# Langtail vs PromptLayer

Langtail records 4,213 monthly visits with +10% month-over-month growth and Freemium, Paid pricing. PromptLayer records 85,899 monthly visits with -4.6% growth and Free Trial, Contact for Pricing pricing.

| Metric | [Langtail](https://openaitools.app/tool/langtail) | [PromptLayer](https://openaitools.app/tool/promptlayer) |
| :--- | :--- | :--- |
| Website URL | https://langtail.com | https://promptlayer.com |
| Categories | Large Language Models (LLMs), AI Testing, No-Code&Low-Code, Prompt Engineering | Prompt Engineering, Large Language Models (LLMs), AI Monitor, AI Developer Tools |
| Pricing Model | Freemium, Paid | Free Trial, Contact for Pricing |
| Monthly Visits | 4,213 | 85,899 |
| MoM Growth Rate | +10% | -4.6% |
| Primary Market | United States | United States |
| Direct Visits | 1,680 | 14,092 |
| Review Score | 4.4 | 4.5 |
| Saved Count | 0 | 3 |
| Supported Platforms | Website | Website |

## Langtail

Langtail is built around a single premise: LLM output is unpredictable, and the way to regain control is to treat prompts as managed production assets. Instead of scattering prompt strings through application code, teams write them in a spreadsheet-like editor, run them through evaluation suites, version the changes, and invoke them by name from a typed SDK or the OpenAPI interface. A TypeScript SDK with code completion makes the same prompts callable from application code, so what a product manager edits in the UI is exactly what ships.

The observability layer is what makes testing meaningful. Every invocation is logged, so you can inspect inputs, outputs, latency, and cost, then trace a bad answer back to a prompt change or a model switch. Evaluation supports natural-language assertions, regex-style pattern matching, or fully custom code, and teams can experiment with models and parameters side by side to find the combination that performs best. Langtail positions this as essential infrastructure rather than a nice-to-have, using publicised incidents where unguarded chatbots misfired to make the point.

Security rounds out the platform. The AI Firewall is a one-click integration that inspects traffic for prompt injection, denial-of-service patterns, and information leakage, with content filtering you can tune and alerts for unusual activity. The platform works with all major model providers and exposes a public API and status page; enterprise customers can self-host for maximum data control, while a free tools section offers extras such as a prompt improver and an LLM price comparison outside the paid plans.

**Pricing & Plans:** Free tier of $0/month with unlimited users, 2 prompts or assistants, 1,000 logs per month, and 30 days of data retention. Pro is $99/month for a single user with 20 prompts, unlimited logs, 90-day retention. Team is $499/month for 10 users with unlimited prompts, unlimited logs, one-year retention, and Radars & Alerts. Enterprise is custom and adds the AI Firewall, self-hosting, and dedicated support. Prices exclude VAT.

- **Spreadsheet-style prompt editor:** Build, test, and version prompts in a table-based editor that anyone comfortable with spreadsheets can use.
- **Automated evaluation and test runs:** Add natural-language assertions, pattern matching, or custom code checks and run them over datasets to catch regressions.
- **Request logging and observability:** Trace every request and response, inspect latency and cost, and diagnose why an LLM answered the way it did.
- **AI Firewall and safety checks:** One-click AI Firewall blocks prompt injection, denial-of-service attempts, and information leaks with customisable content filtering and alerts.
- **Multi-provider support and versioning:** Compare OpenAI, Anthropic, Gemini, Mistral and more, and roll out prompt changes through versioned environments.

**Strengths:** Non-developers can manage prompts without touching the codebase; Evaluation and log inspection live alongside prompt editing; Works across all major LLM providers, avoiding lock-in; Self-hosting on Enterprise answers strict data-control requirements

**Limitations:** Pro plan supports only a single user, so small teams may need the pricier Team tier; Log limits and retention windows differ sharply between tiers; Feature depth is aimed at production teams rather than one-off prompt experiments; Self-hosting and the AI Firewall sit behind the Enterprise plan

[Profile (Markdown)](https://openaitools.app/tool/langtail.md)

## PromptLayer

PromptLayer targets the gap between prototyping with an LLM API and running that application reliably in production. It packages the tooling teams usually end up building themselves: a prompt registry, a visual CMS for editing and versioning prompts, an evaluation harness, and an observability stack that ties production traffic back to the prompt versions that generated it.

The core insight is that prompt quality is a product concern, not only an engineering one. Because prompts live in a dashboard rather than scattered through a codebase, domain experts — product managers, marketers, curriculum designers, support leads — can edit and test them directly, while engineers keep control over what actually ships. Version history, diffs, comments and rollbacks keep that collaboration auditable.

