LastMile AI

LastMile AI AutoEval — Generative AI Evaluation Platform is an enterprise-grade platform designed to help developers test, evaluate, and benchmark AI applications. It ships with battery-included evaluation metrics for RAG and multi-agent AI, along with fine-tuning capabilities to design custom evaluators. The platform emphasizes reproducibility, private deployment, and real-time evaluation at scale.

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How it works

1. Install and integrate: Quick-start with code examples for Python and TypeScript.
2. Run evaluations: Use built-in metrics or your own custom evaluators to measure how well your AI system performs on real-world tasks.
3. Fine-tune evaluators: Train evaluator models tailored to your data distribution and evaluation criteria.
4. Deploy securely: Run AutoEval in Private Virtual Cloud or on your own infrastructure with robust data governance.
5. Monitor in real time: Real-time inference, guardrails, and continuous monitoring for production-grade reliability.

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Core Capabilities

• AutoEval Out-of-the-Box Metrics for RAG and multi-agent AI applications
• Fine-tuning service to design your own evaluators
• Real-time AI evaluation with blazing-fast inference
• Private deployment options (Private VPC / On-Prem) for data security and compliance
• Synthetic data generation to automate labeling and reduce manual effort
• Reproducible experiment management to accelerate innovation
• Custom metrics support to capture nuanced evaluation criteria
• Guardrails and proactive monitoring to detect anomalies and mitigate risks
• Cross-language client examples (Python and TypeScript) for easy integration
• Scalable evaluation runs and large-scale data support

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How to Use AutoEval

• Python example (pip install lastmile):

• from lastmile.lib.auto_eval import AutoEval, BuiltinMetrics

• client = AutoEval()

• result = client.evaluate_data( data=pd.DataFrame({"input": ["Where did the author grow up?"], "output": ["France"], "ground_truth": ["England"]}), metrics=[BuiltinMetrics.FAITHFULNESS] )

• TypeScript example:

• const { AutoEval, BuiltinMetrics } = require("lastmile/lib/auto_eval");

• const client = await AutoEval.create();

• const result = await client.evaluateData({ data: [{ input: "Where did the author grow up?", output: "France", ground_truth: "England" }], metrics: [BuiltinMetrics.FAITHFULNESS] });

• Custom metrics: Upload app data, define your own evaluator models, and fine-tune as needed.

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Feature Highlights

• Out-of-the-Box metrics for evaluation of RAG and multi-agent systems
• Fine-tuning of evaluator models to align with app-specific criteria
• Real-time evaluation with ultra-low latency inference
• Private deployment options for data control and regulatory compliance
• Synthetic data generation to automate labeling and data creation
• Reproducible experiment management for reliable results
• Custom metrics and custom evaluator support for bespoke needs
• Guardrails and continuous monitoring to proactively manage risk
• Cross-language SDKs (Python and TypeScript) for seamless integration
• Scalable evaluation workflows with support for large datasets

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Why Choose AutoEval

• Trustworthy, production-ready evaluation tooling designed for real-world AI systems
• End-to-end workflow from data generation to evaluation and monitoring
• Flexible deployment models to meet enterprise security, privacy, and compliance requirements
• Accelerates AI innovation by reducing manual labeling and accelerating experimentation

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Safety and Deployment Considerations

• Deploy within your own private cloud or on-prem to maintain data sovereignty
• Use synthetic data generation to minimize exposure of sensitive information
• Implement guardrails to detect and mitigate risky model behaviors in production

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Quick Start Resources

• Official documentation and API guides
• Examples and tutorials for AutoEval in Python and TypeScript
• Pricing tiers including no-cost entry for quick experimentation