LLM Selection Optimizer

Use data to make the right LLM choice to accelerate growth and cut costs by 60%

Remove the guesswork and stop overpaying

Want to cut Large Language Model-related costs but not performance? Struggling to accelerate LLM adoption? What if you could get proof which model yields the best ROI?

Choosing the wrong Large Language Model can waste your budget, slow MVP validation, and increase technical debt.

LLM Selection Optimizer compares leading LLMs using your real datasets and workflows to find the right foundation model on Amazon Bedrock for your exact situation.

Make a data-backed choice before going into production

Audit:

Automat-it’s AWS AI Competency team evaluates your use case and proprietary datasets against the current LLM landscape

Test:

We simulate your workload to measure real-world cost vs. performance, benchmarking across cost, latency, accuracy, and task performance

Optimize:

Receive a Benchmarking Report and data-backed recommendation to confidently deploy the model that maximizes ROI

Remove the risk in your LLM roadmap and benefit from day one

Optimize Burn rate

Use right-sized models to avoid wasted spend

Faster Time-to-Decision

Skip trial-and-error cycles with standardized, reproducible benchmarks

Scalable Strategy

Avoid vendor lock-in with a flexible, growth-aligned strategy

Insights Before You Commit

Understand model response times, accuracy, and reasoning power before production

Seamless Stack Integration

Leverage Amazon Bedrock best practices and reference architectures for smooth deployment

Work with Experts

Automat-it has the AWS AI Services Competency. This means we have undergone rigorous technical validation and demonstrated successful customer implementations that meet AWS’s high standards for security, reliability, and operational excellence.

Ready to remove risk from your AI roadmap?

Optmize burn rate, reduce time-to-decision, and implement a winning scale strategy with Automat-it’s LLM Selection Optimizer.