graph.one은 AI 기반 개인 CRM으로, 전문 네트워크를 매핑, 검색 및 활용하는 데 도움을 줍니다. 이메일 및 캘린더와 동기화하여 관계 그래프를 자동으로 구축하고, 자연어 검색을 통해 적합한 사람을 찾고 가장 따뜻한 소개 경로를 발견할 수 있도록 합니다.
Tapt는 기존의 종이 명함을 NFC 지원 디지털 명함으로 대체하는 차세대 네트워킹 솔루션입니다. 사용자는 맞춤형 디지털 프로필을 통해 즉시 연락처 정보를 공유하고, 리드를 포착하며, 인맥을 관리할 수 있습니다. 개인과 팀 모두를 위해 설계된 Tapt는 주요 CRM과 통합되며 강력한 분석 및 보안 기능을 제공합니다.
제품 개요
graph.one 제품 개요
graph.one은 AI 기반 개인 CRM으로, 전문 네트워크를 매핑, 검색 및 활용하는 데 도움을 줍니다. 이메일 및 캘린더와 동기화하여 관계 그래프를 자동으로 구축하고, 자연어 검색을 통해 적합한 사람을 찾고 가장 따뜻한 소개 경로를 발견할 수 있도록 합니다.
Tapt 제품 개요
Tapt는 기존의 종이 명함을 NFC 지원 디지털 명함으로 대체하는 차세대 네트워킹 솔루션입니다. 사용자는 맞춤형 디지털 프로필을 통해 즉시 연락처 정보를 공유하고, 리드를 포착하며, 인맥을 관리할 수 있습니다. 개인과 팀 모두를 위해 설계된 Tapt는 주요 CRM과 통합되며 강력한 분석 및 보안 기능을 제공합니다.
Detailed feature comparison
graph.one vs Tapt monthly traffic
Compare graph.one and Tapt by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the graph.one vs Tapt monthly traffic comparison, graph.one currently shows 449 visits and Tapt shows 51.7K; Tapt has about 115.2 times the visible traffic of graph.one, an absolute difference of about 51.3K 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.
graph.one monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 387 월 방문
- 2026/1: 2.9K 월 방문
- 2026/2: 2K 월 방문
- 2026/3: 550 월 방문
- 2026/4: 992 월 방문
- 2026/5: 449 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 100% | 449 |
검색 키워드
Tapt monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 38K 월 방문
- 2026/1: 51.3K 월 방문
- 2026/2: 108.9K 월 방문
- 2026/3: 71.5K 월 방문
- 2026/4: 36K 월 방문
- 2026/5: 51.7K 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 38.53% | 19.9K |
| 🇦🇺Australia | 34.86% | 18K |
| 🇬🇧United Kingdom | 11.73% | 6.1K |
| 🇮🇳India | 10.54% | 5.5K |
| 🇵🇭Philippines | 4.34% | 2.2K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 73.39% | 37.9K |
| 리퍼럴 | 17.24% | 8.9K |
| 이메일 | 9.37% | 4.8K |
검색 키워드
Usage comparison
Compare the core capabilities of graph.one and Tapt
graph.one Core features
Tapt Core features
Use cases
graph.one Use cases
Tapt Use cases
graph.one vs Tapt:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth graph.one vs Tapt comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. graph.one is primarily listed under “관계 관리”, while Tapt is primarily listed under “브랜딩”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (graph.one: 관계 관리; Tapt: 브랜딩); Pricing (graph.one: Free; Tapt: Paid); Monthly visits (graph.one: 449; Tapt: 51.7K); Monthly growth (graph.one: -54.7%; Tapt: 43.5%); Favorites (graph.one: 99; Tapt: 97). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the graph.one vs Tapt monthly traffic comparison, graph.one currently shows 449 visits and Tapt shows 51.7K; Tapt has about 115.2 times the visible traffic of graph.one, an absolute difference of about 51.3K 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.
If public market visibility is an important first-pass criterion, investigate Tapt 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
graph.one and Tapt currently overlap in shared categories: 네트워킹 및 리드 생성; shared tags: 연락처 관리 및 리드 생성. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
graph.one's unique categories/tags are 관계 관리, AI 검색, CRM, 네트워크 분석, 전문 네트워킹, 스타트업 도구 및 벤처 캐피탈; Tapt's are 브랜딩, CRM 통합, 디지털 명함, 네트워킹 도구, NFC 카드, 영업 도구, 지속 가능한 비즈니스 및 가상 명함. 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
graph.one has no verified rating, 0 comments, 99 favorites, and 104 likes;Tapt has no verified rating, 0 comments, 97 favorites, and 102 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate graph.one first
Put graph.one on the priority trial list when the task aligns with “관계 관리” and especially 관계 관리, AI 검색, CRM, 네트워크 분석, 전문 네트워킹 및 스타트업 도구. This follows recorded positioning and does not imply unlisted capabilities are absent.
graph.one also currently records: pricing is free, product type is website, 449 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 Tapt first
Put Tapt on the priority trial list when the task aligns with “브랜딩” and especially 브랜딩, CRM 통합, 디지털 명함, 네트워킹 도구, NFC 카드 및 영업 도구. This follows recorded positioning and does not imply unlisted capabilities are absent.
Tapt also currently records: pricing is paid, product type is website, 51.7K 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 graph.one and Tapt, 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.




