HR AI Index
Index Vendors Clair › Alternatives · September 2026 Edition
One category · what the models named instead

Alternatives to Clair, as AI models named them

In the September 2026 Edition, 194 of the 216 answers collected in the one category where Clair holds a standing named it neither as a first choice nor as an alternative. These are the products those answers put first, category by category and buyer by buyer. The output is the models' output.

Named instead, most often
First choices in the 194 answers that did not name Clair, every category and segment above added together; a product can be counted in several. Each category below keeps its own denominator.

Earned wage access

Compensation and total rewards. Six framings, twelve models, one answer each per buyer segment; an answer counts here when Clair is not its first choice or an alternative in it.
Small businessClair holds 7 labels here, under the 10-label cutoff, so it is unranked.

Sixty-five of the seventy-two answers did not name Clair; it was the first choice in two. The first choices in those sixty-five answers, eight products in all:

The full small business standing →
Mid-marketClair is #6 of 12 here at 7% of first choices, 11 labels.

Sixty-three of the seventy-two answers did not name Clair; it was the first choice in three. The first choices in those sixty-three answers, twelve products in all, the eight most named:

4 more in the record.The full mid-market standing →
EnterpriseClair holds 8 labels here, under the 10-label cutoff, so it is unranked.

Sixty-six of the seventy-two answers did not name Clair; it was the first choice in zero. The first choices in those sixty-six answers, twelve products in all, the eight most named:

4 more in the record.The full enterprise standing →

How to read this

A category is asked six ways of each of twelve models on behalf of each buyer segment, so a segment is seventy-two answers. An answer belongs on this page when the judge labeled Clair neither its first choice nor an alternative in it; the products listed are the first choices those answers made, counted once per answer. An answer that named nothing first, or named Clair only in passing, is in the denominator and adds to no product. The counts are not the category standing, which is on the category page with its share and rank; they are the same record read from Clair's side.

Every answer and every label is in the free record. The output is the models' output; nothing here is a recommendation by the index, and a product named instead of Clair was named by a model, not endorsed by anyone.