Liquid AI, in Collaboration with Qualcomm Technologies, Brings Personal AI Context to Devices Powered by Snapdragon

Liquid AI today, at Snapdragon Summit 2026, announced  that Liquid Context, an on-device context layer, is now optimized for Snapdragon® processors, specifically using the Qualcomm® Hexagon™ NPU. In collaboration with Qualcomm Technologies, Liquid Context built a persistent understanding of the user from signals from devices with Snapdragon processors and made relevant context available to AI agents, whether they ran on the device, in the cloud or across both. Device manufacturers now have a foundation for more proactive, personalized and trustworthy AI experiences, alongside Liquid Agent, Liquid AI’s efficient embedded agent.

Personal Context That Makes Any Agent More Useful

Useful agents need to understand what matters to the user and when help is needed. With the user’s permission, Liquid Context learns from device signals, builds an understanding of routines, preferences and needs, and keeps that understanding current. It provides a shared context layer between the device and the user’s chosen agents, including third-party agents and Liquid Agent. Context supplies the understanding; agents use it to reason, suggest next steps and take action with permission. Personal context is built and maintained locally, with relevant context made available to connected agents according to the user’s permissions. 

“Personal AI starts with understanding how you live and what you need, when you need it,” said Liquid AI CEO and co-founder Ramin Hasani. “Liquid Context builds that understanding on your device so the agents you choose can offer more relevant help and anticipate your needs. The Hexagon NPU makes this continuous, local intelligence practical. Together, we are bringing personal context to the devices people rely on every day.”

Efficient NPU execution is central to keeping this understanding current. Liquid Context is designed to run in the background, turning permitted device signals into useful context without requiring a cloud model to process every update. Agents can then use that context to recognize when help would be valuable and respond in a way that reflects the user’s priorities.

Illustrative experiences enabled by Liquid Context include:

• Adapting to a family emergency: a message arrives that the user’s child is sick and needs an early school pickup. Liquid Context supplies relevant family context and the user’s priorities. A connected agent checks the calendar, identifies which meetings can move while preserving an important commitment, and drafts rescheduling emails for the user to approve.
• Turning a conference day into a personal recap: after a day of networking and keynotes, Liquid Context supplies the user’s preference for sharing a LinkedIn recap and their writing style, alongside relevant context from the day. A connected agent selects photos the user has permitted it to access, drafts a post in their voice and queues it for review.
• Carrying context from a run into the car: the user leaves their phone at home and runs with a smartwatch. The watch captures local context about the run, including a new personal record. When the user returns to the car, that context syncs locally with permission. The car’s agent congratulates them, cools the cabin according to their preferences and suggests a stop for a recovery smoothie.

Bringing Liquid Context to Snapdragon Platforms

Qualcomm Technologies and Liquid AI are exploring additional opportunities to work together to further enhance the performance of Liquid Context with Snapdragon platforms, so OEMs can offer personal context as a built-in device capability, making it easier for users to enable Liquid Context. Compatible embedded, cloud and hybrid agents could even use that context to deliver proactive, personalized assistance. 

For OEMs choosing a platform for agentic experiences, the optimization brings together Hexagon NPU hardware built for AI workloads and Liquid Context software that makes device signals useful to agents. It gives manufacturers a path to add personal context while supporting their choice of agents and services.

"Qualcomm Technologies is at the forefront of advancing AI across devices, edge solutions and datacenters, driving the innovations needed to deliver increasingly intelligent, personalized experiences for consumers around the world. By combining our industry-leading Snapdragon platforms with innovative AI technologies from companies like Liquid AI, we're helping accelerate the next generation of Agentic AI experiences." – Durga Malladi, EVP & GM, Technology Planning, Edge Solutions, and Data Center, Qualcomm Technologies, Inc. 

Hexagon NPU: Built for Context and Agents

Continuous context processing and responsive agent execution both require efficient hardware. Liquid AI has optimized its Liquid Context memory layer and, separately, the LFM2.5-2.6B agentic model that powers Liquid Agent to take advantage of processing, memory access and low latency of Snapdragon processors. The next-generation Hexagon NPU combines scalar, vector and matrix processing with dedicated transformer hardware to accelerate these workloads. This pairing can support ongoing context updates and capable embedded agents within the power constraints of everyday devices.

Liquid Agent: An Efficient Embedded Agent for OEMs

OEMs building embedded or hybrid agents can also work with Liquid AI to evaluate Liquid Agent, powered by its state-of-the-art, efficient LFM2.5-2.6B agentic model and optimized for execution on the Hexagon NPU. Liquid Agent can be tailored to a manufacturer’s hardware, services, interface and brand, and can consume Liquid Context to deliver personalized, proactive assistance. Liquid Context provides the shared context layer for that vision, preserving relevant understanding and task state with permission so different agents can pick up where the user left off. OEMs can use the Hexagon NPU and Liquid Context as a foundation for their chosen agents, and evaluate Liquid Agent when they need an efficient embedded or hybrid agent of their own.