EigenPrompt

Multi-objective prompt optimisation for production LLM systems. Automatically find the optimal trade-off between cost and accuracy — in minutes, not weeks.

The Problem

Manual prompt tuning doesn't scale. Engineers spend days tweaking prompts through trial and error, LLM inference costs spiral without clear benchmarks, and hallucinations erode user trust. EigenPrompt automates the process — systematically generating and evaluating hundreds of prompt variations to find what works best for your specific use case.


How It Works

1
Define

Set your evaluation criteria and choose your target LLM provider.

2
Submit

Provide your base prompt and test dataset.

3
Optimise

EigenPrompt automatically generates and evaluates hundreds of prompt variations. Runs typically complete in 5–10 minutes.

4
Explore

Review results on an interactive Pareto frontier — visualising the precise trade-off between cost and accuracy for every variation.

5
Deploy

Select your optimal prompt and ship with confidence.


Key Capabilities

Pareto Frontier

Interactive cost-vs-accuracy visualisation for data-driven prompt selection. No more guesswork — see exactly where each variation sits on the efficiency curve.

Model Agnostic

Works across all major providers. Bring your own API keys and optimise on the models you actually use in production.

Dual Evaluation

Quantitative scoring with expected outputs for classification and extraction tasks, or qualitative assessment using LLM judges with custom rubrics for open-ended outputs.

Enterprise Security

AES-256-GCM encryption at rest, TLS in transit, per-account key derivation. Your prompts and data stay yours.

Supported Providers
  • OpenAI
  • Anthropic
  • Google
  • Mistral
  • Cerebras
  • Groq
  • OpenAI-Compatible APIs

Stop Guessing. Start Optimising.

Try EigenPrompt with a free trial — if we can't find a better prompt, your credit is refunded.

Try EigenPrompt