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5 prompts × 4 models, one-shot. A real Foxish account runs 150-550 prompts per scan, weekly or daily cadence depending on plan across 5 models with weekly or daily refreshes with full historical trends, alerts, citation tracking, and ai-generated content fixes.
Foxish sample report · September 6, 2026
AI Visibility Report: Fracta
fracta.ai · Water utility asset intelligence
Visibility score
Based on 5 prompts × 4 models
Discovery score
How often AI surfaces Fracta unprompted
Your equivalent — in 60 sec
See how AI talks about your brand across 5 models with weekly or daily refreshes and history.
Start free trialIn a full Foxish account: Foxish tracks visibility & discovery scores week-over-week and alerts you on drops of 5+ points. This sample only shows a single point in time.
Performance by AI model
All 4 base-plan models · Perplexity available as add-on
Not mentioned in any of the 5 sample prompts. ChatGPT is the largest AI surface by user count — this is Fracta's single biggest visibility gap.
Mentioned in 2/5 prompts. Ranked #3 for main-break prediction and cited in-prose for pipe-replacement prioritization — Claude has the best per-mention placement across the base models.
Mentioned in 2/5 prompts (water main break prediction + water infrastructure risk analytics), both at position #7 — buried below Xylem, VODA.ai, and Autodesk/Innovyze.
Mentioned in 1/5 prompts at position #3 — strong when it fires, silent on the broader queries.
Available as add-on. Mentioned in 1/5 prompts, ranked #3 — strong placement when surfaced but misses 4 of 5 core queries.
In a full Foxish account: Foxish runs ChatGPT, Claude, Gemini, Google AI Overview on every paid plan with full web-search-grounded responses. Perplexity is available as add-on. Each model gets per-prompt drill-down so you can read the exact response text Foxish captured.
Competitive snapshot
Top 6 of unlimited
In a full Foxish account: Track unlimited competitors with week-over-week deltas, sentiment scoring, share-of-voice trends, and AI-recommended counter-positioning when a competitor surges past you.
AI queries we tested
5 of hundreds
“What's the best AI tool for predicting water main breaks?”
In answerRecommended: VODA.ai, Xylem, Autodesk, Innovyze, InfoWater
“Software for water utility asset management and risk assessment”
Not in answerRecommended: Xylem, Autodesk, Innovyze, Bentley, Trimble Cityworks, VODA.ai
“Best predictive maintenance platforms for wastewater infrastructure”
Not in answerRecommended: Xylem, Autodesk, Innovyze, Bentley, Trimble Cityworks
“How can utilities use AI to prioritize pipe replacement?”
Not in answerRecommended: VODA.ai, Xylem
“Top vendors for water infrastructure risk analytics in 2026”
In answerRecommended: Xylem, VODA.ai, Autodesk, Bentley, KETOS, Klir, Sensus
In a full Foxish account: Foxish runs 150-550 prompts per scan from a category-specific prompt library, plus your own custom prompts. Scans run weekly or daily depending on plan. Every AI response is stored — you can read the full text, see the citations, and track how recommendations shift over time.
Top recommendations
Sample: 3 of usually 10-20
Close the ChatGPT gap: get Fracta into 3 vendor-comparison articles ChatGPT cites
High priorityChatGPT surfaced Fracta in 0 of 5 sample prompts — the exact opposite of Gemini and Perplexity, which both name Fracta on the core "water main break prediction" query. ChatGPT's citation graph for utility software leans on WaterWorld magazine, Utility Dive, Global Water Intel, and consulting-firm reports (Bluefield Research, S&P Global). None of them currently rank Fracta in a top-5 vendor list. Action: Pitch Fracta's EBMUD case study + measurable break-prediction accuracy to WaterWorld and Utility Dive as an editorial byline. Target 3 placements in Q4 2026. Re-run the Foxish scan monthly to track ChatGPT ranked-mention pickup.
Estimated impact: ChatGPT mention rate 0% → 40% within 90 days. Potential 3-5× lift in AI-referred inbound leads from utility procurement teams.
Own the "asset management" and "pipe replacement" queries: publish 2 comparison pages
High priorityFracta is invisible on 3 of 5 sample queries: "software for water utility asset management," "predictive maintenance for wastewater," and "how utilities use AI to prioritize pipe replacement." Instead, all four AI models cite Xylem, Autodesk/Innovyze, Bentley, and Trimble Cityworks — broad ERP/CMMS vendors, not AI-native. Action: Publish two comparison pages on fracta.ai: (1) "Fracta vs Innovyze InfoAsset: AI-first vs traditional asset management" and (2) "Predicting pipe failures: Fracta's ML models vs traditional condition-based scoring." Both should include concrete accuracy metrics, case study data, and Schema.org FAQPage markup. Distribute via LinkedIn to utility director/manager audience.
Estimated impact: Broadens Fracta's category authority beyond "main break prediction" into the full asset management stack. Estimated +25-30 aggregate visibility points across Gemini and Perplexity.
Compete with VODA.ai head-to-head on the queries where they're winning and you're missing
MediumVODA.ai is Fracta's most direct AI competitor — both are AI-native water infrastructure risk platforms, but VODA.ai gets cited on 4 of 5 queries vs Fracta's 2 of 5. VODA.ai appears in almost every AI answer where Fracta doesn't. Action: Publish a public head-to-head technical brief ("Fracta vs VODA.ai: pipe-failure prediction methodology comparison") that clearly differentiates the two on model accuracy, deployment complexity, and integration depth. Get it referenced by at least one industry analyst (Bluefield Research, Global Water Intel) and syndicate to the American Water Works Association (AWWA) journal. AI models heavily weight AWWA citations for this category.
Estimated impact: Move from #4/#5 mention position to #1/#2 in queries where both vendors currently appear. Estimated +15 visibility points overall.
In a full Foxish account: Full accounts surface 10-20 prioritized recommendations including specific schema fixes, content briefs, citation-target outreach lists, and one-click AI-generated content drafts for each gap.
What this sample doesn’t show
This page is a one-shot snapshot of 1 prompt × 4 models. A real Foxish account is meaningfully deeper across six areas:
Coverage & cadence
- 150-550 prompts per scan (this sample is 1)
- Weekly or daily refreshes with full historical trends
- Perplexity add-on for additional model coverage
Deeper analysis
- Per-prompt drill-down with full AI response text
- Citation tracking — which sources AI cites about you
- Knowledge graph showing brand co-mentions
- Trend charts over time per model and competitor
- Category benchmarks — your scores vs. industry average
- Sentiment scoring on every mention
- Discovery vs. brand-direct query separation
Competitor & community intelligence
- Unlimited competitor tracking with share-of-voice
- Community monitoring across Reddit, X, and Instagram
- Draft-response generation for community mentions
Action
- AI-generated content drafts for each recommendation
- Website intelligence — AEO + schema audit
- Custom prompt library tuned to your category
- Prompt Lab to test your own queries
Workflow & integration
- Real-time alerts when scores drop or competitors gain
- Scheduled email reports + Slack notifications
- REST API access (Pro plan and up)
- Multi-user team collaboration
Agency plan adds
- White-label branding and per-client dashboards
- Bulk CSV import (up to 100 clients)
- Pitch reports for new client acquisition
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Sample reports are illustrative and use publicly-available information about each brand. Foxish does not represent that Fracta is a customer or partner.