Documentation

Everything you need to make better decisions with Vesta.

What is Vesta?

Vesta is a decision-support tool that helps you compare options against multiple criteria — price, quality, risk, strategic fit, and anything else that matters to you — and arrive at a ranked, defensible recommendation.

Instead of relying on gut feeling or a spreadsheet full of weighted averages, Vesta guides you through a structured process:

  1. Define what matters (criteria)
  2. Define what you're choosing between (alternatives)
  3. Express how much each criterion matters (weights via pairwise comparison)
  4. Resolve trade-offs head-to-head (duels)
  5. Get a transparent, auditable ranking

AI analysis is woven throughout to flag inconsistencies, explain results, and suggest improvements — but you remain in control at every step.

Quick start

1 — Create a project

From your project list, click New project. Give it a name that describes the decision (e.g. "Choose a CRM"). You can also start from a ready-made template — useful if your use case is common (vendor evaluation, hiring, tool selection…).

2 — Add criteria

Open the Criteria tab. Add each factor that matters in your decision. For each criterion, pick the right type (numeric, rating scale, label-based, or yes/no) and optionally set a veto threshold to automatically disqualify options that cross a hard limit.

3 — Add alternatives

Open the Alternatives tab. Add each option you're considering. Fill in the value for each criterion. Vesta handles the rest.

4 — Set weights

In the Criteria tab, use the pairwise comparison matrix to express which criteria matter more than others. You compare them two at a time, so you never have to juggle all of them at once.

5 — Run duels

The Duels tab shows head-to-head comparisons between alternatives on individual criteria. Confirm automatic results or override them when you have contextual knowledge the numbers don't capture.

6 — Read the ranking

The Ranking tab shows your final ordered list with per-criterion score breakdowns and optional AI insights explaining why each alternative landed where it did.

Criteria

Criteria are the factors you use to judge each alternative. Vesta supports four types, so you can model almost any real-world attribute.

Quantitative

A numeric value with a unit (price in $, weight in kg, response time in ms). You choose whether higher is better or lower is better. Two alternatives are considered tied when their values are within 3% of the full range — this prevents spurious precision from skewing results.

Ordinal

A rating on a fixed numeric scale (e.g. 1–5 stars, 1–10). Displayed as a slider or star control. Higher is always better. Alternatives with the same score are tied.

Mapped

A set of named labels that map to numeric scores — for example Small → 2, Medium → 5, Large → 10. Useful for categorical attributes like company size, support tier, or contract type. Each label can optionally be marked as a veto: any alternative with that value is automatically disqualified.

Boolean

A yes/no criterion. You define which answer is preferred and, if needed, which answer triggers a veto. Useful for compliance checkboxes, feature presence, or legal requirements.

Veto thresholds

A veto is a hard disqualification rule. If an alternative violates a veto condition (e.g. price > budget, or a required feature is absent), its total score is forced to zero and it appears at the bottom of the ranking labelled "vetoed". Its potential score (what it would have scored without the veto) remains visible for reference.

Categories

Group related criteria into categories (e.g. "Cost", "Technical", "User experience"). When you have two or more categories, Vesta uses a two-level weight system: you express how much each category matters, then how criteria within each category compare to each other. This makes large decisions easier to reason about. With zero or one category all criteria are compared directly.

Alternatives

Alternatives are the options you're deciding between — vendors, job candidates, products, strategies, or anything else.

Entering values

For each alternative, enter the value for every criterion. The input control matches the criterion type: a number field for quantitative, a slider or stars for ordinal, a dropdown for mapped, and a toggle for boolean.

Additional properties

Attach non-scored metadata to any alternative — a website link, a location, or a free-text note. Properties are shown in the ranking view for easy reference but do not affect scoring.

The starred alternative

Star one alternative to mark it as your preferred fallback (the option you would choose if you had to decide right now). This activates the Vesta adjustment: the weight system subtly shifts to emphasize the criteria where the starred alternative is strong, giving it a fair chance against rivals that may outperform it on criteria you actually care less about. The starred alternative also stays visible in the ranking even if it violates a veto.

