AI implementation
Making AI work in the real world.
Optimizing AI for real-world use
Successful AI implementation hinges on inference: the process of running trained models in production to generate real-time predictions and decisions. Efficient inference is key to ensuring AI delivers value while operating within the constraints of modern devices and systems.
Master the inference challenge
We specialize in optimizing AI inference to make models work seamlessly in the environments where they’re needed most, including:
On-device processing that reduces or eliminates cloud dependencies
Low-latency solutions for time-sensitive applications
Secure deployment that protects sensitive data
Resource optimization to minimize computational overhead
Cost-effective scaling across multiple devices or systems
Enhancing collaboration
AI agents are powerful tools, but they are not a replacement for human expertise. We help businesses integrate AI agents into their workflows while maintaining a balance with their existing human teams. Our approach ensures:
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Complementary Roles
AI agents handle repetitive or data-intensive tasks, freeing up human teams to focus on higher-level decision-making and creativity.
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Avoiding Pitfalls
We identify the limitations of current AI capabilities, ensuring that businesses don’t rely on AI for tasks it isn’t yet equipped to handle.
Custom model development
Not all AI challenges can be solved with off-the-shelf models. Our AI engineers and data scientists design custom models tailored to your specific needs, whether it’s optimizing for low-power devices, integrating with proprietary data, or achieving high accuracy under strict computational constraints.
