Stop wasting engineering hours manually testing AI models—Airtrain lets you run thousands of LLM evaluations in parallel without writing infrastructure code.
What It Does for Your Business
Airtrain is a no-code batch compute platform that handles the heavy lifting of evaluating and tuning large language models at scale. Instead of spinning up servers, managing cloud resources, or writing custom evaluation scripts, your team uploads datasets, defines test cases, and Airtrain runs thousands of model experiments simultaneously—then shows you exactly which versions perform best and why. It's built for teams that need to move fast with AI but don't have dedicated MLOps engineers on staff.
For small businesses and agencies building AI features, this cuts evaluation time from days to hours. You can test prompt variations, compare different models (GPT-4, Claude, open-source options), and measure quality metrics—accuracy, latency, cost—without manually running each test. Airtrain handles the compute scaling, logs all results, and gives you clear dashboards to compare performance and ROI.
Key Features
- No-Code Batch Evaluation — Upload CSV or JSON datasets and run thousands of LLM tests in parallel without touching infrastructure or writing code
- Multi-Model Comparison — Test your prompts against GPT-4, Claude, open-source models, and fine-tuned variants side-by-side in one job
- Custom Metrics & Scoring — Define business-specific quality measures (accuracy, relevance, tone, compliance) and automatically score all outputs
- Cost & Performance Dashboards — See token usage, API costs, latency, and quality scores broken down by model and prompt version
- Prompt Version Control — Track and compare every prompt iteration; rollback or deploy winners with one click
- Integration-Ready Exports — Pull results into your workflow via API, webhook, or direct integrations with data pipelines
Best For
Development teams, AI-first startups, marketing agencies using AI content tools, customer support platforms, e-commerce companies building AI search or recommendations, SaaS companies evaluating LLM features, and any small business piloting multiple AI models before full deployment.
Pricing
Freemium model with free tier for small batch jobs. Paid plans start around $99/month for higher throughput; pricing scales with compute usage (token volume and parallel evaluations). Specific enterprise pricing available on request.
Business ROI
A typical small business team running manual LLM tests spends 8–12 hours per week on evaluation work; Airtrain cuts that to 2–3 hours by automating parallel testing and scoring. Cost savings compound when you identify the cheapest-performing model (switching from GPT-4 to a tuned open-source model can save $500–$2,000/month in API costs for small to medium workloads). Teams also ship AI features 2–3 weeks faster because you're no longer bottlenecked on manual QA and model selection, directly improving time-to-revenue and competitive positioning.
