecture suitable for running large models and consider how to deploy the models to meet business needs. This includes formulating technical solutions, designing system architecture, configuring software and hardware resources, and developing deployment strategies.
Risk assessment and management
In the process of deploying large models, enterprises may face various risks, such as technical risks, data security risks, and business risks. Consulting services should provide risk assessment and management recommendations to help enterprises identify potential risks and develop corresponding mitigation strategies.
Prompt optimization
Understand the enterprise’s business processes to assist in designing professional and suitable prompts tailored to the business. Regularly review and update prompts to more precisely control the output of the large model, ensuring it better aligns with actual needs, and establish these prompts as fixed templates.
Custom Development
We provide a one-stop large model solution, including private model deployment and training, business system integration, and custom development.
Frequently Asked Questions
1. What is AI model training?
AI model training involves teaching an AI system to recognize patterns, make decisions, and improve over time by processing large datasets. During training, the model learns from examples to perform specific tasks, such as identifying anomalies, automating tasks, or analyzing data.
2. How long does it take to train an AI model?
The time required to train an AI model depends on various factors, including the complexity of the task, the size of the dataset, and the computational resources available. It can range from a few hours to several weeks, depending on these variables.
3. What kind of data is needed for AI model training?
AI models require large volumes of high-quality data relevant to the task they are being trained for. This data can include text, images, videos, or numerical data. The quality and quantity of the data are critical to the success of the model.