Codegate is an open-source security gateway and multiplexing framework for AI agentic systems. Developed by Stacklok, it provides secure workspaces and policy-based access control, enabling developers to build and manage complex multi-agent applications safely and efficiently.
Sylph AI is a development platform designed to maximize the potential of LLM applications. It features AdalFlow, a leading open-source library for building and auto-optimizing LLM task pipelines, and an AI Teammate that provides expert guidance throughout the entire development workflow, from ideation to production.
Product overview
codegate Product overview
Codegate is an open-source security gateway and multiplexing framework for AI agentic systems. Developed by Stacklok, it provides secure workspaces and policy-based access control, enabling developers to build and manage complex multi-agent applications safely and efficiently.
Sylph AI Product overview
Sylph AI is a development platform designed to maximize the potential of LLM applications. It features AdalFlow, a leading open-source library for building and auto-optimizing LLM task pipelines, and an AI Teammate that provides expert guidance throughout the entire development workflow, from ideation to production.
Detailed feature comparison
| Feature | codegate | Sylph AI |
|---|---|---|
| Primary category | Agentic Frameworks | Libraries |
| Added | 2025-08-16 | 2025-08-16 |
| Pricing | Free | Freemium |
| Official website | github.com | www.sylph.ai |
| Product type | App | Website |
| Performance data | ||
| User rating | Not verified | Not verified |
| Comments | 0 | 0 |
| Monthly visits | 636.1M | 22.5K |
| Monthly growth | 0.8% | -13.2% |
| Favorites | 108 | 136 |
| Details | View details | View details |
codegate vs Sylph AI monthly traffic
Compare codegate and Sylph AI by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the codegate vs Sylph AI monthly traffic comparison, codegate currently shows 636.1M visits and Sylph AI shows 22.5K; codegate has about 28,321.6 times the visible traffic of Sylph AI, an absolute difference of about 636.1M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
codegate is registered at the github.com/stacklok subpage. Because the current data does not state whether other host pages are excluded, treat this as domain-level context rather than independent traffic for one product or project.
codegate monthly traffic:
Latest traffic
Monthly traffic trend
- 2026/1: 542.6M Monthly visits
- 2026/2: 534.8M Monthly visits
- 2026/3: 634.3M Monthly visits
- 2026/4: 631M Monthly visits
- 2026/5: 636.1M Monthly visits
Top regions
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 36.14% | 229.9M |
| 🇨🇳China | 22.96% | 146M |
| 🇮🇳India | 17.41% | 110.7M |
| 🇷🇺Russia | 15.84% | 100.8M |
| 🇩🇪Germany | 7.65% | 48.7M |
Traffic sources
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 82.14% | 522.5M |
| Referral | 16.14% | 102.7M |
| 1.72% | 10.9M |
Search keywords
Sylph AI monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 8.2K Monthly visits
- 2026/1: 12K Monthly visits
- 2026/2: 18.6K Monthly visits
- 2026/3: 32.7K Monthly visits
- 2026/4: 25.9K Monthly visits
- 2026/5: 22.5K Monthly visits
Top regions
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 70.84% | 15.9K |
| 🇮🇳India | 9.68% | 2.2K |
| 🇮🇩Indonesia | 6.55% | 1.5K |
| 🇻🇳Vietnam | 6.47% | 1.5K |
| 🇧🇷Brazil | 6.46% | 1.5K |
Traffic sources
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 75.46% | 16.9K |
| Referral | 24.54% | 5.5K |
Search keywords
Usage comparison
Compare the core capabilities of codegate and Sylph AI
codegate Core features
Sylph AI Core features
Use cases
codegate Use cases
Sylph AI Use cases
codegate vs Sylph AI:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth codegate vs Sylph AI comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. codegate is primarily listed under “Agentic Frameworks”, while Sylph AI is primarily listed under “Libraries”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (codegate: Agentic Frameworks; Sylph AI: Libraries); Product type (codegate: App; Sylph AI: Website); Pricing (codegate: Free; Sylph AI: Freemium); Monthly visits (codegate: 636.1M; Sylph AI: 22.5K); Monthly growth (codegate: 0.8%; Sylph AI: -13.2%). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the codegate vs Sylph AI monthly traffic comparison, codegate currently shows 636.1M visits and Sylph AI shows 22.5K; codegate has about 28,321.6 times the visible traffic of Sylph AI, an absolute difference of about 636.1M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
codegate is registered at the github.com/stacklok subpage. Because the current data does not state whether other host pages are excluded, treat this as domain-level context rather than independent traffic for one product or project.
codegate is registered under a github.com subpath, so its large visible total may include the host platform. The current data does not justify choosing codegate for traffic alone; shortlist by unique taxonomy and use case, then validate with the same tasks.
Product positioning, use cases, and roles
codegate and Sylph AI currently overlap in shared categories: Automation; shared tags: AI agent, automation, developer tools, open source, and python. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
codegate's unique categories/tags are Agentic Frameworks, Security, agentic framework, AI security, DevSecOps, kubernetes, and security gateway; Sylph AI's are Libraries, Llm, llm, model fine-tuning, optimization, pipeline, and prompt engineering. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
codegate has no verified rating, 0 comments, 108 favorites, and 111 likes;Sylph AI has no verified rating, 0 comments, 136 favorites, and 110 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate codegate first
Put codegate on the priority trial list when the task aligns with “Agentic Frameworks” and especially Agentic Frameworks, Security, agentic framework, AI security, DevSecOps, and kubernetes. This follows recorded positioning and does not imply unlisted capabilities are absent.
codegate also currently records: pricing is free, product type is app, 636.1M monthly visits shown for the registered host (subpage scope unknown), no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Sylph AI first
Put Sylph AI on the priority trial list when the task aligns with “Libraries” and especially Libraries, Llm, llm, model fine-tuning, optimization, and pipeline. This follows recorded positioning and does not imply unlisted capabilities are absent.
Sylph AI also currently records: pricing is freemium, product type is website, 22.5K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in codegate and Sylph AI, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




