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Title:PromptLayer - Your workbench for AI engineering. Platform for prompt management, prompt evaluations, and LLM observability

Description:Advanced prompt management and prompt engineering. Powerful prompt engineering tools for evaluation, deployment, observability, and analytics. Enable team collaboration, get help writing prompts, monitor AI agents, and improve prompt quality.

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Fetched At:October 29, 2025

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h1Your workbench for AI engineering

h2Case Studies

h3Gorgias Scaled Customer Support Automation 20x with LLMs

h3How Speak Empowers Non-Technical Teams with Prompt Engineering

h3ParentLab Builds Highly Personalized AI Interactions with PromptLayer

h3How NoRedInk Used PromptLayer Evals to Deliver 1M+ Trustworthy Student Grades

h3Lawyers in the Loop: How Midpage Uses PromptLayer to Evaluate and Fine-Tune Legal AI Models

h3How Magid built enterprise-grade AI agents for content creation with PromptLayer

h2Rigorously build great AI products.

h3Prompt with experts

h3No-code prompt editor

h3Include non-technical domain experts

h3Avoid engineer bottlenecks

h3Version prompts

h3Organize versions

h3Deploy new prompts

h3Clean up your repo

h3A/B test prompts

h3Evaluate iteratively

h3Historical backtests

h3Regression tests

h3Compare models

h3One-off bulk jobs

h3Monitor usage

h3Cost, latency stats

h3Latency trends

h3Jump to bug report

h2Prompt with experts

h3Prompt with actions

h3No-code prompt editor

h3Include non-technical stakeholders

h3Avoid engineer bottlenecks

h3Version prompts

h3Organize versions

h3Deploy new prompts

h3Clean up your repo

h3A/B test prompts

h3Evaluate iteratively

h3Historical backtests

h3Regression tests

h3Compare models

h3One-off bulk jobs

Markdown Content

PromptLayer - Your workbench for AI engineering. Platform for prompt management, prompt evaluations, and LLM observability

- Product

Prompt Management

Evaluations

Observability

Dataset Management

Prompt Chaining
- Docs
- Blog
- Case Studies
- Careers
- Contact UsLog In

# Your workbench for AI engineering

Version, test, and monitor every prompt and agent with robust evals, tracing, and regression sets. Empower domain experts to collaborate in the visual editor.

Start for free

Trusted by companies like you

Prompt management

Visually edit, A/B test, and deploy prompts. Compare usage and latency. Avoid waiting for eng redeploys.

Collaboration with experts

Open up prompt iteration to non-technical stakeholders. Our LLM observability allows you to read logs, find edge-cases, and improve prompts.

Evaluation

Evaluate prompts against usage history. Compare models. Schedule regression tests. Build one-off batch runs.

Prompt engineer with the whole team. Manage prompts visually in the Prompt Registry.

## Case Studies

### Gorgias Scaled Customer Support Automation 20x with LLMs

Gorgias is using PromptLayer to build an autonomous prompt engineering team, enabling them to scale their AI-powered helpdesk to millions of shoppers. They use PromptLayer every single day to store and version control prompts, run evaluations on regression and backtest datasets, and review logs to identify issues.

### Gorgias Scaled Customer Support Automation 20x with LLMs

### How Speak Empowers Non-Technical Teams with Prompt Engineering

PromptLayer empowers non-technical teams to iterate on AI features independently, saving engineering time and costs. See how Speak compressed months of curriculum development into a single week and launched in 10 new markets with PromptLayer.

### ParentLab Builds Highly Personalized AI Interactions with PromptLayer

PromptLayer enabled ParentLab to craft personalized AI interactions 10x faster, with 700 prompt revisions in 6 months, saving 400+ engineering hours. Prompts are deployed and updated solely by teams of non-technical domain experts.

### How NoRedInk Used PromptLayer Evals to Deliver 1M+ Trustworthy Student Grades

NoRedInk serves 60% of their U.S. school districts with AI-generated student grades, with curriculum designers and engineers collaborating in PromptLayer to design pedagogical evals and iterate on prompts directly. Their evaluation pipeline helped them deliver trustworthy, teacher-quality feedback at scale while giving educators orders of magnitude time savings on grading.

### Lawyers in the Loop: How Midpage Uses PromptLayer to Evaluate and Fine-Tune Legal AI Models

Midpage empowers their former litigator head of product to own 80 production prompts across their legal AI platform, using PromptLayer's evaluation pipelines to catch regressions before they reach hundreds of litigators. Their lawyers iterate on prompts and fine-tune models independently while engineers focus on infrastructure, achieving the domain expertise needed for trustworthy legal AI at scale.

### How Magid built enterprise-grade AI agents for content creation with PromptLayer

Magid built enterprise AI agents that process thousands of newsroom stories daily with near-zero errors, using PromptLayer's orchestration and custom evals to ensure journalism-grade accuracy. Their Collaborator suite achieved 80% journalist adoption and unlocks 2-6 FTEs per newsroom, with PromptLayer's evaluation framework enabling rapid iteration on complex multi-agent workflows.Retry

## Rigorously build great AI products.

### Prompt with experts

Building good AI is about understanding your users. That's why subject matter experts are the best prompt engineers.

