Profound ↗
Enterprise answer-engine intelligence and reporting are preferred.
← All toolsAnother direction / 01 Another direction / 02 Another direction / 03 Another direction / 04
The selection guideSource-backed research ↗
AI Search Monitoring / AI visibility monitoring and answer-engine evidence
Proofsource
AI visibility monitoring that shows which buyer questions name you and who gets named instead
AI visibility monitoringCitation analysisGEO/AEO diagnosis
Why it stands out
Question-level answers show who is named and which pages are cited.
Source review: · Public-source research, not a hands-on test
↗ Best for
Teams needing question-level AI visibility and competitor answers.
! Know before you buy
No checked source proves citation precision, repeatability, causal visibility lift, traffic, conversion, or revenue impact.
01 / Editorial assessment
Is Proofsource for you?
The AICiteKit take
Proofsource is a credible new entrant for teams that want AI-search observations tied to buyer questions and the sources behind them. Official pages document answer records, citations, competitors, sentiment, crawler checks, fixes, exports, API, and MCP, while the pricing page exposes a $9/month starting configuration and a no-card trial. The evidence is stronger for advertised scope than for accuracy or outcomes: a Hacker News launch post is maker-authored, and no checked source proves citation precision, repeatability, customer satisfaction, traffic lift, or revenue impact. Run a fixed-prompt pilot and manually validate a sample before treating aggregate movement as evidence.
A good fit if you are…
- Teams needing question-level AI visibility and competitor answers.
- SEO, content, marketing, and agencies that need cited URLs and exportable evidence.
- Buyers wanting a low-cost trial before expanding engine and question coverage.
- Technical teams evaluating API or MCP access alongside a dashboard.
Consider another option if…
- Buyers requiring independently benchmarked citation accuracy.
- Teams wanting guaranteed traffic, conversion, or revenue outcomes.
- Organizations needing a fully published enterprise API, retention, or white-label contract.
- Users who need unlimited multi-engine monitoring at the $9 starting price.
02 / Scope, not promises
Features & coverage
- Named engines and methods
ChatGPT, Perplexity/Sonar, Claude Haiku 4.5, and Google AI Overviews; fallbacks and model metadata are documented.
Archived research · Confirm current contracted engines, regions, and versionsResearch excerpt · Engine and model coverage- Public starting price
$9/month for five ChatGPT questions checked weekly; pay per brand and question.
Archived research · Official pricing page checked 2026-10-28; confirm plan matrix and usage boundariesResearch excerpt · Pricing, trial, and limits- Free trial
200 answers, 25 prompts/questions, top AI engines, two days, no card.
Archived research · Official pricing page checked 2026-10-28Research excerpt · Pricing, trial, and limits
Question-level visibility and citations
Proofsource records the buyer question, answer, named brands, cited pages, sentiment, and model detail when available. This establishes the documented workflow, not independent extraction accuracy.
Pricing and trial boundary
The public starting signal is $9/month for five weekly ChatGPT questions, with a two-day no-card trial offering 200 answers and 25 prompts/questions. Confirm higher coverage and engine entitlements.
Exports, API, and MCP
Official documentation says answers and citations can be exported as CSV, prompts and engine searches as CSV or JSON, and API/MCP access is available; plan scope must be confirmed.
Evidence and outcome limits
No checked source independently validates citation precision, repeatability, customer satisfaction, or causal business outcomes. The HN launch post's adoption figures are vendor-reported.
A focused evaluation workflow
- Define brands, competitors, buyer questions, topics, markets, and engines.
- Run recurring checks and inspect answers, mentions, citations, sentiment, and model details.
- Review uncertainty intervals and distinguish movement from answer variation.
- Use crawler findings, ranked fixes, content drafts, alerts, exports, API, or MCP as appropriate.
- Repeat comparable prompt and engine cells and validate a sample manually.
03 / Commercial boundaries
Pricing & limits
Terms below reflect the 2026-10-28 source review, not a new live quote. Confirm currency, billing term, tax and required scope with the provider.
- Public starting price
$9/month for five ChatGPT questions checked weekly; pay per brand and question.
Archived research · Official pricing page checked 2026-10-28; confirm plan matrix and usage boundariesResearch excerpt · Pricing, trial, and limits- Free trial
200 answers, 25 prompts/questions, top AI engines, two days, no card.
