LastMile AI Platform

Q: How fast can I compute my first evaluation metric with LastMile?

You can compute your first evaluation metric within 5 minutes using the provided quickstart guide. The AutoEval engine supports Python and Node.js, making it easy to integrate into existing codebases and start evaluating LLM applications quickly.

Q: What out-of-the-box metrics does LastMile offer?

LastMile includes Faithfulness for hallucination detection, Relevance for semantic similarity, Summarization Quality, and Toxicity metrics. These are designed for common AI applications like RAG and multi-agent systems, providing immediate evaluation capabilities without custom setup.

Q: Can I create custom evaluators with LastMile?

Yes, LastMile offers a fine-tuning service to design custom evaluators. You upload datasets, generate synthetic labels using LLM Judge with human-in-the-loop refinement, and fine-tune evaluators that represent your specific application quality criteria.

Q: What are the alBERTa small language models in LastMile?

alBERTa is a family of small language models optimized for evaluation. alBERTa-512 has 400M parameters, 512 token context, and runs CPU inference under 300ms. alBERTa-LC-8k scales up to 128k tokens for long-context tasks.

Q: How does LastMile compare to LangSmith or Weights & Biases?

LastMile focuses on full-stack development with Python and Node.js support and proprietary alBERTa SLMs for fast evaluation. It offers fine-tuning for custom evaluators, unlike competitors relying on LLM-as-judge. However, it is smaller with less community adoption and no public pricing.

LastMile AI Platform is a full-stack developer platform for debugging, evaluating, and improving LLM applications.

Updated 18 days ago Reviewed by 7wData

Publisher review

LastMile AI Platform is a full-stack developer platform for debugging, evaluating, and improving LLM applications. It is designed for developers who need to move beyond ad-hoc testing and implement systematic evaluation pipelines. The platform supports both Python and Node.js, making it accessible to a wide range of engineering teams. Its primary audience includes developers building RAG systems, multi-agent compound AI systems, and any production LLM application that requires rigorous quality control. The platform distinguishes itself by providing a complete workflow from data management to fine-tuning custom evaluators, all within a single interface.

Key capabilities center on the AutoEval evaluation engine. Users can compute their first evaluation metric within 5 minutes using the provided quickstart guide. The platform offers out-of-the-box metrics including Faithfulness (for hallucination detection), Relevance (semantic similarity), Summarization Quality, and Toxicity. For custom needs, LastMile provides a fine-tuning service to design custom evaluators that represent specific application quality criteria. The platform also includes alBERTa, a family of small language models (SLMs) optimized for evaluation: alBERTa-512 (400M parameters, 512 token context, runs inference on CPU in under 300ms) and alBERTa-LC-8k (long-context variant scaling up to 128k tokens). Additional features include synthetic labeling using LLM Judge with human-in-the-loop refinement, guardrail setup, and monitoring of app performance.

LastMile operates in the LLM evaluation and observability space, competing with platforms like LangSmith, Weights & Biases Prompts, and Arize AI. Its focus on full-stack development (Python and Node.js) and its proprietary SLM family (alBERTa) differentiate it from competitors that rely solely on LLM-as-judge approaches. The platform's emphasis on fine-tuning custom evaluators also positions it as a more customizable alternative to out-of-the-box evaluation tools. However, LastMile is a smaller, less established player compared to these competitors, and its market share and community adoption are not yet at the scale of more mature platforms.

Honest trade-offs include the lack of publicly available pricing information, which makes it difficult for teams to budget for the tool without a sales conversation. The platform also does not specify its customer support model or community resources, which could be a concern for teams that rely on community forums or dedicated support. While the alBERTa SLMs are fast and small, they are specialized for evaluation tasks and may not match the general-purpose reasoning of larger LLM judges for complex scenarios. Finally, the platform's documentation, while clear, is relatively sparse compared to more established competitors, potentially requiring more self-directed exploration for advanced use cases.

How it works

AutoEval evaluation engine

Compute evaluation metrics on data using Python or Node.js, with first metric achievable within 5 minutes via the quickstart guide.
Out-of-the-box metrics

Includes Faithfulness, Relevance, Summarization Quality, and Toxicity metrics for common AI application types like RAG and multi-agent systems.
Fine-tune custom evaluators

Design your own evaluators representing custom criteria by uploading datasets, generating synthetic labels, and fine-tuning using the AutoEval service.
alBERTa SLM family

Small language models (400M parameters) for evaluation: alBERTa-512 (512 tokens, CPU inference <300ms) and alBERTa-LC-8k (up to 128k tokens).
Synthetic labeling

Generate high-quality labels for evaluation data using LLM Judge with human-in-the-loop refinement to improve label accuracy.
Guardrails and monitoring

Set up real-time guardrails and monitor app performance to catch issues in production LLM applications.
Multi-language support

Supports both Python and Node.js with equivalent APIs, allowing teams to integrate evaluation into existing codebases in either language.

