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codegate
Frameworks Agentiques · 636.1M visites mensuelles

Codegate est une passerelle de sécurité open-source et un framework de multiplexage pour les systèmes d'agents IA. Développé par Stacklok, il fournit des espaces de travail sécurisés et un contrôle d'accès basé sur des politiques, permettant aux développeurs de construire et de gérer des applications multi-agents complexes de manière sûre et efficace.

VS
Sylph AI
Bibliothèques · 22.5K visites mensuelles

Sylph AI est une plateforme de développement conçue pour maximiser le potentiel des applications LLM. Elle propose AdalFlow, une bibliothèque open-source de premier plan pour construire et auto-optimiser les pipelines de tâches LLM, et un AI Teammate qui fournit des conseils d'expert tout au long du flux de travail de développement, de l'idéation à la production.

codegate vs Sylph AI : prix, fonctions et trafic

Comparez codegate et Sylph AI selon leur positionnement, prix, fonctions, trafic et avis.

Mis à jour 5 août 2026

Aperçu du produit

codegate Aperçu du produit

Codegate est une passerelle de sécurité open-source et un framework de multiplexage pour les systèmes d'agents IA. Développé par Stacklok, il fournit des espaces de travail sécurisés et un contrôle d'accès basé sur des politiques, permettant aux développeurs de construire et de gérer des applications multi-agents complexes de manière sûre et efficace.

Preview

Sylph AI Aperçu du produit

Sylph AI est une plateforme de développement conçue pour maximiser le potentiel des applications LLM. Elle propose AdalFlow, une bibliothèque open-source de premier plan pour construire et auto-optimiser les pipelines de tâches LLM, et un AI Teammate qui fournit des conseils d'expert tout au long du flux de travail de développement, de l'idéation à la production.

Preview

Detailed feature comparison

FeaturecodegateSylph AI
Catégorie principaleFrameworks AgentiquesBibliothèques
Ajouté2025-08-162025-08-16
TarificationGratuitFreemium
Site officielgithub.comwww.sylph.ai
Type de produitApplicationSite web
Performance data
Note utilisateurNon vérifiéNon vérifié
Commentaires00
Visites mensuelles636.1M22.5K
Croissance mensuelle0.8%-13.2%
Favoris108136
DetailsVoir les détailsVoir les détails

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

Visites mensuelles
636.1M
Durée moyenne
6:23
Pages par visite
5.92
Taux de rebond
36.46%
Data updated 2026-06-11

Monthly traffic trend

  • 2026/1: 542.6M Visites mensuelles
  • 2026/2: 534.8M Visites mensuelles
  • 2026/3: 634.3M Visites mensuelles
  • 2026/4: 631M Visites mensuelles
  • 2026/5: 636.1M Visites mensuelles

Principales régions

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States36.14%229.9M
🇨🇳China22.96%146M
🇮🇳India17.41%110.7M
🇷🇺Russia15.84%100.8M
🇩🇪Germany7.65%48.7M

Sources de trafic

Source typePercentageTraffic
Direct82.14%522.5M
Référence16.14%102.7M
E-mail1.72%10.9M

Mots-clés

githubgithub copilothermes agentzapretзапрет

Sylph AI monthly traffic:

Latest traffic

Visites mensuelles
22.5K
Durée moyenne
0:31
Pages par visite
2.1
Taux de rebond
36.32%
Data updated 2026-06-11

Monthly traffic trend

  • 2025/9: 8.2K Visites mensuelles
  • 2026/1: 12K Visites mensuelles
  • 2026/2: 18.6K Visites mensuelles
  • 2026/3: 32.7K Visites mensuelles
  • 2026/4: 25.9K Visites mensuelles
  • 2026/5: 22.5K Visites mensuelles

Principales régions

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States70.84%15.9K
🇮🇳India9.68%2.2K
🇮🇩Indonesia6.55%1.5K
🇻🇳Vietnam6.47%1.5K
🇧🇷Brazil6.46%1.5K

Sources de trafic

Source typePercentageTraffic
Direct75.46%16.9K
Référence24.54%5.5K

Mots-clés

adaladal agentadal cliadal coding agentclaude opus 4.6 free use app
Traffic-based selection guidance: 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.

Usage comparison

Compare the core capabilities of codegate and Sylph AI

codegate Core features

Automatisation
Frameworks Agentiques
Sécurité

Sylph AI Core features

Automatisation
Bibliothèques
LLM

Use cases

codegate Use cases

Agent IA
automatisation
Outils pour développeurs
Open source
Python
Cadre agentique
Sécurité de l'IA
DevSecOps
Kubernetes
passerelle de sécurité

Sylph AI Use cases

Agent IA
automatisation
Outils pour développeurs
Open source
Python
Grand modèle linguistique
Réglage fin de modèle
optimisation
Pipeline
Ingénierie de prompt

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 “Frameworks Agentiques”, while Sylph AI is primarily listed under “Bibliothèques”, 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: Frameworks Agentiques; Sylph AI: Bibliothèques); 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: Automatisation; shared tags: Agent IA, automatisation, Outils pour développeurs, Open source et 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 Frameworks Agentiques, Sécurité, Cadre agentique, Sécurité de l'IA, DevSecOps, Kubernetes et passerelle de sécurité; Sylph AI's are Bibliothèques, LLM, Grand modèle linguistique, Réglage fin de modèle, optimisation, Pipeline et Ingénierie de prompt. 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 “Frameworks Agentiques” and especially Frameworks Agentiques, Sécurité, Cadre agentique, Sécurité de l'IA, DevSecOps et 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 “Bibliothèques” and especially Bibliothèques, LLM, Grand modèle linguistique, Réglage fin de modèle, optimisation et 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.

FAQ comparative

How should I choose between codegate and Sylph AI?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.