Frequently Asked Questions

ASTONTO is an independent AI research company that studies the observable behaviour of large language models and AI recommendation systems.

ASTONTO researches how AI platforms interpret corporate information, resolve entity identity, select citation sources, compare alternatives, and generate brand recommendations across platforms, locations, and languages.

ASTONTO is an independent research company. AnswerSignal is our applied commercial service that provides empirical AI Search Visibility audits and optimisation sprints for corporate clients.

Black-box AI evaluation is the scientific observation of publicly accessible AI outputs under controlled prompt conditions, measuring real-world model responses without claiming internal access to proprietary code or weights.

No. ASTONTO evaluates observable outputs from public and enterprise interfaces. We do not claim access to proprietary model weights, hidden ranking algorithms, or undisclosed vendor update schedules.

ASTONTO enforces strict methodology controls, preserves verbatim output logs, and refuses commercial arrangements that mandate specific research findings or ranking outcomes.

AnswerSignal is ASTONTO's applied AI Search Visibility product. It measures how ChatGPT, Perplexity, Gemini, and Google AI Overviews recommend a company compared with four selected competitors.

AI Search Visibility is the degree to which an organisation is accurately cited, prominently positioned, and positively recommended by generative AI engines when prospects ask commercial buyer queries.

AnswerSignal evaluates ChatGPT (OpenAI), Perplexity, Gemini (Google), and Google AI Overviews.

An AI mention occurs whenever a brand name appears in an answer. An AI recommendation occurs when the AI engine explicitly endorses the company as a preferred solution for a specific buyer context.

AI engines rely on clear entity resolution, structured data, and third-party citation density. Market leaders with weak digital entity signals or fragmented third-party references are often omitted by LLMs.

No. Commercial AI engines operate non-deterministically. AnswerSignal identifies visibility gaps and implements evidence-based improvements, but does not guarantee future AI recommendation outcomes.

Competitors are selected during audit scoping based on direct commercial overlap, geographic market rivalry, and buyer evaluation context.

AI platforms draw from different index sources, user IP geolocations, and linguistic models, resulting in distinct vendor recommendations across geographic markets.

Because commercial LLMs update continuously, baseline benchmarking should be performed quarterly, supported by ongoing monthly monitoring for high-value buyer prompts.

The PULSE Method is ASTONTO's proprietary framework for calculating multi-platform AI recommendation visibility, prominence, sentiment, and competitor performance.

A PULSE Score measures observed AI recommendation strength across position, endorsement classification, sentiment, and prompt importance.

PULSE Reliability indicates statistical confidence based on prompt volume, repeat test runs, platform coverage, and testing duration (High, Medium, or Indicative).

A PULSE Benchmark Score establishes an organisation's baseline AI visibility score at the start of an audit or optimisation sprint.

A PULSE Market Score measures visibility across a defined geographic or sector market segment.

PULSE Share of Voice measures your company's relative visibility and recommendation win rate compared with four selected competitors.

Negative sentiment, hallucinated errors, or cautionary disclaimers reduce the Sentiment Factor in the PULSE formula and are flagged as Reputation Risks.

LLM outputs are stochastic. Running 5–10 iterations per prompt ensures reliable measurement of true underlying recommendation consistency.

The audit evaluates your company plus four competitors across four AI platforms, delivering a PULSE Score, preserved evidence log, Reputation Risk analysis, and live presentation.

The 90-day sprint includes entity and technical clarity fixes, answer-ready content expansion, third-party authority building, gap closure, and final retesting.

Key improvements target entity schema resolution, answer-ready site content structure, third-party profile consistency, and authoritative industry citations.

Pricing is calculated based on market scope, language requirements, prompt volume, and implementation depth. Live scope confirmation is provided before agreement.

Yes. The 24-Hour AI Visibility Audit fee is credited toward the 90-Day Optimisation Sprint when agreed within the approved timeframe.

AI Visibility Monitoring tracks monthly PULSE Score movements, competitor overtakes, prompt changes, negative sentiment alerts, and LLM model updates.

To begin an audit, we require your corporate domain, primary geographic markets, key service offerings, and four selected market competitors.