# Cencurity vs PromptLayer

Cencurity records 0 monthly visits with 0% month-over-month growth and Free pricing. PromptLayer records 85,899 monthly visits with -4.6% growth and Free Trial, Contact for Pricing pricing.

| Metric | [Cencurity](https://openaitools.app/tool/cencurity) | [PromptLayer](https://openaitools.app/tool/promptlayer) |
| :--- | :--- | :--- |
| Website URL | https://cencurity.com | https://promptlayer.com |
| Categories | AI Developer Tools, AI Agent, Large Language Models (LLMs), Log Management | Prompt Engineering, Large Language Models (LLMs), AI Monitor, AI Developer Tools |
| Pricing Model | Free | Free Trial, Contact for Pricing |
| Monthly Visits | 0 | 85,899 |
| MoM Growth Rate | 0% | -4.6% |
| Primary Market | Global | United States |
| Direct Visits | 0 | 14,092 |
| Review Score | 4.2 | 4.5 |
| Saved Count | 0 | 3 |
| Supported Platforms | Website | Website |

## Cencurity

Cencurity is built for teams that have started shipping AI agents and AI-assisted coding workflows and now need a control point over what those agents send and receive. The product places itself between your agents, IDEs and the LLM providers they depend on, so a single integration gives consistent behavior across models, tools and environments without rewriting existing workflows. A centralized dashboard shows every agent call in real time, including requests, responses, latency, policy hits, redactions and blocks.

The core protection model is policy-first. Cencurity detects policy violations as traffic flows, prioritizes the events that matter, and applies zero-click guardrails so security does not become a manual review queue. Sensitive data is identified at the edge and stopped before it reaches a model or a user, and the same pipeline can proxy LLM traffic while automatically redacting sensitive content. Because policies can be run in dry-run mode first, teams can measure the impact of a rule before they enforce it and roll it out gradually.

Operationally, Cencurity is aimed at developers rather than security analysts alone: getting started means opening the repository and following a quickstart, and webhook notifications push verified alerts into tools like Slack and Jira rather than flooding inboxes. Combined with end-to-end log analysis that lets you search, filter and correlate requests, responses and policy decisions, this makes it a practical way to add governance and an audit trail to AI coding without slowing delivery.

**Pricing & Plans:** Cencurity offers a free entry point: the Get Started Free path opens the public repository and quickstart documentation. The site lists no published paid tiers, so larger or managed deployments likely require contacting the team.

- **Real-time leak protection:** Automatically detects and blocks secrets, PII and risky model output before it reaches users or upstream providers.
- **LLM proxy with redaction:** Routes LLM traffic through the gateway and redacts sensitive data inline, so agents keep working while secrets stay out of prompts.
- **Centralized security dashboard:** One pane of glass for requests, responses, latency, policy hits, redactions and blocks across every agent call.
- **End-to-end log analysis:** Search, filter and correlate requests, responses and policy decisions to pinpoint risk in seconds.
- **Dry-run rollout and webhooks:** Measure a policy's impact before enforcement, then push only verified alerts to Slack, Jira and similar tools.

**Strengths:** Covers secrets, PII and risky output in one gateway rather than separate point tools; Works with existing agents and IDEs through one integration, no rewrites required; Dry-run mode lets teams validate policies before enforcing them; Free repository-based quickstart makes evaluation easy for developers

**Limitations:** Pricing beyond the free entry point is not published on the site; Requires developer involvement to deploy and configure policies

[Profile (Markdown)](https://openaitools.app/tool/cencurity.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 Cencurity and PromptLayer compare in monthly traffic?

Cencurity has 0 monthly visits, while PromptLayer has 85,899. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Cencurity has a month-over-month growth rate of 0%; PromptLayer has -4.6%.

### How does pricing compare?

Cencurity: Free. Cencurity offers a free entry point: the Get Started Free path opens the public repository and quickstart documentation. The site lists no published paid tiers, so larger or managed deployments likely require contacting the team. 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 | [Datadog](https://openaitools.app/tool/datadog) | 5,175,760 | -4.8% | Freemium, Free Trial, Paid, Contact for Pricing, Free | Unified observability, security and incident response for cloud-scale engineering teams | [.md](https://openaitools.app/tool/datadog.md) |
| 2 | [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) |
| 3 | [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) |
| 4 | [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) |
| 5 | [Mindgard](https://openaitools.app/tool/mindgard) | 153,455 | +1.3% | Contact for Pricing | Attack-led AI security testing and red teaming | [.md](https://openaitools.app/tool/mindgard.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 | [Lakera Guard](https://openaitools.app/tool/lakera-guard) | 88,435 | -24% | Contact for Pricing | Runtime security that stops prompt injection and data leaks in LLM apps | [.md](https://openaitools.app/tool/lakera-guard.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/cencurity-vs-promptlayer

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