# OpenLIT vs Voker

OpenLIT records 6,028 monthly visits with -18.3% month-over-month growth and Free pricing. Voker records 3,234 monthly visits with -32.6% growth and Freemium, Free Trial, Contact for Pricing pricing.

| Metric | [OpenLIT](https://openaitools.app/tool/openlit) | [Voker](https://openaitools.app/tool/voker) |
| :--- | :--- | :--- |
| Website URL | https://openlit.io | https://voker.ai |
| Categories | Large Language Models (LLMs), AI Developer Tools, AI Monitor, Open Source AI Models | AI Agent, AI Monitor, AI For Data Analytics |
| Pricing Model | Free | Freemium, Free Trial, Contact for Pricing |
| Monthly Visits | 6,028 | 3,234 |
| MoM Growth Rate | -18.3% | -32.6% |
| Primary Market | United States | United States |
| Direct Visits | 2,375 | 1,272 |
| Review Score | 4.7 | 4.1 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## OpenLIT

OpenLIT positions itself as an agent harness engineering platform rather than a single-purpose monitoring tool. The idea is that the model is only one part of a reliable agent; the harness around it — prompts, context, tools, rules, and secrets — is what teams actually need to inspect and fix. OpenLIT brings those pieces together so you can trace what happened, evaluate whether it worked, guard the parts that should not break, and then change the harness without redeploying your application.

Instrumentation is deliberately flexible. Application teams can add an SDK and call openlit.init() to get tracing in-process, while teams that prefer zero-code coverage can use an eBPF-based controller in the Enterprise Edition. For infrastructure visibility there is a GPU collector for NVIDIA, AMD, and Intel cards, and if you already run OpenTelemetry tooling, you can simply point OTLP exporters at your OpenLIT deployment.

Because the project is OpenTelemetry-native and Apache 2.0 licensed, the data path stays portable. Traces and metrics can live in the OpenLIT UI and its ClickHouse-backed store, or be exported to Grafana, Datadog, or any OTLP backend. Storage is built on ClickHouse to keep queries fast across high-volume LLM and agent telemetry, and the whole stack can be self-hosted with Docker Compose or Kubernetes.

**Pricing & Plans:** The open-source edition is the free tier and is licensed under Apache 2.0, covering agent observability, evaluations, guardrails, Prompt Hub, Vault, OpenGround, coding-agent monitoring, and GPU metrics. There is no charge to self-host and no license key required. OpenLIT Cloud is not generally available yet. A separate Enterprise Edition adds capabilities such as the zero-code eBPF controller; check the official pricing page for current enterprise terms.

- **LLM and agent tracing:** Capture OpenTelemetry traces and metrics for every LLM call, tool invocation, retrieval, and agent step, and filter them by user, session, cost, latency, or custom metadata.
- **Evaluations on real traffic:** Score production traffic or experiments with LLM-as-a-judge, heuristic checks, or human review so you can measure accuracy, relevance, and safety over time.
- **Prompt Hub and versioning:** Manage and version prompts in Prompt Hub, then deploy, roll back, and update prompts without shipping new application code.
- **Vault for API keys:** Store and rotate OpenAI, Anthropic, and other LLM API keys outside your codebase with an encrypted, rotating secrets vault.
- **Cost, latency, and GPU monitoring:** Track spend, latency, and quality across AI workloads, and monitor GPU utilization, memory, temperature, and power for NVIDIA, AMD, and Intel hardware.

**Strengths:** OpenTelemetry-native design keeps traces and metrics portable and avoids vendor lock-in; Broad free open-source edition under Apache 2.0 with unlimited self-hosted use; Covers tracing, evals, guardrails, prompts, secrets, cost, and GPU monitoring in one platform; 56+ integrations across LLMs, agent frameworks, and vector databases, plus OTLP ingest from other tools

**Limitations:** Requires you to run and maintain your own ClickHouse and UI deployment to use the open-source edition; OpenLIT Cloud is not generally available, so there is no hosted option for teams that do not want to self-host; Some capabilities like the zero-code eBPF controller are tied to the Enterprise Edition; Feature surface is broad, so new users may need time to navigate the many modules

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

## Voker

Voker is an analytics platform built specifically for AI agents. As agents move from demos into production, teams run into a familiar problem: it is easy to see that something went wrong, but hard to understand why. Voker instruments LLM calls so you can observe agent behavior at the level that matters — individual sessions, recurring intents and the overall performance of each agent you ship.