Evidence comes from evaluation and production. Teams define datasets, run automated and human grading, set up regression tests that fire whenever a prompt changes, and backtest new versions against historical data. In production, traces connect each request to its prompt version, so quality, cost and latency can be compared side by side. Agent workflows get the same treatment: prompts, tool calls, evaluations and logs stay in one place for multi-step runs.

**Pricing & Plans:** PromptLayer has a free tier and three paid tiers. Free is $0/month with 5 users, 2.5k requests per month, 1 workspace, 250 eval cell executions and 10MB datasets. Pro is $49/month and adds unlimited playgrounds, unlimited workspaces and 150MB datasets. Team is $500/month with 25 users, 100k+ requests, 7.5k+ eval cell executions and 1GB datasets. Enterprise offers custom limits plus RBAC, deployment approvals, HIPAA with BAA, self-hosted or EU hosting and dedicated support. Overage is billed per transaction (about $0.003 on Pro, $0.002 on Team).

- **No-code visual prompt CMS:** Edit, version, diff and roll back prompts from a visual dashboard with no coding, so product, marketing and content teams can iterate on prompts while engineers keep control of the deploy.
- **Evaluations and regression testing:** Run dataset-backed tests with human and AI graders, trigger regression evals whenever a prompt changes, backtest new versions against historical data and compare prompts across models.
- **Observability and tracing:** Connect production traces to the exact prompt version that produced them and inspect failures, cost, latency and token usage by feature, model or user.
- **Agent workflow support:** Build, trace and improve agent workflows with prompts, tool calls, evaluations and logs in one place, so multi-step runs can be tested before they ship.
- **A/B testing and usage analytics:** Release new prompt versions gradually, compare live metrics, and see exactly how the LLM application is being used, by whom and how often, without jumping to a separate analytics tool.

**Limitations:** Team plan jumps to $500/month, which is steep for small teams that outgrow Pro; Usage beyond plan limits is billed per transaction, so heavy LLM traffic needs forecasting; Role-based access controls, deployment approvals and SSO are Enterprise-only; Live in the developer ecosystem, so setup expects an LLM API and engineering involvement

[Profile (Markdown)](https://openaitools.app/tool/promptlayer.md)

## Frequently Asked Questions

### How do Langtail and PromptLayer compare in monthly traffic?

Langtail has 4,213 monthly visits, while PromptLayer has 85,899. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Langtail has a month-over-month growth rate of +10%; PromptLayer has -4.6%.

### How does pricing compare?

Langtail: Freemium, Paid. Free tier of $0/month with unlimited users, 2 prompts or assistants, 1,000 logs per month, and 30 days of data retention. Pro is $99/month for a single user with 20 prompts, unlimited logs, 90-day retention. Team is $499/month for 10 users with unlimited prompts, unlimited logs, one-year retention, and Radars & Alerts. Enterprise is custom and adds the AI Firewall, self-hosting, and dedicated support. Prices exclude VAT. PromptLayer: Free Trial, Contact for Pricing. PromptLayer has a free tier and three paid tiers. Free is $0/month with 5 users, 2.5k requests per month, 1 workspace, 250 eval cell executions and 10MB datasets. Pro is $49/month and adds unlimited playgrounds, unlimited workspaces and 150MB datasets. Team is $500/month with 25 users, 100k+ requests, 7.5k+ eval cell executions and 1GB datasets. Enterprise offers custom limits plus RBAC, deployment approvals, HIPAA with BAA, self-hosted or EU hosting and dedicated support. Overage is billed per transaction (about $0.003 on Pro, $0.002 on Team).

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |
| 3 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |
| 4 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 5 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) |
| 6 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Build, simulate, evaluate and monitor self-improving AI agents | [.md](https://openaitools.app/tool/future-agi.md) |
| 7 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Evaluate, monitor, and govern your AI applications in production | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 8 | [testRigor](https://openaitools.app/tool/testrigor-com) | 105,865 | -2.7% | Free Trial, Contact for Pricing, Free | Write end-to-end test automation in plain English, no code required | [.md](https://openaitools.app/tool/testrigor-com.md) |
| 9 | [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | -3.3% | Freemium, Paid, Contact for Pricing | Standardize LLM evaluation, observability, and red teaming across your whole org | [.md](https://openaitools.app/tool/confident-ai.md) |
| 10 | [HumanLayer](https://openaitools.app/tool/humanlayer) | 63,865 | -33.4% | Freemium | A multiplayer control plane for AI coding agents | [.md](https://openaitools.app/tool/humanlayer.md) |

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Source: https://openaitools.app/compare/langtail-vs-promptlayer

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