AI model decision dashboard

A rapid prototype for discussing AI model choices. I defined the brief and built an interface with comparative views of public benchmark data. The useful lesson is how quickly an idea can become reviewable; moving from that demonstration to a supported enterprise tool remains a separate engineering and governance task.

Evidence and scope

Live personal prototype

Product brief, interaction design and build

Three hours is a self-reported prototype build time, not a production delivery estimate. An earlier internal-team estimate concerned a different, production-grade scope and is not used as a cost or time saving. Public source data and a live demo do not constitute a model-selection accuracy evaluation.

Outcome and evidence

A rapid prototype for discussing AI model choices. I defined the brief and built an interface with comparative views of public benchmark data. The useful lesson is how quickly an idea can become reviewable; moving from that demonstration to a supported enterprise tool remains a separate engineering and governance task.

My role

I owned the product requirements, interaction design and AI-assisted prototype build. Artificial Analysis provides the benchmark data; this project does not claim ownership of its underlying research.

The problem

Model choice involves tradeoffs across performance, cost and latency. The prototype makes these comparisons easier to explore before conducting a use-case-specific evaluation.

The approach

Build a React and TypeScript interface using AI-assisted development, charts and public benchmark data. Comparative views and an AI-insights interaction make the product idea available for review.

Constraints and governance

Benchmark results may not transfer to a company's workload. Data freshness, access controls, security, integrations and support must be addressed before production. Prototype features are not evidence of reliable recommendations.

Outcome and evidence

A working personal prototype, built in a self-reported three hours. It demonstrates a product interaction, not a like-for-like replacement for a production project. No production delivery saving or independently measured model-selection improvement is claimed.

Outcome and evidence

  • Build time (self-reported): 3 hours
  • Scope: Prototype, not production
  • Data source: Artificial Analysis

Sources

Canonical URL: https://juanbeltran.ch/portfolio/ai-model-benchmarking-dashboard