Match made plain

The silence after apply

In April 2026, Enhancv surveyed 1,066 U.S. job seekers. Half of them, 50.5 percent, had been rejected at least once in the past year without a single word from a human. Only 5.5 percent of rejected candidates received any feedback at all, though 94 percent said they wanted it.

A decision you cannot see

The harder part is not the rejection. It is the blackout around it. The same Enhancv survey found that just 9.7 percent of job seekers had ever been clearly told AI was involved in their hiring. People are filtered by a system they cannot see, cannot question, and were rarely told existed. When the answer is silence, there is nothing to learn from.

What CoBlack shows you

CoBlack puts the reasoning on your side of the table. Before you apply, Auto Match shows why a role fits, in plain language. It names the parts of your Career Capability Map that line up with the opening, the seniority it reads you at, and the gaps that may count against you. The match is not a score you have to trust. It is an explanation you can read.

Transparency before the application

This is what job match transparency means in practice. You see the same logic the engine used, stated in words, before you spend thirty minutes on a form. If a role is a stretch, you know why. If it is a strong fit, you know which strengths carried it. The decision stays yours, made with the reasoning in front of you.

Nothing left to guess

The hiring system has trained job seekers to guess. To rewrite a resume for a rejection no one explained, then apply again into the same quiet. CoBlack does the opposite. It tells you what it sees, and why, while you can still act on it.