Interactive LLM Demos

Built an interactive LLM demo experience to showcase AI hardware performance to customers.

Key Takeaways:

Visibility: Interactive demos replaced abstract performance metrics with real-time LLM workload visualization.
Engagement: The public-facing AI Starter Kit became a focal point for customer strategy and internal team engagement.
Velocity: Publicly accessible tooling accelerated product feedback loops and de-risked the hardware evaluation process.

Interactive AI Starter Kit Clarifies LLM Performance for Hardware Evaluation

Factored architected an open, configurable demo infrastructure to showcase the speed and flexibility of reconfigurable dataflow units, transforming abstract hardware specs into a tangible evaluator experience.

Hardware Performance Complexity Constraining Sales

A technology firm specializing in reconfigurable dataflow units (RDUs) faced a significant barrier in customer acquisition: demonstrating hardware performance for Large Language Model (LLM) workloads remained too abstract. Without a tangible way to explore the hardware’s speed and flexibility, potential buyers struggled to assess its "Operational Reality" within their own environments.

Decoupling Hardware Utility from Abstraction

The challenge was to design a public-facing infrastructure that allowed users to independently configure and explore LLM performance across varied parameters. The solution needed to be lightweight enough for rapid deployment yet rigorous enough to serve as a reliable technical receipt for skeptical VPs of Engineering and CTOs.

Public-Facing AI Starter Experience

Supported by our Machine Learning and Software Engineering Centers of Excellence, we engineered an interactive AI Starter Kit designed for modularity and high engagement.

Technical Components:

  • Interactive Configuration: Built a lightweight application layer allowing users to modify LLM parameters and observe performance deltas in real time.
  • Hosted Integration: Architected the demo to integrate seamlessly with hosted LLMs, ensuring a low-latency user experience.
  • Public Repository: Operationalized the code within a public repository to encourage transparency and community-driven feedback.

Results: Evidence-Based Customer Discovery

The interactive experience was successfully operationalized, shifting the sales narrative from strategy to execution:

  • Clarified Performance: Prospective buyers gained a precise understanding of hardware efficiency, resulting in faster evaluation cycles.
  • Accelerated Feedback: The public tooling enabled a continuous feedback loop between customers and internal product teams.
  • Strategic Alignment: The demo infrastructure became the primary technical anchor for customer-facing conversations, reducing the "Execution Risk" associated with hardware investment.
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