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AI application scoring

Stop choosing between reviewing every applicant and reviewing them well. Score all of them.

The AI evaluator reads every application against your program's thesis, scores it, and explains why, so your reviewers start from a ranked shortlist instead of a cold pile of hundreds. Your team still makes every decision.

Advisory by design 2,000,000+ applications processed ISO 27001 certified
AI evaluation · Startup early stage app.acceleratorapp.co
Ranked shortlist 87 scored
1Sol Energy
Strong thesis fit · climate
9.1
2Mira Health
Clear traction signal
9.0
3Marrow
Team gap flagged
8.7
Advance threshold · 7.5
4Tilt Robotics
Below thesis fit
6.4
5Patchwork
Off-thesis · drafted feedback
5.2
Advisory. A human evaluator decides every applicant.
AcceleratorApp Bot · Sol Energy 9.1 / 10
Is the problem clearly defined and tied to your program thesis?
9.4
AIScopes a specific climate & energy problem with credible context and named stakeholders.
How strong is the founding team for this stage?
8.8
AITwo technical co-founders with prior exits; commercial hire still a gap.
Is there evidence of early traction?
9.0
AIPre-seed traction is ahead of cohort median; two signed pilots support demand.

See it in action

A 15 to 45 minute walkthrough of the platform, tailored to your program. See how teams like yours are running on AcceleratorApp.

  • Full migration included for every new customer
  • Most teams are live within one to two weeks
  • You control the pace of onboarding

No commitment. No credit card. Just a walkthrough.

200+
organizations
2,000,000+
applications processed
6,000+
program managers
ISO 27001
certified
GDPR
compliant
Start It @KBC SparkLabs German Accelerator Startup Braga MBC Africa MIT Design X Imagine H2O Ignite Bermuda
Quick answer

What the AI evaluator is

The AI evaluator is an evaluator type you assign to a round exactly like a human reviewer. It reads each application against your funnel's thesis and evaluation form, produces a score with per-question reasoning, and ranks the pool. Reviewers open a shortlist instead of hundreds of raw applications. When an applicant is not advancing, the AI can draft tailored feedback your team sends, so no one gets a generic rejection. Every AI evaluation is advisory: a human decision is always required before a round closes.

The problem

Review depth and review volume are in direct conflict.

01

Review depth and review volume are in direct conflict

With a few hundred applications and a small panel, you choose: review everyone shallowly, blow the deadline, or bring in ad-hoc reviewers whose calibration is inconsistent. Quality drops either way. The constraint is human hours, and you cannot add them fast enough.

02

The first read is the most repetitive and the least strategic

Sorting the clearly-strong from the clearly-weak is mechanical work that eats most of the review window. Your best evaluators spend their scarce time on the easy 80 percent instead of the genuinely hard calls in the middle.

03

Rejected founders get nothing useful

When you reject hundreds of applicants, almost none of them get real feedback. A generic form rejection is the norm, and in a small ecosystem that costs you reputation and future applicants.

The signature capability

A ranked, reasoned starting point for every reviewer

The AI evaluator gives every reviewer a ranked, reasoned starting point, so human judgment goes where it actually matters.

Scored against your thesis · Sol Energy
SE
Sol Energy
Scored against your funnel thesis
9.1
/ 10
Thesis fit9.4
Team8.8
Traction9.0
AI reasoning Strong fit with your climate & energy thesis. Pre-seed traction is ahead of cohort median; recommend advancing to human review.
Your definition of fit
Ranked shortlist · 87 scored
1Sol Energy
Strong thesis fit · advance
9.1
2Mira Health
Clear traction signal · advance
9.0
3Marrow
Strong product · team gap flagged
8.7
4Lattice Bio
Borderline · needs human read
7.8
Advance threshold · 7.5
5Tilt Robotics
Below thesis fit
6.4
6Patchwork
Off-thesis · feedback drafted
5.2
Advisory. Reviewers decide who advances.
Hard calls in the middle
Rejection feedback · drafted for review
PW
Patchwork
Not advancing · score 5.2
AI draft
Thank you for applying. After review against our program thesis, we're not advancing your application this round. The team and early traction were strong, but the solution sits outside our climate & energy focus for this cohort.
Review & send Edit draft
Specific, never generic

How it works

From thesis to shortlist in four steps

1

Write your thesis

Describe what a strong applicant looks like for this program. A built-in coach scores your thesis against a clear framework and suggests improvements before you assign the evaluator, so the AI has what it needs to score well.

