Maschinelles Lernen · 16.2K monatliche besuche

Ragie ist eine vollständig verwaltete RAG-as-a-Service-Plattform für Entwickler. Sie vereinfacht die Erstellung und Bereitstellung von KI-Anwendungen, indem sie die gesamte Pipeline der Retrieval-Augmented Generation (RAG) übernimmt. Verbinden Sie Ihre Datenquellen und nutzen Sie eine einfache API, um präzise, kontextbezogene Chatbots, semantische Suche und Wissensmanagementsysteme zu betreiben, ohne die Komplexität der Infrastrukturverwaltung.

Website besuchen Details ansehen

supermemory

LLM · 174.2K monatliche besuche

supermemory ist eine Speicher-API und Infrastruktur für das KI-Zeitalter, die für Entwickler konzipiert wurde, um LLMs mit einem langlebigen, persistenten Gedächtnis zu erstellen. Es überwindet die Begrenzung des endlichen Kontextfensters und ermöglicht die Erstellung intelligenter, kontextbewusster KI-Agenten, Chatbots und Anwendungen, die sich an vergangene Interaktionen und Informationen über verschiedene Plattformen hinweg erinnern.

Website besuchen Details ansehen

ragie vs supermemory: Preise, Funktionen und Traffic

Vergleiche ragie und supermemory nach Positionierung, Preis, Funktionen, Traffic und Nutzerfeedback.

Aktualisiert 05.08.2026

Produktübersicht

ragie Produktübersicht

Preview

supermemory Produktübersicht

Preview

Detailed feature comparison

Feature	ragie	supermemory
Hauptkategorie	Maschinelles Lernen	LLM
Hinzugefügt	2025-08-15	2025-08-16
Preismodell	Freemium	Freemium
Offizielle Website	www.ragie.ai	supermemory.ai
Produkttyp	Website	Website
Performance data
Nutzerbewertung	Nicht verifiziert	Nicht verifiziert
Kommentare	0	0
Monatliche Besuche	16.2K	174.2K
Monatliches Wachstum	-5.8%	-28.8%
Favoriten	130	122
Details	Details ansehen	Details ansehen

ragie vs supermemory monthly traffic

Compare ragie and supermemory by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the ragie vs supermemory monthly traffic comparison, ragie currently shows 16.2K visits and supermemory shows 174.2K; supermemory has about 10.7 times the visible traffic of ragie, an absolute difference of about 158K 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.

ragie monthly traffic:

Latest traffic

Monatliche Besuche

16.2K

Ø Besuchsdauer

0:49

Seiten pro Besuch

2.33

Absprungrate

35.97%

Data updated 2026-06-15

Monthly traffic trend

Top-Regionen

Top 5 countries/regions

Country/region	Percentage	Traffic
🇺🇸United States	67.49%	10.9K
🇵🇰Pakistan	12.26%	2K
🇮🇳India	10.76%	1.7K
🇨🇦Canada	4.92%	798
🇵🇱Poland	4.57%	741

Traffic-Quellen

Source type	Percentage	Traffic
Direkt	44.75%	7.3K
Verweis	44.04%	7.1K
E-Mail	11.21%	1.8K

Suchbegriffe

configure mcp google doc server cursorrag as a serviceragierag over multimodal content like audio, video, imagevideo rag model

supermemory monthly traffic:

Latest traffic

Monatliche Besuche

174.2K

Ø Besuchsdauer

1:11

Seiten pro Besuch

3.55

Absprungrate

42.55%

Data updated 2026-06-15

Monthly traffic trend

Top-Regionen

Top 5 countries/regions

Country/region	Percentage	Traffic
🇺🇸United States	56.33%	98.1K
🇮🇳India	22.09%	38.5K
🇳🇬Nigeria	8.47%	14.8K
🇨🇦Canada	6.67%	11.6K
🇹🇭Thailand	6.44%	11.2K

Traffic-Quellen

Source type	Percentage	Traffic
Direkt	84.44%	147.1K
Verweis	14.32%	24.9K
E-Mail	1.24%	2.2K

Suchbegriffe

super memorysupermemorysuper memory aisupermemory aisupermemory mcp

Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate supermemory first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.

Usage comparison

Compare the core capabilities of ragie and supermemory

ragie Core features

API & Integration

Wissensmanagement

Maschinelles Lernen

supermemory Core features

API & Integration

Wissensmanagement

LLM

Use cases

ragie Use cases

API

Chatbot

Entwicklerwerkzeuge

Großes Sprachmodell

Retrieval-Augmentierte Generierung

KI-Assistent

Datenintegration

Wissensdatenbank

Semantische Suche

Vektordatenbank

supermemory Use cases

API

Chatbot

Entwicklerwerkzeuge

Großes Sprachmodell

Retrieval-Augmentierte Generierung

KI-Agent

Kontextverwaltung

Wissensmanagement

Langzeitgedächtnis

Speicher-API

Zweites Gehirn

ragie vs supermemory：In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

This in-depth ragie vs supermemory comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. ragie is primarily listed under “Maschinelles Lernen”, while supermemory is primarily listed under “LLM”, so the first decision is whether your actual task matches their recorded scope.

The structured fields currently show these decision-relevant differences: Primary category (ragie: Maschinelles Lernen; supermemory: LLM); Monthly visits (ragie: 16.2K; supermemory: 174.2K); Monthly growth (ragie: -5.8%; supermemory: -28.8%); Favorites (ragie: 130; supermemory: 122); Website (ragie: www.ragie.ai; supermemory: supermemory.ai). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.

If public market visibility is an important first-pass criterion, investigate supermemory first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.

Product positioning, use cases, and roles

ragie and supermemory currently overlap in shared categories: API & Integration und Wissensmanagement; shared tags: API, Chatbot, Entwicklerwerkzeuge, Großes Sprachmodell und Retrieval-Augmentierte Generierung. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

ragie's unique categories/tags are Maschinelles Lernen, KI-Assistent, Datenintegration, Wissensdatenbank, Semantische Suche und Vektordatenbank; supermemory's are LLM, KI-Agent, Kontextverwaltung, Wissensmanagement, Langzeitgedächtnis, Speicher-API und Zweites Gehirn. 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

ragie has no verified rating, 0 comments, 130 favorites, and 132 likes；supermemory has no verified rating, 0 comments, 122 favorites, and 100 likes。

Neither product has enough rating or comment samples for a credible reputation ranking.

Selection guidance by actual need

When to evaluate ragie first

Put ragie on the priority trial list when the task aligns with “Maschinelles Lernen” and especially Maschinelles Lernen, KI-Assistent, Datenintegration, Wissensdatenbank, Semantische Suche und Vektordatenbank. This follows recorded positioning and does not imply unlisted capabilities are absent.

ragie also currently records: pricing is freemium, product type is website, 16.2K 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.

When to evaluate supermemory first

Put supermemory on the priority trial list when the task aligns with “LLM” and especially LLM, KI-Agent, Kontextverwaltung, Wissensmanagement, Langzeitgedächtnis und Speicher-API. This follows recorded positioning and does not imply unlisted capabilities are absent.

supermemory also currently records: pricing is freemium, product type is website, 174.2K 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 ragie and supermemory, 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.

Vergleichs-FAQ

How should I choose between ragie and supermemory?

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.