# Agenta vs Langtail

Agenta records 45,760 monthly visits with +29.5% month-over-month growth and Freemium pricing. Langtail records 4,213 monthly visits with +10% growth and Freemium, Paid pricing.

| Metric | [Agenta](https://openaitools.app/tool/agenta) | [Langtail](https://openaitools.app/tool/langtail) |
| :--- | :--- | :--- |
| Website URL | https://www.agenta.ai | https://langtail.com |
| Categories | AI Developer Tools, Prompt Engineering, Large Language Models (LLMs), AI Agent | Large Language Models (LLMs), AI Testing, No-Code&Low-Code, Prompt Engineering |
| Pricing Model | Freemium | Freemium, Paid |
| Monthly Visits | 45,760 | 4,213 |
| MoM Growth Rate | +29.5% | +10% |
| Primary Market | United States | United States |
| Direct Visits | 17,206 | 1,680 |
| Review Score | 4.4 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Agenta

Agenta positions itself as an open-source workspace where teams build AI agents and AI co-workers rather than one-off prompts. You can start from pre-built agent templates, give an agent access to models and tools, and run it from a chat surface, Slack or Telegram so the work happens where your team already communicates. Agents can browse, read and write files, and run scheduled automations that trigger from your connected systems.

What sets Agenta apart is its focus on operational control. Agents connect to more than a thousand integrations and MCP servers, secrets live in a vault the agent can use but not read, and permissions and approval steps decide which actions run automatically and which need a human sign-off. Every run is logged with duration, token usage and cost, so you can trace why an agent produced a certain result and iterate on it with feedback.

For engineering teams, Agenta ships as MIT-licensed software you can self-host with Docker Compose or Helm, keeping agents and data on your own infrastructure with no vendor lock-in. A managed cloud option is available for teams that prefer not to run the stack themselves, and both share the same workspace concepts of agents, skills, sessions and automations.

**Pricing & Plans:** Freemium. The open-source edition is MIT-licensed and free to self-host; cloud access is offered alongside it, with a demo available for larger teams. Exact seat and usage limits are listed on the pricing page.

- **Agent and co-worker builder:** Assemble agents from templates or from scratch, give them models, skills and tools, and run them from a chat UI, Slack or Telegram.
- **MCP connections and 1,000+ integrations:** Wire agents into Notion, GitHub, HubSpot, Slack, Linear, Drive and more over MCP, and swap tools or skills without rewriting the agent.
- **Evaluations and run observability:** Score agent outputs, collect feedback and inspect every run with duration, token usage and cost logging so improvements are measurable.
- **Guardrails, approvals and a secret vault:** Decide which actions run unattended and which require approval, while credentials stay in a vault your agent can use but cannot read.
- **Self-hosting with MIT license:** Deploy the full workspace on your own infrastructure with Docker Compose or Helm charts and keep agents and data on-premises.

**Strengths:** Open-source and MIT-licensed, so it can be self-hosted without vendor lock-in; Connects to over a thousand tools and MCP servers instead of a fixed integration list; Built-in evaluation and full run logging with token and cost tracking; Approval gates and a secret vault keep agents within human control

**Limitations:** The workspace concept is broad, so new users need time to map it to their workflow; Self-hosting requires someone comfortable running containers and Helm charts; Some enterprise features are only fully explained after contacting sales

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

## 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)

## Frequently Asked Questions

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

Agenta has 45,760 monthly visits, while Langtail has 4,213. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Agenta has a month-over-month growth rate of +29.5%; Langtail has +10%.

### How does pricing compare?

Agenta: Freemium. Freemium. The open-source edition is MIT-licensed and free to self-host; cloud access is offered alongside it, with a demo available for larger teams. Exact seat and usage limits are listed on the pricing page. 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.

## 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 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) |
| 3 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Run many coding agents in parallel, each in its own worktree | [.md](https://openaitools.app/tool/orca.md) |
| 4 | [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) |
| 5 | [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) |
| 6 | [LobeHub](https://openaitools.app/tool/lobehub) | 654,548 | -25% | Freemium | Put always-on AI agents on your team chat | [.md](https://openaitools.app/tool/lobehub.md) |
| 7 | [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) |
| 8 | [Sim AI](https://openaitools.app/tool/sim-ai) | 140,953 | +20.6% | Freemium, Paid (per user/month), and Enterprise with custom pricing; self-hosting free under Apache 2.0 | Open-source workspace to build, deploy and govern AI agents | [.md](https://openaitools.app/tool/sim-ai.md) |
| 9 | [Agno](https://openaitools.app/tool/agno) | 140,302 | -3.3% | Contact for Pricing, Free | Self-driving agent platform you run in your own cloud | [.md](https://openaitools.app/tool/agno.md) |
| 10 | [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) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)