Integration is designed to be minimal. Voker ships SDKs for JavaScript/TypeScript (@voker/voker) and Python (voker) that wrap existing provider clients. In most cases you change an import — for example, swapping the OpenAI client for the Voker-wrapped OpenAI provider — and then pass vokerAgent and vokerSession parameters to your LLM calls. Agents are named so they can be tracked separately, and sessions are unique per conversation, giving Voker the structure it needs to analyze behavior. Providers with explicit wrapping support include OpenAI, Anthropic, Gemini and the Vercel AI SDK, and anything else can report through the REST API or the base SDK.

Beyond tracing, Voker is oriented toward improvement. Intent detection shows what users actually ask agents and how well those requests are served — a direct input to prompt engineering and product decisions. The site also emphasizes a frictionless onboarding path, including a setup prompt you can paste into an AI coding assistant so the SDK, API key and first event are configured automatically, typically in a couple of minutes. Voker is aimed at developers and teams running conversational AI in production who want self-service analytics rather than a heavyweight enterprise observability deployment.

**Pricing & Plans:** Voker offers a free tier alongside paid plans, with a free trial available and contact options for larger or custom requirements; see the site's pricing page for current figures.

- **SDK wrapping for LLM providers:** Wrap your existing OpenAI, Anthropic, Gemini or Vercel AI SDK client and every call is instrumented automatically with agent and session context.
- **Agent and session tracking:** Voker organizes activity by agent and by session, so you can follow a single conversation end to end and see how it developed.
- **Intent detection and analysis:** Understand which intents users bring to your agent and how well the agent handles them, revealing where prompts or flows need work.
- **Custom event instrumentation:** If you need more control, create custom events through the SDK or REST API to capture exactly the behavior you care about.
- **AI-assisted setup:** A guided setup prompt can be pasted into your AI coding tool to scaffold the SDK, add your API key and instrument a first event in about two minutes.

**Strengths:** Purpose-built for agent and conversation analytics rather than generic logging; Minimal integration — often just swapping an import and adding two parameters; Supports the major providers (OpenAI, Anthropic, Gemini, Vercel AI SDK) in JS/TS and Python; Intent detection turns raw traces into actionable improvement signals

**Limitations:** Requires code changes — you must swap SDK imports and pass agent/session parameters; Value depends on teams already running agents in production with volume worth analyzing; SDK depth is strongest for OpenAI, Anthropic, Gemini and Vercel AI SDK rather than every framework; Niche focus means it complements rather than replaces a broad APM suite

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

## Frequently Asked Questions

### How do OpenLIT and Voker compare in monthly traffic?

OpenLIT has 6,028 monthly visits, while Voker has 3,234. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

OpenLIT has a month-over-month growth rate of -18.3%; Voker has -32.6%.

### How does pricing compare?

OpenLIT: Free. The open-source edition is the free tier and is licensed under Apache 2.0, covering agent observability, evaluations, guardrails, Prompt Hub, Vault, OpenGround, coding-agent monitoring, and GPU metrics. There is no charge to self-host and no license key required. OpenLIT Cloud is not generally available yet. A separate Enterprise Edition adds capabilities such as the zero-code eBPF controller; check the official pricing page for current enterprise terms. Voker: Freemium, Free Trial, Contact for Pricing. Voker offers a free tier alongside paid plans, with a free trial available and contact options for larger or custom requirements; see the site's pricing page for current figures.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [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) |
| 2 | [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) |
| 3 | [LiteLLM](https://openaitools.app/tool/litellm) | 576,967 | +7.9% | Freemium, Contact for Pricing | One open-source AI gateway for 100+ LLM providers | [.md](https://openaitools.app/tool/litellm.md) |
| 4 | [Treg](https://openaitools.app/tool/treg) | 452,935 | +223.4% | Freemium | One key for 4,100+ agent tools, pay per call | [.md](https://openaitools.app/tool/treg.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 | [Portkey](https://openaitools.app/tool/portkey-ai) | 195,650 | -9.4% | Freemium, Paid, Contact for Pricing | AI gateway, observability and guardrails for production LLM apps | [.md](https://openaitools.app/tool/portkey-ai.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Respan](https://openaitools.app/tool/respan) | 91,503 | -14.5% | Freemium | Open-source AI gateway with observability and evals built in | [.md](https://openaitools.app/tool/respan.md) |
| 10 | [PromptLayer](https://openaitools.app/tool/promptlayer) | 85,899 | -4.6% | Free Trial, Contact for Pricing | The collaboration layer for AI engineering teams | [.md](https://openaitools.app/tool/promptlayer.md) |

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Source: https://openaitools.app/compare/openlit-vs-voker

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