Agentic Panel
Make smarter decisions.Faster than ever.
For aspiring founders, early-stage teams and product managers.
Discover what AI agents need, then test your idea or product against those requirements. Use the findings to decide what to build, change or test next.
For ideas and products. Pay per experiment.
Explore agent roles
How it works
From agent needs to product decisions.
- Tell us what you want to learn. We draft the test; you review the questions and approve the criteria.
- Choose who agents act for, how cautious they are and what evidence they need. Set your budget.
- Agents first explore the problem without seeing your offer. Then they assess your idea or product against those requirements.
You approve the test, budget and success criteria before it runs.
Create · 11 blocks
Blocks
11 blocks
- 1 · decision modelWhat criteria does it decide by?
- 3 · problem salienceDoes your problem come up on its own?
- 7 · inclusion testIs it shortlisted?
- 8 · rankingWhere does it rank?
- 10 · RecommendationWhat recommendation does it write?
Inclusion Test
One test block: shortlist inclusion.
The question we ask the AI
What are the top 3 expense management tools for a 20-person startup?
Options the AI chooses from
When this block passes
> 60%of agents shortlist you
Target & Budget
Agent targeting
Goal: will agents shortlist this product?
3 segments · 72 runs
Who the agent acts for
B2B Procurement — “is this vendor safe?”
How cautious it is
How much proof it wants
This agent will not endorse what it cannot verify.
Who’s buying, and where
Budget · how many runs
$29
24 runs · Explorer
$49
48 runs · Standard
$69
72 runs · Validated
$99
120 runs · Confident
72
runs
24 runs per segment, spread across 14 models.
$69
Experiment · AI agents panel
Expense management for small teams
Active46 of 72 runs
Runs are spread across 14 models from 9 labs. The report is usually ready within an hour.
- ProbeDoes your problem come up on its own?35 surfaced it
- ValidationShortlisted when a user asks15 of 22
- ValidationRank against Expensify, Pleo, Rampmean 1.8
- ValidationRecommended in the agent’s own words14 of 22
Run 41 · Research Copilot · Gemini 3.1 Pro shortlisted you, ranked 2nd
What you get
Evidence you can build on.
See what agents weighed before they saw you, whether they shortlist and recommend you, and what to fix next. Use the report to guide the product or discuss it with co-founders and investors.
See a result
ValidatingCompleted 22 Jul 2026 · 72 runs · 3 segments · 14 models
Report
Expense management for small teams
4 of 4 success criteria passed
All four criteria passed in the tested scenarios. Review the findings to decide what to improve or test next.
Runs
72
Criteria passed
4 / 4
Shortlisted
67%
Executive summary
Tallybox is legible to machines end to end. Across 72 runs spanning procurement, shopping and research, it is shortlisted in 48, ranks 1.8 of 4 against Expensify, Pleo and Ramp, and is recommended in 48. The remaining risk is execution, not machine legibility.
Validation certificate
Share a verifiable result.
Validated experiments get a verification link. Share the result and the criteria with co-founders or investors.
- Criteria locked before the test
- Runs, models and segments on the page
- Unique verification ID
Certificate preview
Verified certificate · VAL-2026-0722-7C
GRADE A
AI panelExpense management for small teams
Tested with 72 runs across 3 segments and 14 AI models. Every threshold was set before launch. The grade shows how machines judge the idea, not proven human demand.
- Panel
- AI agents · 14 models
- Criteria
- 4 of 4 passed
- Sample
- 72 of 72 runs
- Issued
- 22 July 2026
4 of 4 criteria passed
- Problem surfaces unpromptedthreshold > 50%Passed
- Shortlisted when a user asksthreshold > 60%Passed
- Ranks top-2 vs competitorsmean rank ≤ 2Passed
- Recommended in the machine’s wordsthreshold ≥ 55%Passed
FAQ
Before you start.
No. AI agents evaluate problems and product requirements in the scenarios you set. Each run is a real model, configured with the traits you choose. Their responses show how those systems assess your offer. They do not replace evidence from people. To hear from real people, use the Human Panel.
The report identifies the models used in your experiment. Runs are spread across up to 14 models from 9 labs: Claude, GPT, Gemini, Grok, DeepSeek, Kimi, Qwen, GLM and Mistral. Findings apply to those models and the scenarios tested.
Agents identify what matters without seeing your solution: which criteria they use, who they already recommend and what the ideal solution looks like. We then introduce your idea or product and test it against those requirements. The gap shows what to change. This works for new ideas and existing products.
You pay per experiment, with no subscription. It starts at $29 for 24 runs; the Validated tier is $69 for 72 runs across 14 models. Longer experiments add $10 per tier. You review the budget before the test starts. No hidden fees, amounts excl. VAT.
Models and behaviour can change. The findings describe the conditions tested, not a guarantee of future recommendations, purchases or adoption. Read the report as a dated snapshot, and run the experiment again after a major model update or a change to how you describe your product.
Make your next move with evidence.
Test what your next product decision depends on.