Retroactive security reviews added a week to projects. Embedding controls cut build times 30% and scaled AI to 50k employees.
A global professional services firm advises clients in highly regulated sectors on adopting generative AI while managing strict data privacy and compliance requirements.
Clients hesitated to deploy AI due to risks of data leakage, while building custom safeguards from scratch caused significant delays. Security...
“Customers want to use GenAI, but they do not want to sacrifice data security and compliance. By using the Purview SDK, we are able to apply protections and observability directly into the platform design.”
EY's Secure AI development is part of this use case:
Global professional services for assurance, tax, consulting, and strategy.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Daily GenAI use introduced prompt injection risks. Real-time monitoring now blocks threats and addresses 8 of 10 top LLM security risks.
Basic AI chat couldn't resolve complex workflow bottlenecks. Now, non-technical staff build tens of thousands of custom micro-agents.
Technical debt in large codebases hindered velocity. Now, AI handles execution-heavy updates while engineers retain merge approval.
Engineers rebuilt routing and access controls for every AI feature. Now, a central gateway standardizes governance portfolio-wide.
Privacy rules bottlenecked AI scaling. A secure internal platform now cuts AML investigation time by days and security resolution by 50%.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Lawyers manually reviewed 300-page technical reports. AI now scans the docs to draft affidavits and witness tables instantly.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Retroactive security reviews added a week to projects. Embedding controls cut build times 30% and scaled AI to 50k employees.
A global professional services firm advises clients in highly regulated sectors on adopting generative AI while managing strict data privacy and compliance requirements.
Clients hesitated to deploy AI due to risks of data leakage, while building custom safeguards from scratch caused significant delays. Security...
“Customers want to use GenAI, but they do not want to sacrifice data security and compliance. By using the Purview SDK, we are able to apply protections and observability directly into the platform design.”
EY's Secure AI development is part of this use case:
Global professional services for assurance, tax, consulting, and strategy.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Daily GenAI use introduced prompt injection risks. Real-time monitoring now blocks threats and addresses 8 of 10 top LLM security risks.
Basic AI chat couldn't resolve complex workflow bottlenecks. Now, non-technical staff build tens of thousands of custom micro-agents.
Technical debt in large codebases hindered velocity. Now, AI handles execution-heavy updates while engineers retain merge approval.
Engineers rebuilt routing and access controls for every AI feature. Now, a central gateway standardizes governance portfolio-wide.
Privacy rules bottlenecked AI scaling. A secure internal platform now cuts AML investigation time by days and security resolution by 50%.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Lawyers manually reviewed 300-page technical reports. AI now scans the docs to draft affidavits and witness tables instantly.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.