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Monitoring workflow for up to 9 AI engines with 8 detection layers depending on setup: Prompt set, AI run, Source/Citation Samples, Response Snapshots, Competitor Deltas and Recheck Proof.
Live analysis
Beconova Visibility Layer
Source/Citation Samples
Signal 01
Response Snapshots
Signal 02
Competitor Deltas
Signal 03
Comparison
Beconova product path
Tracker -> AI-readable Data Layer -> Proof Loop. Beconova is not only a tracker. Not an AI SEO OS clone: the tool connects observed AI answers with machine-readable data delivery and a traceable action, recheck and report workflow.
Prompts, providers, mentions, sources, citations, sentiment and Competitor Deltas are monitored as repeatable samples.
Proof: Response Snapshots show what was observed and with which confidence.
Snippet, WAI, llms.txt, product feeds, service feeds and schema data make maintained content machine-readable.
Proof: feed, snippet, crawler and schema evidence show technical delivery.
Actions are prioritized, rechecked after implementation and documented as a report handoff.
Proof: action, recheck, delta and versioned report remain traceably connected.
Product language
AI Visibility is the buyer-facing product name: tracker + AI-readable Data Layer + Proof Loop.
Observed signals and proof artifacts, not a ranking or citation guarantee.
Context
AI engines change answers by prompt, provider, language, timing and available sources.
Without monitoring, teams often notice changes late. A visibility tool checks defined prompts regularly, compares results over time and shows when competitors or false facts appear.
Beconova separates measurement from optimization: monitoring shows the change, the dashboard prioritizes the next actions, and hosted feeds deliver AI-readable data through the snippet.
Beconova solution
You define relevant queries, such as best [product type] for [audience], [city] [service] provider or [product] alternative. Beconova checks these prompts across enabled engines.
Each run creates Response Snapshots with mentions, Source/Citation Samples, competitor mentions and confidence cues. That turns isolated answers into a comparable timeline.
After an action is implemented, Recheck Proof closes the loop: did the answer change, which source appeared, which Competitor Delta remains open and which claim is still wrong?
Dashboard proof
Buyers should not only hear that Beconova measures. They should understand which proof artifacts later appear in the dashboard and report.
Artifact 01
Stores prompt, provider, answer text, timestamp, sentiment, source state and competitor context for each run.
Proof: repeatable answer sample instead of a manual one-off check.
Artifact 02
Separates mention, cited URL, extracted source, missing source and confidence cue.
Proof: source quality becomes visible without promising citation success.
Artifact 03
Connects implemented actions with the next prompt run, delta and report handoff.
Proof: action, recheck and result remain traceably connected.
Proof Delivery Journey
From website promise to dashboard review: every observation gets visible proof and lands in the report handoff.
01 Dashboard
The buyer sees prompt, provider, answer, sentiment and competitor context as dashboard proof.
Next steps02 Sources
Mention, cited source, missing source and confidence are separated instead of promising citation success.
Next steps03 Report
Action, recheck, delta and report handoff stay connected as the Proof Loop.
Next stepsDemo and Proof Handoff
After the Proof Loop, the page leads directly to demo, dashboard tour and report evidence.
Product modules
Every observed answer separates mention, cited URL, extracted source and missing source. You see whether a model only mentions you or backs the answer with evidence.
Answer text, provider, prompt, timestamp, sentiment, hallucination signal and source state are stored as a snapshot.
The tool shows which competitors appear, replace you or move ahead on sources and citations.
After an action, the same prompt is checked again. The timeline shows whether mention, citation, source or competitor state changed.
Comparison
Prompt set -> AI run -> Response Snapshot -> Source/Citation Sample -> Competitor Delta -> Action -> Recheck instead of asking once.
Next steps
Consensus scoring workflow.
02The data layer beneath monitoring.
03How the AI-readable Data Layer is technically delivered.
04Details on detecting and correcting false AI claims.
05Which AI bots crawl your site?
06Basics and use cases.
07Plans from €59/month.
FAQ
Configured queries are checked regularly across the providers enabled for the plan. The dashboard shows fresh observations after each completed run.
A verifiably false statement about your business, for example wrong prices, wrong addresses, invented products or false personal data.
Yes. Manual findings can be documented and routed into correction workflows where the data-authority mechanism applies.
Manual checks are biased and not repeatable. Monitoring uses consistent prompts, multiple providers and historical comparison.
Yes. The system records competitor mentions and shows how your visibility changes over time.
It is most useful once you have recurring relevant search demand. For very small demand, technical data quality and classic SEO may come first.
Ready to start
Alerts and monitoring evidence depend on setup, source quality and enabled providers. Beconova shows what was observed, not a ranking guarantee.
View pricing