Archived research · Official pricing page checked 2026-10-28Research excerpt · Pricing, trial, and limits
Your buying checklist
Get these answers first.
- Which exact engines, models, regions, languages, and provider fallbacks are included in this plan?
- How are question, answer, engine, cadence, and historical-retention units billed?
- Can buyers export raw answers, citations, prompts, timestamps, and model metadata?
- How are the 95% intervals calculated and how are prompt/model changes handled?
- What are the API, MCP, retention, deletion, team, cancellation, and data-use terms?
Pricing context & qualifications
Research checked 2026-10-28. The official pricing page shows pay per brand and question, from $9/month for five ChatGPT questions checked weekly, plus a two-day no-card trial with 200 answers and 25 prompts/questions. Confirm engine multipliers, cadence, quotas, history, API/MCP access, retention, and cancellation.
04 / The tradeoffs
Strengths & weaknesses
Reasons to shortlist
- Question-level answers show who is named and which pages are cited.
- Public docs explain engine collection and model-recording behavior.
- Uncertainty intervals help distinguish movement from noise.
- Broad workflow includes crawler access, fixes, content, alerts, API, and MCP.
- Published entry price and no-card trial lower pilot friction.
Reasons to pause
- No independent benchmark of citation precision, recall, sentiment, or repeatability.
- Provider fallbacks and model changes can alter the observation process.
- Question, engine, cadence, answer, and history limits require plan confirmation.
- No checked source proves causal visibility lift, AI traffic, conversion, or revenue.
- HN customer and usage figures are vendor-reported, not independent feedback.
No checked source proves citation precision, repeatability, causal visibility lift, traffic, conversion, or revenue impact.
05 / Choose by the job
Alternatives to consider
Editorial fit comparisons—not performance rankings or claims that one option always wins.
Otterly.AI ↗
Managed recurring SaaS monitoring is preferred.
Peec AI ↗
Focused AI-search visibility tracking is preferred.
CiteLadder ↗
Open-source or self-hosted implementation is preferred.
06 / What we can substantiate
Reviews & evidence
No product-specific rating sample or controlled external benchmark was found. The Hacker News post is maker-authored and reports early adoption; it does not validate accuracy, customer satisfaction, repeatability, or outcomes.
AICiteKit assessment: public-source research, not a hands-on product test. Official materials establish stated scope; reviews are dated and may concern the broader platform. Neither establishes guaranteed citations, traffic or revenue.
Sources & original verification dates
| Source | Evidence type | Checked |
|---|---|---|
| Proofsource official homepage ↗ | Official product page | |
| Proofsource pricing ↗ | Official pricing and trial page | |
| Which AI engines and models Proofsource asks ↗ | Official documentation | |
| Export Proofsource data, or reach it over the API and MCP ↗ | Official documentation | |
| Show HN: Proofsource ↗ | Community launch discussion; maker-authored evidence | |
| Proofsource Product Hunt listing ↗ | Launch/discovery context; not efficacy evidence |
Original review evidence & date context
Preserved from the published research. Dates, review counts and product-scope qualifications below have not been refreshed by this layout migration.
Evidence checked 2026-10-28. Official pages support product identity, question-level visibility, named engine methods, citations, exports, API/MCP, and pricing/trial boundaries. Hacker News provides a maker-authored launch post with reported early adoption, not an independent test. No checked source proves citation precision, repeatability, customer satisfaction, causal visibility lift, AI traffic, conversions, or revenue.
Pilot checks
- Freeze prompts, engines, models, regions, languages, and dates.
- Export raw answers, citations, timestamps, and model metadata.
- Human-review a stratified sample of mentions, citations, and sentiment.
- Recheck results after provider/model changes.
- Confirm plan, API/MCP, retention, deletion, and provider-data terms.
Research notes & unresolved discrepancies
- Official homepage, pricing, engine/model docs, and export/API docs checked 2026-10-28.
- Hacker News Show HN post checked as maker-authored launch context, not independent validation.
- Product Hunt listing was treated as launch/discovery context only.
- No product-specific rating sample or controlled benchmark was found.
Layout migration: October 4, 2026. The original MDX research is retained in the repository; this reorganization does not refresh its factual verification dates.