兩者的成長率相比如何？

Citely 的月增率為 -6.1%；Teaming 為 +926.1%。

價格相比如何？

Citely：免費增值。Citely uses a credit-based model with four published tiers: a $9 one-time trial, $19/month billed monthly, $14/month billed yearly, and a $347 one-time three-year Believer plan. Higher tiers raise the credit allowance, extend the character limit for reference verification from 2,000 to 4,000 characters, and add citation export in APA, MLA, and Chicago. Enterprise and larger credit bundles are available on request. Teaming：免費試用、付費。Free 14-day trial. Published plan is $25 per employee per month billed annually with all features included; per-manager and custom company pricing is quoted on request.

Citely 與 Teaming 有哪些替代方案？

相關分類中的其他工具包括 Scribbr, Jenni, Scite, Motion, Yoodli AI 演講教練。

Citely vs Teaming — 流量 (6.23萬 vs 944)、定價與選型結論

Open AI Tools

Citely vs Teaming — 流量 (6.23萬 vs 944)、定價與選型結論 | Open AI Tools

流量與規格並排比較表

面向／指標	Citely	Teaming
官方網域	citely.ai	teaming.com
定價模式	免費增值	免費試用、付費
每月造訪次數	6.23萬 (62,271)	944 (944)
月流量變化量	-4056 (-6.1%)	+852 (+926.1%)
主要市場與市佔	🇺🇸 美國 (25.9%)	🇧🇷 巴西 (100%)
每月直接造訪	9641	358
使用者評分	4.2	4.1
支援平台	網站	網站

Citely

Citely is an academic citation tool that checks whether the references in a paper actually exist and point to the right work. You paste a reference list or a claim, and Citely cross-checks it against large scholarly indexes such as CrossRef, PubMed, arXiv, and OpenAlex, flagging fabricated DOIs, mismatched titles, and the hallucination patterns typical of AI-written references. It also works in reverse as a source finder: give it a claim and it returns real, citable papers with verified metadata in APA, MLA, or Chicago format.

AI Source Finder

Paste a claim or paragraph and Citely returns matching academic papers with verified metadata, ready to cite in APA, MLA, or Chicago style.

Citation & Reference Checker

Submit a reference list and Citely tests each entry against scholarly databases, marking entries that cannot be confirmed or that point to the wrong work.

AI Hallucination Detection

Citely targets the specific errors AI models make when inventing references, including chimera citations, invented DOIs, and citations that drift across years.

Multi-Database Verification

Checks run against CrossRef, PubMed, arXiv, and OpenAlex, so verification reflects real indexed scholarship rather than a single narrow database.