2

Assign the AI evaluator

It slots into the same evaluator assignment you already use for humans, with a clear AI badge. Assign it to the whole round or to specific applications.

3

Applications get scored

Each application is scored against your thesis and form, with reasoning per question. You watch progress update live on the application overview.

4

Your reviewers decide

Reviewers work from a ranked shortlist with the AI's reasoning attached. They make every call. A human decision is always required before the round closes.

Capabilities

Built for the reality of high-volume review

Scored against your criteria, not a generic model

The evaluator scores against the thesis you write and the evaluation form you built. Your definition of fit drives every score.

Every score comes with its reasoning

The AI explains why it scored each question the way it did. Reviewers see the logic, not just a number, and can trust or challenge it.

Open a shortlist, not a pile

The pool arrives ranked. Your scarce review hours go to the hard calls in the middle, not the obvious top and bottom.

Specific feedback for every applicant

The AI drafts rejection feedback grounded in each application. Your team reviews and sends it. No more generic form rejections.

Help writing a thesis the AI can use

A built-in coach scores your thesis and evaluation instructions against a clear framework and suggests fixes, so weak inputs do not produce weak evaluations.

Your team always decides

Every AI evaluation is advisory. A human decision is required before any round closes. The AI never auto-accepts or auto-rejects.

Why AcceleratorApp

AI you can put in front of a funder

Advisory by design, enforced in the product

A round cannot be closed on AI scores alone. At least one human decision is always required. This is built into the platform, not a policy you have to remember.

Scores your thesis, not a template

The evaluator works from your specific definition of fit. The built-in coach helps you write that definition well, so the scores reflect your program's judgment.

Feedback that protects your reputation

Tailored rejection feedback, drafted for every applicant, means founders learn why. In a small ecosystem, that is the difference between a respected program and a resented one.

Private and compliant

AI evaluations are never shown to applicants. ISO 27001 certified, GDPR compliant, with data processing terms in place with the AI provider.

Predictable cost

Metered per evaluation run against a monthly quota. Failed runs do not count. No surprise bills.

See it mapped to your program

Walk through it with someone who has run a round

Pricing

Plans start from $499 per month

$499 / month

AI evaluation is metered with a predictable monthly quota. No hidden setup fees.

Free download

The AI for Program Operations Guide

How program teams use AI to score applications, rank a shortlist, and draft feedback, without taking the decision out of human hands.

Book a demo

Pick a time that works

45-minute walkthrough, tailored to your program.

FAQ

Questions program managers actually ask

No. The evaluator is advisory. It scores and ranks applications and drafts feedback, but a human evaluator's decision is always required before a round closes. The platform enforces this: a round cannot be decided on AI submissions alone.
You write a thesis describing what makes a strong applicant for your program, and you add instructions to your evaluation form. The AI scores against both. A built-in coach helps you write a thesis it can use effectively.
Every score comes with per-question reasoning, so your reviewers see the logic behind it and can accept or override it. The AI is a faster first read, not a black box, and never the final word.
No. The AI drafts tailored feedback grounded in each applicant's submission. Your team reviews it and sends it. The AI does not contact applicants.
No. AI evaluations and any drafted feedback are internal to your team. What you disclose about your process is your choice.
The platform guards against this. The thesis and evaluation instructions must pass a quality check from the built-in coach before you can assign the AI evaluator, so vague inputs are caught before they produce vague evaluations.
Yes. ISO 27001 certified and GDPR compliant, with data processing terms in place with the AI provider. Optional web research on applicants is off by default.
Metered per evaluation run against a monthly quota included in your plan. Failed runs consume nothing. The thesis coach does not consume your evaluation quota.

Review every applicant well. Decide every applicant yourself.

Advisory by design · A human decides every round · Used by 200+ organizations