PromptLayer
Streamline and optimize AI prompts efficiently with real-time analytics.. [Free]
Last verified:
What is PromptLayer?
PromptLayer is a collaboration layer for AI engineering teams that provides prompt CMS, eval harness, and observability stack for versioning, testing, and monitoring every prompt and agent. It acts as middleware between your code and LLM provider libraries (like OpenAI's Python library), automatically logging all API requests with metadata to a searchable dashboard. The platform enables teams to manage prompt templates visually without touching codebase, making it easier for domain experts to collaborate on prompt engineering.
Key features include Prompt Registry for versioning and creating prompt templates visually, Evaluations for batch-running prompts against datasets with quality dimensions and scoring logic, Dataset Management for building and organizing evaluation datasets, Observability for reviewing inference usage/cost/latency with full AI-application traces, Workflows for building complex multi-step processes by chaining prompts, A/B Testing for comparing prompt variants in production, Release Labels for promoting tested prompt versions across environments, Analytics for tracking usage and quality trends, Role-Based Access Control for workspace permissions, Webhooks for event notifications, and SDKs for Python and JavaScript.
PromptLayer is designed for prompt engineers, AI engineers, developers, data scientists building LLM applications, and non-technical domain experts who need to collaborate on prompts without engineering involvement. It serves AI engineering teams at companies of all sizes, from individual hackers to large enterprises requiring HIPAA compliance and self-hosting options.
PromptLayer pricing
Pricing model: Freemium
PromptLayer offers four pricing tiers: Free ($0/month) for hackers with 5 users, 2,500 requests/month, 1 workspace, 250 eval cell executions/month, 10MB max per dataset, 10 playground runs/day, and 750 agent node executions/month. Pro ($49/month) for small teams includes same base limits plus unlimited playgrounds, unlimited workspaces, 150MB max per dataset, and pay-as-you-go overage at $0.003 per transaction. Team ($500/month) for growing teams offers 25 users, 100k+/month requests, 7,5k+/month eval cell executions, 1GB max per dataset, webhooks, and pay-as-you-go at $0.002 per transaction. Enterprise has custom pricing with custom limits on everything, RBAC, deployment approvals, HIPAA with BAA, flexible hosting (self-hosted on GCP/AWS/Azure, cloud-hosted in EU, or single-tenant), dedicated support, and data retention control. All plans include unlimited prompts (except Free has 10 prompts). Free/Pro/Team are cloud-hosted in the US; Enterprise can choose self-hosted or EU cloud-hosting.
PromptLayer pros
- Visual prompt editor enables non-technical domain experts to collaborate without code
- Automatic middleware logging captures all OpenAI API requests with metadata
- Prompt Registry separates prompt management from application code
- Robust evaluation harness with batch runs against custom datasets
- Regression testing capabilities backtest new prompts against historical data
- Full AI-application traces show complete request/response pairs
- A/B testing routes production traffic based on measured performance
- Release labels promote tested prompt versions across environments safely
- Python and JavaScript SDKs with REST API for programmatic access
- Role-Based Access Control granular permissions for engineers and reviewers
- Analytics track usage, cost, latency, and quality trends over time
- Webhooks notify on events like prompt executions and workflow runs
- OpenTelemetry integration connects with tracing pipelines and providers
- SOC2 Type 2, GDPR, HIPAA, and CCPA certified for enterprise compliance
- Free tier available with 2,500 requests/month and 250 eval executions
PromptLayer cons
- Free tier limited to 2,500 requests/month and 1 workspace only
- Pro plan at $49/month still limited to 5 users like Free tier
- Team plan at $500/month may be expensive for small startups
- Pay-as-you-go overage billing adds up quickly for high-volume usage
- Self-hosting and single-tenant only available for Enterprise customers
- Cloud-hosted in US only for Free/Pro/Team plans (no EU option)
- Basic support included on all non-Enterprise plans
- Dataset size limits restrictive on lower tiers (10MB Free, 150MB Pro)
- 7-day log retention on Free plan may be insufficient for debugging
- Enterprise custom pricing requires sales contact instead of transparent pricing
Frequently asked questions about PromptLayer
What does PromptLayer do?
