Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
A global technology company launched a new portfolio of AI PCs featuring a personal AI agent, designed to operate across diverse hardware platforms in over 200 markets.
The company needed to protect users from harmful content generated on-device, even when offline, while complying with varying global privacy...
“Through joint engineering and optimization, the final results were astounding. The AI safety detection runs entirely on-device, achieving millisecond-level response time.”
Personal computers, smartphones, and data center infrastructure manufacturer.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Lenovo's On-device moderation is part of this use case:
Related implementations across industries and use cases
Outsourcing restricted confidential data. A two-week sprint equipped teams with standardized workflows to securely build AI in-house.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Data was scattered across six mailboxes. Now, AI summarizes history in one view, cutting resolution time by 35%.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Generic tools misread student nuance, triggering false alarms. Now, an AI judge evaluates context, alerting teachers only to true crises.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Fragmented legacy platforms took weeks to scale. Now, AI routes emails by intent while unified desktops let agents resolve issues faster.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
A global technology company launched a new portfolio of AI PCs featuring a personal AI agent, designed to operate across diverse hardware platforms in over 200 markets.
The company needed to protect users from harmful content generated on-device, even when offline, while complying with varying global privacy...
“Through joint engineering and optimization, the final results were astounding. The AI safety detection runs entirely on-device, achieving millisecond-level response time.”
Personal computers, smartphones, and data center infrastructure manufacturer.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Lenovo's On-device moderation is part of this use case:
Related implementations across industries and use cases
Outsourcing restricted confidential data. A two-week sprint equipped teams with standardized workflows to securely build AI in-house.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Data was scattered across six mailboxes. Now, AI summarizes history in one view, cutting resolution time by 35%.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Generic tools misread student nuance, triggering false alarms. Now, an AI judge evaluates context, alerting teachers only to true crises.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Fragmented legacy platforms took weeks to scale. Now, AI routes emails by intent while unified desktops let agents resolve issues faster.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.