HealthTech80-200 employees14 weeks

Case Study on Private GPT (GDPR & SOC2)

Project Overview: Project Title: Private GPT Development Client Industry: Confidential Introduction: Our team, over at Kryoverse took on a venture to create a version of GPT (Generative Pre trained Transformer) for a sig

Challenge

Project Overview: Project Title: Private GPT Development Client Industry: Confidential Introduction: Our team, over at Kryoverse took on a venture to create a version of GPT (Generative Pre trained Transformer) for a significant client. The main goal was to design a question and answer system resembling ChatGPT focusing on maintaining top notch data security in alignment with SOC 2 and GDPR regulations. Client Background: The client, a player in the Finance sector aimed to leverage AI driven con.

Engagement Context

Client
Kryoverse Client
Team Composition
1 AI Lead, 2 Full-stack Engineers, 1 DevOps Engineer
Confidentiality
Anonymized case details

Approach

Their top priority revolved around safeguarding information leading them to explore a GPT solution. Challenges: The key hurdles encountered by the client encompassed: Data Security Considerations: Given the growing emphasis on data protection laws like GDPR the client required a solution that could ensure security for user interactions within their platform. Adherence to SOC 2 Requirements: The industry standards dictated adherence, to SOC 2 protocols introducing an added layer of complexity into the project. Solution: Our team devised a GPT model that seamlessly integrated cutting edge conversational AI capabilities. while meeting the clients specific security and regulatory needs.

Solution

Functionality Overview: The Private GPT system offered features akin to ChatGPT, such as: Natural Language Processing: capabilities for understanding and generating human responses. Adaptive Learning: Enhancing responses through improvement based on user interactions while upholding privacy standards. Outcomes: Implementing the Private GPT system led to: Improved Data Security: Clients could confidently deploy the AI system knowing that user data was well protected against unauthorized access. C.

Results

100%

Project Completion

Tech Stack

PythonLangChainPostgreSQLAWS

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