Strengths and trade-offs

Strengths

Developers can compute their first evaluation metric within 5 minutes using the provided quickstart guide, lowering the barrier to entry for systematic LLM evaluation.
The platform includes a family of small language models (alBERTa-512 and alBERTa-LC-8k) optimized for evaluation, with alBERTa-512 running inference on CPU in under 300ms.
Full-stack support for both Python and Node.js allows teams to integrate evaluation into existing codebases without switching languages.
The fine-tuning service enables creation of custom evaluators that represent specific application quality criteria, going beyond out-of-the-box metrics.

Trade-offs

Pricing details are not publicly available, making it difficult for teams to estimate costs without engaging in a sales process.
No specific mention of customer support channels or community resources, which may be a concern for teams that rely on forums or dedicated support.
The alBERTa SLMs, while fast, are specialized for evaluation tasks and may not match the general-purpose reasoning of larger LLM judges for complex scenarios.
Documentation is relatively sparse compared to more established competitors, potentially requiring more self-directed exploration for advanced use cases.

Pricing context

Not publicly specified in the available sources.

Getting started with LastMile AI Platform

Sign up for LastMile

Go to the LastMile AI Platform website and create an account. Provide your email and set a password, or sign up using a supported SSO provider. Verify your email to activate the account.
Install the SDK

Install the LastMile SDK in your project using pip for Python or npm for Node.js. Run `pip install lastmile` or `npm install lastmile` in your terminal to add the library to your dependencies.
Connect your LLM app

Initialize the LastMile client in your code with your API key. Pass your LLM application's output data or logs to the client, enabling the platform to capture and evaluate responses.
Compute your first metric

Use the AutoEval quickstart guide to compute a metric like Faithfulness or Relevance. Load a sample dataset or your own data, then call the evaluation function to get results within minutes.
Set up guardrails

Configure guardrails in the LastMile dashboard to monitor your app in real time. Define thresholds for metrics like Toxicity, and enable alerts to catch issues before they affect users.

Frequently Asked Questions

What is the LastMile AI Platform used for?

LastMile AI Platform is a full-stack developer platform for debugging, evaluating, and improving LLM applications. It helps developers move beyond ad-hoc testing to systematic evaluation pipelines, supporting RAG systems, multi-agent AI, and production LLM apps with rigorous quality control.

How fast can I compute my first evaluation metric with LastMile?

You can compute your first evaluation metric within 5 minutes using the provided quickstart guide. The AutoEval engine supports Python and Node.js, making it easy to integrate into existing codebases and start evaluating LLM applications quickly.

What out-of-the-box metrics does LastMile offer?

LastMile includes Faithfulness for hallucination detection, Relevance for semantic similarity, Summarization Quality, and Toxicity metrics. These are designed for common AI applications like RAG and multi-agent systems, providing immediate evaluation capabilities without custom setup.

Can I create custom evaluators with LastMile?

Yes, LastMile offers a fine-tuning service to design custom evaluators. You upload datasets, generate synthetic labels using LLM Judge with human-in-the-loop refinement, and fine-tune evaluators that represent your specific application quality criteria.

What are the alBERTa small language models in LastMile?

alBERTa is a family of small language models optimized for evaluation. alBERTa-512 has 400M parameters, 512 token context, and runs CPU inference under 300ms. alBERTa-LC-8k scales up to 128k tokens for long-context tasks.

How does LastMile compare to LangSmith or Weights & Biases?

LastMile focuses on full-stack development with Python and Node.js support and proprietary alBERTa SLMs for fast evaluation. It offers fine-tuning for custom evaluators, unlike competitors relying on LLM-as-judge. However, it is smaller with less community adoption and no public pricing.

Alternatives in this category

How LastMile AI Platform compares

Direct head-to-head against 2 competitors. Picked by 7wData.

Pricing: Not publicly specified in the available sources.
Target: LastMile AI Platform is a full-stack developer platform for debugging, evaluating, and improving LLM applications.
Strength: Developers can compute their first evaluation metric within 5 minutes using the provided quickstart guide, lowering the barrier to entry for systematic LLM evaluation.
Watch for: Pricing details are not publicly available, making it difficult for teams to estimate costs without engaging in a sales process.

Pricing: Custom/Contact sales
Target: Developers building AI apps
Deployment: Cloud
Strength: Unified platform for advanced AI models
Watch for: Complex pricing structure

Pricing: $99/user/year
Target: Excel users automating workflows
Deployment: Desktop
Strength: SQL and .NET integration in Excel
Watch for: Limited to Excel environments

User reviews

No user reviews yet. Be the first to write one.

Sources

Reporting on this tool draws on these publicly available sources.

LastMile AI Platform

On this page

Publisher review

How it works

AutoEval evaluation engine

Out-of-the-box metrics

Fine-tune custom evaluators

alBERTa SLM family

Synthetic labeling

Guardrails and monitoring

Multi-language support