# Activepieces vs Superlog

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. Superlog records 1,313 monthly visits with -75.2% growth and Freemium, Paid, Contact for Pricing, Free pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [Superlog](https://openaitools.app/tool/superlog) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://superlog.sh |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | AI Agent, AI Code Assistant, AI Developer Tools, AI Code Review |
| Pricing Model | Freemium | Freemium, Paid, Contact for Pricing, Free |
| Monthly Visits | 258,553 | 1,313 |
| MoM Growth Rate | +1.5% | -75.2% |
| Primary Market | United States | Global |
| Direct Visits | 111,328 | 507 |
| Review Score | 4.6 | 4.3 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Activepieces

Activepieces is an AI-first automation platform built around the idea that a team's agents and its people should share one workspace. At the center are AI agents: you describe a job in plain words and the agent works out the steps, the order and which tools to open across your connected apps and any MCP server you point it at. Sensitive steps can be gated behind human approval, so money, customer and production actions stay under control.

Underneath the agent layer sits a mature workflow engine with a visual builder. Chat can draft most of a flow, while branching, retries, waitpoints, subflows, error handling and human approvals handle the hard cases. Where a step needs real logic, you can drop into inline TypeScript and keep the rest visual. Chat, Tables (a lightweight structured data layer), a knowledge base and an MCP server round out the platform so agents and teammates operate on the same data.

The project is open source at its core, with hundreds of contributors maintaining MIT-licensed app pieces, and it deploys flexibly: Activepieces Cloud, your own Docker or Kubernetes infrastructure, or a fully air-gapped install. Enterprise controls include projects and access roles, SSO via Okta or Entra, secret managers such as HashiCorp Vault, audit logs streamed to your SIEM, and bring-your-own AI model keys from Anthropic, OpenAI, AWS Bedrock or Google Gemini.

**Pricing & Plans:** Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure.

- **AI agents from plain language:** Describe a task in everyday words and the agent determines the steps, chooses tools from your connected apps and MCP servers, and pauses for approval on sensitive actions.
- **Visual flow builder with inline TypeScript:** Build automations on a canvas with branching, retries, waitpoints, subflows and error handling, then write inline TypeScript for the steps that need real code.
- **770+ open-source app connectors:** Every piece is MIT-licensed and community-built, covering the apps you already run, with an HTTP piece for any REST or GraphQL endpoint with auth and pagination handled.
- **Chat, Tables and knowledge base:** Draft flows by chatting, store structured data in Tables that flows and agents can read and write, and keep internal documents searchable by every agent.
- **Enterprise deployment and governance:** Run on the managed cloud, your Docker/Kubernetes stack or air-gapped, with projects, SSO, role-based access, secret managers, audit logs and bring-your-own AI keys.

**Strengths:** Open-source core with MIT-licensed pieces and a genuinely self-hostable build; Strong blend of AI agents, a visual builder and inline TypeScript; Enterprise-grade controls including SSO, roles, secret managers and audit streaming; Large connector library plus an HTTP piece for anything not covered

**Limitations:** The breadth of agents, tables, flows and MCP features can overwhelm new users; Some advanced enterprise capabilities are reserved for paid and self-managed plans; Self-hosting means you own upgrades, scaling and reliability

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

## Superlog

Superlog positions itself as "monitoring for the AI era." Instead of only charting the telemetry you already send, it actively audits it: an Overview check flags missing logs, missing traces, and tags that violate OpenTelemetry semantic conventions, then hands your coding agent a ready-made prompt to close each gap.

On the frontend side, the browser SDK captures exceptions that never reach your backend — a checkout page can return HTTP 200 and still crash a user's session. Because Superlog maps stack traces through source maps, an agent can point at the exact failing line and turn the fix into a permanent alert or synthetic test.

The automation layer is where the product differentiates. You define a trigger (a Sentry checkout error, a Slack message, a webhook, or a schedule), grant the agent scoped repositories and connected accounts, and give it a runbook: trace the failed checkout, check recent deploys, identify affected customers. Investigations execute in isolated sandboxes and report back in the alert thread with the failing trace plus a pull request for review. Superlog also checks prior reports so recurring alerts get progressively less noisy.

It is designed to sit alongside your existing stack rather than replace it. Sentry, Datadog, Grafana, Google Cloud, PostHog, GitHub, Slack, and AWS all connect, and you can either send telemetry through OpenTelemetry or keep it with your current provider. Teams can bring their own model keys or ChatGPT/Codex subscriptions and switch providers without rebuilding workflows.