Why use a prompt CMS?

### No-code prompt editor

Update and test prompts directly from the dashboard.

### Include non-technical domain experts

Enable product, marketing, and content teams to edit prompts directly.

### Avoid engineer bottlenecks

Decouple eng releases from prompt deploys.

### Version prompts

Edit and deploy prompt versions visually using our dashboard. No coding required.

Get started for free

### Organize versions

Comment, write notes, diff versions, and roll back changes.

### Deploy new prompts

Publish new prompts interactively for prod and dev.

### Clean up your repo

Prompts shouldn't be scattered through your codebase.

### A/B test prompts

Release new prompt versions gradually and compare metrics.

### Evaluate iteratively

Rigorously test prompts before deploying, with the help of human and AI graders.

Learn more

### Historical backtests

See how new prompt versions fair against historical data.

### Regression tests

Trigger evals to run every time a prompt is updated.

### Compare models

Test prompts against different models and parameters.

### One-off bulk jobs

Run prompt pipelines against a batch of test inputs.

### Monitor usage

Understand how your LLM application is being used, by whom, and how often. No need to jump back and forth to Mixpanel or Datadog.

See how it works

### Cost, latency stats

View high level stats about your LLM usage.

### Latency trends

Understand latency trends over time, by feature, and by model.

### Jump to bug report

Quickly find execution logs for a given user.

## Prompt with experts

### Prompt with actions

Building good AI is about understanding your users. That's why subject matter experts are the best prompt engineers.

Why use a prompt CMS?

### No-code prompt editor

Update and test prompts directly from the dashboard.

### Include non-technical stakeholders

Enable product, marketing, and content teams to edit prompts directly.

### Avoid engineer bottlenecks

Decouple eng releases from prompt deploys.

### Version prompts

Edit and deploy prompt versions visually using our dashboard. No coding required.

Get started for free

### Organize versions

Comment, write notes, diff versions, and roll back changes.

### Deploy new prompts

Publish new prompts interactively for prod and dev.

### Clean up your repo

Prompts shouldn't be scattered through your codebase.

### A/B test prompts

Release new prompt versions gradually and compare metrics.

### Evaluate iteratively

Rigorously test prompts before deploying, with the help of human and AI graders.

Learn more

### Historical backtests

See how new prompt versions fair against historical data.

### Regression tests

Trigger evals to run every time a prompt is updated.

### Compare models

Test prompts against different models and parameters.

### One-off bulk jobs

Run prompt pipelines against a batch of test inputs.

### Monitor usage

Understand how your LLM application is being used, by whom, and how often. No need to jump back and forth to Mixpanel or Datadog.

See how it works

### Cost, latency stats

View high level stats about your LLM usage.

### Latency trends

Understand latency trends over time, by feature, and by model.

### Jump to bug report

Quickly find execution logs for a given user.

## Use cases

Language Learning

GTM & Sales

Customer Support

## Personalized
language tutor apps

Busuu uses LLMs to provide every user on their app personalized language learning feedback for their speaking and conversational skills. The team iterates on feedback prompts that are stored in PromptLayer to tailor the right voice, run batch evaluations to examine feedback usefulness, and compare different models against eachother.

"*We use PromptLayer to evaluate changes to our instructions and compare the output across prompt versions and models to make sure our learners receive accurate and useful feedback to help them on their journey."
— Hannah Morris (Head of Learning Design @ Busuu)*

Learn More

## Automated AI sales
outbound

We use PromptLayer internally to build PromptLayer. Every time someone new signs up, it kicks off a PromptLayer agent that qualifies the lead, researches the company, and writes a highly-personalized outreach email. We spent hours in the dasbhoard versioning, tweaking, and test running the email writing prompt until it just right.

Read the blog post

## E-commerce
customer support

Gorgias has built an AI-powered customer helpdesk for Shopify stores. Their team of machine learning engineers and support specialists use PromptLayer to ensure that every user interaction is resolved successfully— refining prompts, replaying edge-cases, running regression evals, and surveying live traffic.

All their prompts, agents, tool calls are stored and iterated on from within PromptLayer.

Read a case-study

## What users are saying

Using PromptLayer, I completed many months' worth of work in a single week. It empowered me to drastically scale our content creation process, going from curriculum outlines to app-ready content that users could engage with immediately.

### Seung Jae Cha

AI Product Lead at Speak

PromptLayer has been a game-changer for us. It has allowed our content team to rapidly iterate on prompts, find the right tone, and address edge cases, all without burdening our engineers. This has been critical for creating an AI that truly connects with and supports our users.

### John Gilmore

VP of Operations at ParentLab

We iterate on prompts 10s of times every single day. It would be impossible to do this in a SAFE way without PromptLayer.

