In today’s data-driven business landscape, the ability to access and extract insights from vast amounts of information is crucial for success. Traditional keyword-based search tools are becoming obsolete as enterprises demand more sophisticated solutions capable of understanding context, intent, and meaning. Enter MyGPT, an Enterprise Grade Search assistant powered by cutting-edge AI technologies, designed to address the challenges and complexities of modern enterprise search.
Problem Statement
The evolution of search technology, particularly with Generative AI and Large Language Models (LLMs), has introduced new possibilities like semantic search and query retrieval. However, existing open-source solutions pose several challenges:
- Manual Efforts for Data Loading/Training: Tedious manual processes are required for data loading and training in current solutions.
- Public LLM Data Privacy Issue: Utilizing public LLMs may compromise data privacy and security.
- UI Interaction Complexity: User interface interactions are often overly complex or poorly structured.
- Lack of Content Access Control: Limited control over permissions for accessing content.
- No History of Auditing and Logging: Absence of comprehensive auditing and logging mechanisms for data.
The MyGPT Solution
MyGPT is a game-changer in the realm of enterprise search, it is an Enterprise Grade Search assistant designed to cater to the needs of enterprise users. MyGPT engages in conversation with users and provides responses sourced from the enterprise’s own document and knowledge base. Leveraging the RAG approach, MyGPT stores data in vector format and conducts semantic search during response generation. Additionally, MyGPT incorporates permission checks to ensure that users only access content they are authorized to view. This approach offers a faster and more cost-effective alternative to traditional fine-tuning methods.
MyGPT is a game-changer in the realm of enterprise search, it is an Enterprise Grade Search assistant designed to cater to the needs of enterprise users. MyGPT engages in conversation with users and provides responses sourced from the enterprise’s own document and knowledge base. Leveraging the RAG approach, MyGPT stores data in vector format and conducts semantic search during response generation. Additionally, MyGPT incorporates permission checks to ensure that users only access content they are authorized to view. This approach offers a faster and more cost-effective alternative to traditional fine-tuning methods.
offering an array of features and functionalities tailored to meet the demands of enterprise users:
1. Crawler for Data Discovery
- MyGPT’s Crawler revolutionizes the way businesses discover and access data within their network drives.
- It leverages asynchronous multiprocessing and a sophisticated producer-worker code design.
- Automatically discovers and indexes relevant data sources from configured network drives such as SharePoint and OneDrive.
- Ensures real-time and accurate document discoverability.
- Offers seamless onboarding for clients by automatically configuring during the signup process.
- Scheduling capabilities allow organizations to define time-based discovery processes.
The insights and analytics provided by MyGPT’s Crawler offer valuable visibility into the file discovery process, empowering businesses with actionable intelligence to optimize data management strategies, identify trends, and make informed decisions regarding their information assets.
2. Multi-Tenant Sign-In and Single-Tenant Deployment
A. Multi-Tenant Sign-In:
- MyGPT offers a cost-effective solution with Multi-Tenant Sign-In, enabling multiple clients to share resources on the MyGPT platform.
- Streamlines onboarding and reduces infrastructure costs.
- Promotes quicker client integration through SAAS signup processes.
- Maintains data security and access control through RBAC mechanisms.
B. Single-Tenant Deployment:
- Provides clients with dedicated resources and infrastructure control.
- Ideal for organizations prioritizing data isolation, enhanced customization, and stringent compliance requirements.
- Enables tailored MyGPT configurations to specific requirements.
3. Private Embedder for Data Security – Utilizes private cloud networks for secure text-to-vector conversions with configurable parameters for optimization.
4. LLM for Question Answering – Hosted within private cloud networks, MyGPT’s LLM feature allows for controlled response generation with modularity and cost-effective deployment options.
5. Role-Based Access Control (RBAC) – Replicates existing permission trees to ensure compliance, protect sensitive data, and streamline access management.
6. Communication Channels – Seamless integration with Microsoft Teams Bot and Webchat UI enables easy interaction and context maintenance.
7. Kubernetes Deployment for Scalability – Cloud-native architecture ensures efficient scalability, cost-effectiveness, and easy maintenance through DevOps pipelines.
Business Values and Impact
- Efficiency: MyGPT automates tedious tasks, reducing manual efforts and increasing productivity.
- Security: Private cloud hosting and RBAC ensure data privacy and compliance with regulations. Cost-Effectiveness: Cloud-native deployment and scalable infrastructure optimize resource utilization and reduce operational costs.
- Customizability: Configurable parameters and deployment options allow for tailoring MyGPT to specific enterprise requirements.
- User Experience: Streamlined UI/UX and seamless integration with communication channels enhance user satisfaction and engagement
Conclusion MyGPT represents a paradigm shift in enterprise search, leveraging AI advancements to deliver a comprehensive, secure, and efficient solution. With its range of features addressing data privacy, access control, automation, and scalability, MyGPT empowers businesses to unlock the full potential of their data assets and drive informed decision-making.
