Diligent는 핀테크 및 은행을 위한 AI 기반 플랫폼으로, 비즈니스 고객에 대한 실사를 자동화하고 강화하도록 설계되었습니다. 생성형 AI를 활용하여 온라인 활동을 조사하고, 고위험 법인과의 네트워크 연결을 파악하며, 새로운 위험을 모니터링하여 사기 및 자금세탁방지(AML) 규정 준수를 강화합니다.
Sphinx는 금융 기관 및 핀테크를 위해 설계된 AI 기반 컴플라이언스 플랫폼입니다. 실시간 유해 미디어 스크리닝, 정치적 주요인물(PEP) 및 제재 목록 확인, 최종 실소유자(UBO) 검증을 제공하여 고객확인(KYC), 자금세탁방지(AML) 및 사기 탐지 프로세스를 자동화하고 간소화합니다. 이 플랫폼은 AI 에이전트를 사용하여 컴플라이언스 병목 현상을 제거하고 위험을 줄이며, 심층적이고 설명 가능한 통찰력으로 규제 준수를 보장합니다.
제품 개요
Diligent 제품 개요
Diligent는 핀테크 및 은행을 위한 AI 기반 플랫폼으로, 비즈니스 고객에 대한 실사를 자동화하고 강화하도록 설계되었습니다. 생성형 AI를 활용하여 온라인 활동을 조사하고, 고위험 법인과의 네트워크 연결을 파악하며, 새로운 위험을 모니터링하여 사기 및 자금세탁방지(AML) 규정 준수를 강화합니다.
Sphinx 제품 개요
Sphinx는 금융 기관 및 핀테크를 위해 설계된 AI 기반 컴플라이언스 플랫폼입니다. 실시간 유해 미디어 스크리닝, 정치적 주요인물(PEP) 및 제재 목록 확인, 최종 실소유자(UBO) 검증을 제공하여 고객확인(KYC), 자금세탁방지(AML) 및 사기 탐지 프로세스를 자동화하고 간소화합니다. 이 플랫폼은 AI 에이전트를 사용하여 컴플라이언스 병목 현상을 제거하고 위험을 줄이며, 심층적이고 설명 가능한 통찰력으로 규제 준수를 보장합니다.
Detailed feature comparison
| Feature | Diligent | Sphinx |
|---|---|---|
| 주요 카테고리 | 준수 | 준수 |
| 등록일 | 2025-08-14 | 2025-08-03 |
| 가격 | 유료 | 유료 |
| 공식 사이트 | www.godiligent.ai | sphinxlabs.ai |
| 제품 유형 | 웹사이트 | 웹사이트 |
| Performance data | ||
| 사용자 평점 | 확인되지 않음 | 확인되지 않음 |
| 댓글 | 0 | 0 |
| 월 방문 | 9.3K | 3.4K |
| 월 성장률 | 17.5% | 확인되지 않음 |
| 즐겨찾기 | 104 | 138 |
| Details | 상세 보기 | 상세 보기 |
Diligent vs Sphinx monthly traffic
Compare Diligent and Sphinx by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Diligent vs Sphinx monthly traffic comparison, Diligent currently shows 9.3K visits and Sphinx shows 3.4K; Diligent has about 2.7 times the visible traffic of Sphinx, an absolute difference of about 5.8K visits. This reflects visible reach, not feature quality or paid users.
Only Diligent has complete third-party traffic details; Sphinx uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
Diligent monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 3.5K 월 방문
- 2026/1: 6.3K 월 방문
- 2026/2: 5.9K 월 방문
- 2026/3: 8.3K 월 방문
- 2026/4: 7.9K 월 방문
- 2026/5: 9.3K 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇬🇧United Kingdom | 30.42% | 2.8K |
| 🇺🇸United States | 25% | 2.3K |
| 🇮🇳India | 20.28% | 1.9K |
| 🇳🇱Netherlands | 15.46% | 1.4K |
| 🇪🇸Spain | 8.84% | 819 |
검색 키워드
Sphinx monthly traffic:
Latest traffic
Usage comparison
Compare the core capabilities of Diligent and Sphinx
Diligent Core features
Sphinx Core features
Use cases
Diligent Use cases
Sphinx Use cases
Diligent vs Sphinx:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Diligent vs Sphinx comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Diligent is primarily listed under “준수”, while Sphinx is primarily listed under “준수”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Monthly visits (Diligent: 9.3K; Sphinx: 3.4K); Favorites (Diligent: 104; Sphinx: 138); Website (Diligent: www.godiligent.ai; Sphinx: sphinxlabs.ai); Added (Diligent: 2025-08-14; Sphinx: 2025-08-03). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Diligent vs Sphinx monthly traffic comparison, Diligent currently shows 9.3K visits and Sphinx shows 3.4K; Diligent has about 2.7 times the visible traffic of Sphinx, an absolute difference of about 5.8K visits. This reflects visible reach, not feature quality or paid users.
Only Diligent has complete third-party traffic details; Sphinx uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
The current traffic scope is not sufficient for a reliable product ranking. Treat monthly visits as a market-interest signal, then decide using taxonomy, use cases, pricing, and a like-for-like trial rather than reading exposure as product capability.
Product positioning, use cases, and roles
Diligent and Sphinx currently overlap in shared categories: 준수, 자동화 및 사기 탐지; shared tags: AML, 핀테크, 사기 탐지, KYC, 레그테크 및 위험 관리. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Diligent's unique categories/tags are 사업 인증, 규정 준수 자동화, 실사, 대규모 언어 모델 및 규제 기술; Sphinx's are 준수, 금융 범죄, PEP 스크리닝, 제재 심사 및 UBO 검증. 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
Diligent has no verified rating, 0 comments, 104 favorites, and 112 likes;Sphinx has no verified rating, 0 comments, 138 favorites, and 154 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Diligent first
Put Diligent on the priority trial list when the task aligns with “준수” and especially 사업 인증, 규정 준수 자동화, 실사, 대규모 언어 모델 및 규제 기술. This follows recorded positioning and does not imply unlisted capabilities are absent.
Diligent also currently records: pricing is paid, product type is website, 9.3K 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 Sphinx first
Put Sphinx on the priority trial list when the task aligns with “준수” and especially 준수, 금융 범죄, PEP 스크리닝, 제재 심사 및 UBO 검증. This follows recorded positioning and does not imply unlisted capabilities are absent.
Sphinx also currently records: pricing is paid, product type is website, 3.4K on-site monthly views, 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 Diligent and Sphinx, 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.