### Victor Duprez

Director of Engineering at Gorgias

PromptLayer is an example of a company that is solving a different lens of the problem, managing all your different prompts as they come in. The thing that I'm most excited about today is evals… I think it's a fundamental challenge for people using LLMs. When a new model comes out whether it's from OpenAI or some other provider, I don't know as the end user of that model how it's going to impact my use case. And, really, the only way to do that is to have a bunch of robust evals that you go and build…

### Logan Kilpatrick

Developer Relations at Gemini

Getting started with LLM APIs is easy. Moving to production and scale is hard. PromptLayer gives me out-of-the-box tooling to iterate, evaluate, monitor, and multisource my LLM-based apps, so I can spend less time building infrastructure. And just like how Wordpress allowed anyone to publish on the web, PromptLayer empowers non-developers and subject matter experts to iterate and improve on prompts without touching the code.

### Greg Baugues

Former Dir. of Developer Relations at Twilio

PromptLayer has become indispensable to our iteration process. Using the Prompt Registry, our team of mental health experts create tests, evaluate responses, and directly make edits to prompts without any engineering support. Even though our team is mostly non-technical, they use PromptLayer to improve the AI based on their personal clinical experience.

### Luis Voloch

CEO of Jimini Health

The team at PromptLayer has built a seriously impressive platform for prompt engineering. Their prompt CMS does a great job of allowing non-technical stakeholders to actually become the prompt engineers. It's the key that brings analytics, observability, and evals together for easy iteration.

### Aman Kishore

Founder at MirageML (aqd. Harvey)

If I'm at my desk and see that somebody's workflow went bad, it takes only 3 or 4 clicks. I go to PromptLayer, filter by the workflow ID, and I'm in. The information density means my time to being productive is really really good.

### Nick Bradford

Founder & CTO at Ellipsis

It takes a lot of work to build a good AI notepad like Granola. Especially because there is no ground-truth to compare against. PromptLayer makes it easy to version and build custom evals for your prompts.

### Chris Pedregal

CEO at Granola

### Seung Jae Cha

Product Lead at Speak

### John Gilmore

VP of Operations at ParentLab

We iterate on prompts 10s of times every single day. It would be impossible to do this in a SAFE way without PromptLayer.

### Victor Duprez

Director of Engineering at Gorgias

### Logan Kilpatrick

Gemini and OpenAI

### Greg Baugues

Former Director of Developer Relations at Twilio

### John Smith

AI Researcher at Stealth Mental Health Startup

### Aman Kishore

Founder at MirageML (aqd Harvey)

### Nick Bradford

Founder & CTO at Ellipsis

### Chris Pedregal

CEO at Granola

### Seung Jae Cha

Product Lead at Speak

### John Gilmore

VP of Operations at ParentLab

We iterate on prompts 10s of times every single day. It would be impossible to do this in a SAFE way without PromptLayer.

### Victor Duprez

Director of Engineering at Gorgias

### Logan Kilpatrick

Gemini and OpenAI

### Greg Baugues

Former Director of Developer Relations at Twilio

### John Smith

AI Researcher at Stealth Mental Health Startup

### Aman Kishore

Founder at MirageML (aqd Harvey)

### Nick Bradford

Founder & CTO at Ellipsis

### Chris Pedregal

CEO at Granola

## Collaborate without engineering

Move your prompts out of code and serve them from our CMS. Enable subject matter experts, like PMs or content writers, to edit and test prompt versions all through the PromptLayer dashboard.

## A high bar for privacy and security

Our customers work with extremely sensitive data. We take that responsibility seriously, and our security measures exceed industry standards. We are SOC 2 Type 2 compliant.

SOC 2 Type 2

HIPAA Compliant

## Our thoughts on prompt engineering and context design

See all tutorials and insights

Best practices

### Best Practices for Evaluating Back-and-Forth Conversational AI

Jul 02, 2025

Prompt engineering

### The Agentic System Design Interview: How to evaluate AI Engineers

Jul 11, 2025

Best practices

### What is Context Engineering?

Jul 10, 2025

Best practices

### Why LLMs Get Distracted and How to Write Shorter Prompts

Jul 14, 2025

Best practices

### How to Evaluate LLM Prompts Beyond Simple Use Cases

Apr 22, 2025

Best practices

### Prompt Management And Collaboration Using A CMS

Mar 7, 2024

Prompt engineering

### Our Favorite Prompts From The Tournament

Apr 4, 2024

Best practices

### Prompting Tips For Anthropic Claude

Jul 31, 2024

Best practices

### Building Better AI Systems

Jul 31, 2024

Best practices

### Prompting Tips For Anthropic Claude

Jul 31, 2024

## Model agnostic

One prompt template for every model.

## Prompt engineering pioneers

We are building a community for the real builders of AI: the prompt engineers. They come in all shapes and all sizes. Lawyers, doctors, educators, and even software engineers.

Get Started

## The First Platform Built For Prompt Engineering

Start for free

Made in NYC 🗽

hello@promptlayer.com

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