EchoScan
Score recorded answer-engine evidence for your brand — and competitors
EchoScan stores analyst-captured responses, scores recorded brand mentions and competitor share of voice, and compares compatible runs. It does not reproduce proprietary ranking systems, automate provider capture today, or guarantee rankings or citations.
The analyst-capture workflow is implemented, and automated multi-engine capture is built too — it runs for EchoScan Monitor subscribers once enabled, and stays off until the owner activates it.
AI Narrative Monitor
Illustrativeprompt · “best [category] tool for teams”
The problem
Generated answers are a separate evidence surface.
A provider may mention, omit, or frame a brand differently for each prompt, model, geography, and point in time. EchoScan records analyst-captured responses so those defined observations can be reviewed; it does not infer buyer behavior or a universal consideration set.
Schema-derived prompts
EchoScan derives candidate buyer and category questions from reviewed site content. The analyst decides which prompts and providers enter the evidence cohort.
Measured, not guessed
Each captured answer is scored for whether your brand appears, the competitors that appear instead, and your share of voice — labelled by confidence, never fabricated.
Alerts on change
When compatible recorded runs show a change, configured alert rules can flag it for review. A recorded change is evidence for that prompt cohort, not a universal ranking result.
EchoScan preview — sample
IllustrativeYour brand: not detected
Appeared instead
This illustration is not a live provider response or market result. EntityMesh can structure approved answers for retrieval, while compatible captured runs are still required to show whether a provider mentions them.
Brand presence
Whether AI answer engines mention your brand for the buyer and category questions that matter.
Competitor share-of-voice
How often competitors are named instead of (or alongside) you across the same controlled prompts.
Narrative & sentiment
How your brand is framed when it does appear — positive, neutral, mixed — and where the framing is weak.
Drift over time
Changes in mention rate, share-of-voice, and framing across runs, with alerts when the signals move.
How it works
- You define the brands, competitors, and prompts included in the evidence cohort.
- Each prompt is put to the answer engines and the responses are captured into the workspace — analyst-entered, or captured automatically across engines with an EchoScan Monitor subscription.
- Each response is scored for brand mention, competitor share-of-voice, and framing.
- Compatible runs can be compared for drift, and reviewed weak spots can inform later build work.
Build first, monitor second
EchoScan's recorded findings can be reviewed alongside EntityMesh build work. A gap does not automatically create or publish content, and a later change is attributed only when compatible before-and-after evidence supports that conclusion.
How EntityMesh buildsPricing
Monitoring plans
These prices describe published future scopes. EchoScan self-service subscription checkout and typed paid fulfillment remain closed; use a reviewed request and do not expect an automatic purchase.
Starter
$79/month
Published future scope — not self-service.
- Proposed capacity: 15 analyst-captured prompts / month
- Responses may be captured from named providers with source receipts
- Implemented share-of-voice scoring for recorded evidence
- Configured competitor-alert rules
Pro
$149/month
Published future scope — not self-service.
- Proposed capacity: up to 50 active prompts
- Analyst-captured provider evidence
- Implemented sentiment and drift scoring on recorded runs
- Competitor share-of-voice views for compatible cohorts
Evidence is always labelled proof-grade, directional, or insufficient. Engine answers can be analyst-captured and then scored, or captured automatically across engines with an EchoScan Monitor subscription. EchoScan reports what the engines say — it never claims proprietary access to answer-engine rankings, and never guarantees rankings or citations.
Proof
Built on the same method we run on ourselves.
The public EntityMesh demo includes a safe sample support center and report shape. No external-client citation, before-and-after outcome, or commercial monitoring result is attached, so this is implementation proof — not an outcome claim.