Weights & comparison

Vesta uses the Analytic Hierarchy Process (AHP) to derive criterion weights from pairwise comparisons. Instead of asking you to assign a percentage to each criterion (which is cognitively hard and prone to error), it asks simpler questions: "Is price more important than delivery speed, and if so, how much more?"

You answer each pair on a scale from equal importance up to extreme importance in either direction. Vesta does the math to turn those answers into a consistent set of weights that sum to 100%.

If you have categories, the same process runs twice: once to weight the categories, and once within each category. The final weight of any criterion is its within-category weight multiplied by its category's weight.

Duels (trade-offs)

When two alternatives score the same on a criterion, the numbers alone can't separate them. That's the only situation where your subjective judgment is actually needed — if one alternative already outperforms the other, you said so when you entered the values.

Pick any two alternatives and the Duels view surfaces only those ties, ready for you to break them.

Breaking a tie

For each tied criterion, drag the nudge slider toward the alternative you prefer. The further you drag, the stronger the preference you express. This creates a small score offset applied to the final evaluation — just enough to break the tie in your favour without distorting the overall ranking.

Reviewing decided criteria

Use the "Show decided criteria" toggle to see how the two alternatives compare on criteria where there is no tie. These rows are read-only — the math already has a clear answer and no input from you is needed or possible.

Ranking

The Ranking tab shows your final ordered list. Every score is traceable: expand any alternative to see exactly how much each criterion contributed to its total.

How scores are calculated

Each criterion value is normalised to a 0–1 scale across all alternatives (0 = worst in the set, 1 = best). Normalised scores are multiplied by their criterion weight and summed. If duels introduced nudges, small offsets are added. The result is a total score between 0 and 1.

Category breakdown

When you use categories, the ranking view also shows a score contribution per category, so you can see whether an alternative wins on cost but loses on quality, for example.

Veto warnings

Vetoed alternatives display their potential score alongside their actual score of zero, so you can see what they would have achieved had they cleared the disqualifying condition.

AI features

AI analysis is optional and complementary — it never changes your data, it explains and challenges it. All insights are marked stale automatically when relevant data changes, so you always know whether they reflect the current state of your project.

Ranking insights

Available from the Ranking tab. Generates three focused cards:

  • The winner — why did the top-ranked alternative win?
  • The kingmaker — which single criterion had the most decisive impact on the final order?
  • Stress test — what would change if a key criterion weight shifted?

Duel guidance

Available from the Duels tab. The AI reads your duel results and flags potential inconsistencies — for example, if you ranked A above B in three criteria but B above A in a fourth that partially overlaps. It helps you spot logical contradictions before they silently distort your ranking.

Project audit

Available from the Audit tab. A full health check of your project:

  • Dissonance patterns — preferences that contradict each other across duels
  • Weight suggestions — adjustments that would better align weights with your revealed duel preferences
  • Omitted variables — criteria you may have forgotten given the nature of your decision
  • Confidence score — an estimate of how internally consistent the project is

Key concepts

AHP — Analytic Hierarchy Process
A method for deriving weights from pairwise comparisons. By comparing options two at a time you avoid the cognitive overload of assigning direct percentages.
Normalisation
Converting raw criterion values to a 0–1 scale so that a price in dollars and a rating out of 5 can be compared on equal footing. The worst value in the set becomes 0 and the best becomes 1.
Veto
A hard disqualification rule. An alternative that crosses the threshold is scored 0 regardless of how well it performs on other criteria.
Duel
A head-to-head comparison of two alternatives. The Duels tab focuses on tied criteria — cases where the computed scores are equal and you need to express a subjective preference to break the deadlock.
Nudge
A small synthetic score offset applied when a duel result is tied. The nudge preserves the tie at the raw-value level while letting you express a slight subjective preference.
Starred alternative
An alternative you mark as your preferred fallback. The Vesta weight adjustment shifts emphasis toward criteria where this alternative is strong, and it remains visible in the ranking even if vetoed.
Hierarchical AHP
A two-level comparison used when criteria are grouped into categories. Category weights are determined first, then criteria are compared within each category. The final weight of a criterion is category weight × within-category weight.
Stale insights
AI-generated analysis that was produced for an earlier version of your project data. Vesta marks insights stale automatically when relevant data changes so you always know if they are up to date.