PromptLayer is a platform for prompt engineering that lets you version, test, and monitor every prompt and agent. It provides a prompt CMS for managing prompt templates visually, an eval harness for testing prompts against datasets with quality scoring, and an observability stack for tracking usage, cost, and latency. It acts as middleware between your code and LLM providers, automatically logging all API requests to a searchable dashboard where you can debug, analyze, and collaborate on prompts without touching your codebase.
How do I get started with PromptLayer?
Visit promptlayer.com and click Sign Up to create a free account. After email verification, create an API key from your dashboard and save it securely. Install the Python library with 'pip install promptlayer' or the JavaScript SDK. Initialize PromptLayer in your code with your API key, and it will automatically start logging all your LLM requests. Navigate to the Prompt Registry to create your first prompt visually, test it in the Playground, and start exploring your request history in the dashboard.
What is the Prompt Registry feature?
The Prompt Registry gives teams a dedicated place to experiment with prompts and manage versions separately from application code. You can create prompt templates visually in the Playground, version them, add release labels to promote tested versions across environments (like staging to production), and programmatically retrieve them via SDK or API. This separates prompt engineering from code deployments, allowing domain experts to iterate on prompts without developer involvement.
How do evaluations work in PromptLayer?
Evaluations let you batch run prompts against sample input datasets to test quality before deploying to production. You define quality dimensions and scoring logic, then run prompts against datasets to get scores. You can build regression tests to catch prompt degradation, run one-off batches for specific testing needs, or backtest new prompts against historical data. Evaluation cell executions are counted against your plan limits (250/month Free, 250+/month Pro, 7,500+/month Team).
What LLM providers does PromptLayer support?
PromptLayer works with any LLM provider through its middleware functionality. It was originally built for OpenAI's GPT models and Python library, but through SDKs and REST API it supports all major providers. The platform logs requests regardless of provider, allowing you to track usage, cost, and performance across different models. LiteLLM integration also enables logging across all providers with just 2 lines of code using callbacks.
Is PromptLayer HIPAA compliant?
Yes, PromptLayer is HIPAA compliant and maintains SOC2 Type 2, GDPR, HIPAA, and CCPA certifications. HIPAA with BAA (Business Associate Agreement) is available as a feature for Enterprise customers. Enterprise plans also offer flexible hosting options including self-hosted on GCP, AWS, and Azure, cloud-hosted in the EU, or cloud-hosted single-tenant for enhanced security and compliance requirements.
What is the difference between Free, Pro, and Team plans?
Free ($0/month) has 5 users, 2,500 requests/month, 1 workspace, 10MB datasets, 10 playground runs/day, and basic features. Pro ($49/month) adds unlimited playgrounds, unlimited workspaces, 150MB datasets, and pay-as-you-go overage at $0.003/txn but keeps 5 users. Team ($500/month) scales to 25 users, 100k+/month requests, 7,500+/month eval executions, 1GB datasets, webhooks, and cheaper overage at $0.002/txn. Enterprise adds RBAC, deployment approvals, HIPAA with BAA, self-hosting, and dedicated support.
How does PromptLayer tracking work?
PromptLayer acts as middleware between your code and LLM provider libraries. When you integrate the SDK, it automatically intercepts all API calls, logging the request, response, metadata, execution time, cost, and token usage to your dashboard. You can search and filter logs by metadata or tags, inspect individual request/response pairs, view full traces for AI applications, and even replay old completions. This happens in real-time without changing your application logic.
Can I self-host PromptLayer?
Self-hosting is available only for Enterprise customers. Enterprise plans offer self-hosted deployment on GCP, AWS, and Azure, as well as cloud-hosted in the EU or cloud-hosted single-tenant options. Free, Pro, and Team plans are cloud-hosted in the US only. Self-hosting gives you full control over data residency and security, which is important for organizations with strict compliance or data governance requirements.
What are Workflows and Agents in PromptLayer?
Workflows let you build complex, multi-step processes by chaining prompts and logical operations together. Agents are predefined workflows that can execute complex sequences. You can run agents using the run_workflow() method in the SDK or via REST API by POSTing to '/workflows/agentName/run'. Agent node executions are counted against your plan (750/month Free, 750+/month Pro, 10k+/month Team). You can poll for completion and retrieve all intermediate node outputs or final results.