Which partner can support a complex B2B decision across markets with evidence the buying team can review?
A defensible recommendation depends on , , and whether the result can be .
AI-native MarTech infrastructure built for decisions made by people and shaped by agents.
See what buyers are being told before the first conversation.
Yonaris makes the questions, evidence and comparisons behind an AI-shaped shortlist visible—so your team can act on the decision, not chase another visibility score.
Bring us one buying questionWhich partner can support this decision?
Observation
Comparison
Evidence
Decision
Observation
- Answer presence
- 79%
- Share of Voice
- 35%
- Prompts
- 42
- Evaluations
- 3,120
30-day evaluation window
Runs approximately once per day.
Share of Voice tracked comparison set
An ordered, de-identified comparison set for the selected observation boundary.
Share of Voice: 35%
- Your brand
- Competitor A
- Competitor B
- Competitor C
Evidence
Public evidence gap: The selected buying question lacks a directly matched public comparison source in this sample.
Selected observation boundary: The selected market, language, engine, tracked prompt, observation target, and 30-day window.
Decision
Sample workspace
Sample data for product demonstration only.
Next action: Review one public comparison brief for the selected buying question.
Comparable retest: Run the same question against the same tracked comparison set and observation boundary.
This sample workspace shows a review method, not a recommendation.
The shortlist now forms before the click.
Traditional MarTech begins with exposure, visits and leads. Yonaris starts earlier: with the question, the evidence an agent can find and the comparison a buyer may inherit.
Product evidence attached to the decision system
Inspect the working state behind the next review.
Yonaris connects buyer questions, company facts, public evidence, content and channels, market observation, customer behaviour, and action and review.
Yonaris public purpose statement · company statement · reviewed 27 Aug 2026 · The purpose applies to decisions reviewed against a stated question, market, language and time.Sample workspace
Sample data for product demonstration only.
Coverage is limited to the selected market, language, engine, tracked prompt, observation target, and 30-day window.
Overview
- Answer presence
- 79%
- Share of Voice
- 35%
- Prompts
- 42
- Evaluations
- 3,120
30-day evaluation window
Runs approximately once per day.
Last updated within the displayed window.
Opportunities
Illustrative signals and review actions grounded in the observed prompt set.
Creation
Create a comparison brief
Illustrative signal The tracked question lacks a directly matched public comparison source.
Review action Review a source-backed comparison brief before publication.
Existing content
Review an existing evidence page
Illustrative signal A relevant public page needs an evidence and freshness review.
Review action Inspect the page against the selected observation boundary.
Outreach
Review independent comparison surfaces
Illustrative signal Independent comparison surfaces appear in the observed evidence set.
Review action Confirm an eligible third-party surface before outreach.
Social
Review community conversations
Illustrative signal Community conversations are part of the evidence surfaces selected for review.
Review action Review an authentic, disclosed participation opportunity.
Query Fan-Out
One tracked prompt followed by de-identified web-query rewrites observed for the selected engine and target.
Tracked prompt
What should a buyer compare before choosing an analytics partner?
Rewritten web query
analytics partner evaluation criteriaAdded Adds evaluation criteria to the buying intent.
compare analytics partners for buyer decisionsPreserved Preserves the analytics-partner comparison intent.
analytics partner evidence by selected market and languageBoundary Applies the selected observation boundary to the rewrite.
Keep the question, evidence and retest together.
A review preserves the original buying question, the answer and sources observed at the time, the change made, and the retest under comparable conditions.
Which company can support this decision without adding risk for the buying team?
- Answer
- The answer describes the company, but does not connect its strongest capability to the buying condition.
- Evidence
- Public product language is broad and no source states the operating boundary.
- Judgment
- The company is relevant, but not yet defensible as a preferred comparison.
- Next action
- Publish the scoped proof required by the buying condition, then repeat the same question.
- Answer
- The answer can connect the capability to the buyer’s condition with a visible, scoped source.
- Evidence
- The new source states the condition, scope and review date beside the capability.
- Judgment
- Record the changed answer only if the question and review conditions remain comparable.
- Next action
- Preserve the retest with its model, market, language, sources and any limits on attribution.
One public truth. Two ways to read it.
People need context and judgment. Agents need explicit facts, evidence and boundaries. The public material should serve both without creating two competing versions of the company.
AI-answer observation connects to a wider marketing system spanning company facts, public evidence, customer behaviour, and action and review.
Yonaris public scope statement · company statement · reviewed 27 Aug 2026 · The observation describes a selected question, market, language, time and AI surface.AI-native MarTech infrastructure built for decisions made by people and shaped by agents.
Public basis revealed.
- Public basis
- Yonaris public company description · company statement · reviewed 27 Aug 2026
- Boundary
The category covers Yonaris public system for buyer questions, evidence, market observation and review.
Machine-readable representations support retrieval and inspection; they do not guarantee ranking, inclusion, retrieval, or citation.
- Stable identity
- yonaris.category.ai-native-martech
- Canonical representations
- Review date
- 27 Aug 2026
Bring one question the market cannot afford to get wrong.
We will establish whether it can be observed, evidenced and turned into a useful next action.