**Pricing & Plans:** Free tier at $0/month including a $5 one-time Superlog AI grant and 2 cloud machine hours. Pro is $100/month (50 machine hours, up to 3 concurrent machines), Team is $200/month (unlimited seats, 500 machine hours, up to 10 machines, shared workspaces), and Enterprise is custom with SSO/SAML, audit logs, and a support SLA. Telemetry is billed per event: every plan includes 1M spans, 5M logs, and 10M metric points monthly, then $0.60 per million spans, $0.50 per million logs, and $0.20 per million metric points, with 30-day retention.

- **Telemetry gap detection:** Overview scans for missing logs, missing traces, and tags that break OpenTelemetry conventions, then generates a suggested agent prompt to repair each gap.
- **Browser error capture with source maps:** A frontend SDK records exceptions that a 200 response would otherwise hide, and source maps resolve them to the exact line that failed.
- **Runbook-driven investigation automations:** Trigger agents from Sentry, Slack, webhooks, or a schedule, scope their repositories and accounts, and have them reply in the alert thread with traces and pull requests.
- **Bring your own model and telemetry backend:** Use your own API key or ChatGPT/Codex subscription, pick your model and harness, and connect existing tools like Sentry, Datadog, or Grafana over OpenTelemetry.
- **Isolated sandboxes and scoped access:** Each agent works inside an isolated investigation sandbox with only the repositories and connected accounts you explicitly allow, with SSO, SAML, and audit logs on Enterprise.

**Strengths:** Actively audits telemetry for gaps instead of only visualizing what is sent; Agents operate with scoped repository access inside isolated sandboxes; Works alongside Sentry, Datadog, Grafana, and cloud providers rather than forcing a migration; Transparent, usage-based telemetry pricing published per million events

**Limitations:** Cloud machine hours and AI usage are separate meters, so cost needs monitoring as automations scale; Telemetry retention is capped at 30 days, with longer retention requiring a conversation with sales; Bring-your-own-model setups mean you manage provider keys and billing yourself

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

## Frequently Asked Questions

### How do Activepieces and Superlog compare in monthly traffic?

Activepieces has 258,553 monthly visits, while Superlog has 1,313. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Activepieces has a month-over-month growth rate of +1.5%; Superlog has -75.2%.

### How does pricing compare?

Activepieces: Freemium. Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure. Superlog: Freemium, Paid, Contact for Pricing, Free. Free tier at $0/month including a $5 one-time Superlog AI grant and 2 cloud machine hours. Pro is $100/month (50 machine hours, up to 3 concurrent machines), Team is $200/month (unlimited seats, 500 machine hours, up to 10 machines, shared workspaces), and Enterprise is custom with SSO/SAML, audit logs, and a support SLA. Telemetry is billed per event: every plan includes 1M spans, 5M logs, and 10M metric points monthly, then $0.60 per million spans, $0.50 per million logs, and $0.20 per million metric points, with 30-day retention.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | The AI coding agent for building ambitious software | [.md](https://openaitools.app/tool/cursor.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 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Massive prebuilt app ecosystem and polished UX, but significantly more expensive and proprietary. | [.md](https://openaitools.app/tool/zapier-com.md) |
| 4 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Powerful open-source workflow automation with robust self-hosting options, but steeper learning curve than Activepieces. | [.md](https://openaitools.app/tool/n8n.md) |
| 5 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | The coding agent that learns your coding taste | [.md](https://openaitools.app/tool/command-code.md) |
| 6 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | Streamlined interface for deploying custom AI agents, but less flexible for traditional data integration pipelines. | [.md](https://openaitools.app/tool/mindstudio.md) |
| 7 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Stronger focus on RAG knowledge bases and LLM application development, but less general business automation. | [.md](https://openaitools.app/tool/dify-ai.md) |
| 8 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Excellent browser and web scraping automation features for AI agents, but fewer standard enterprise app integrations. | [.md](https://openaitools.app/tool/gumloop.md) |
| 9 | [Augment Code](https://openaitools.app/tool/augment-code) | 326,215 | +24.1% | Freemium, Free Trial, Contact for Pricing | Agent orchestration platform for your whole software development lifecycle | [.md](https://openaitools.app/tool/augment-code.md) |
| 10 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | Enterprise-grade security and governance for workflows, but geared more toward security and IT operations. | [.md](https://openaitools.app/tool/tines.md) |

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Source: https://openaitools.app/compare/activepieces-vs-superlog

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