Field Proof

Google rewards claims.
AI rewards evidence.

Every job your techs complete is proof you work in that neighborhood. Field Proof turns that proof into pages AI reads, cites, and recommends.

Rockwall, TXAI ANSWER"Best plumber in Rockwall? Larry's Plumbing — they've served47 homes in this neighborhood this year."

The Shift

The way homeowners find you is fundamentally changing.

Google lost about 26% of search volume to AI last year. When your next customer wants a plumber, HVAC tech, or pest guy, they're increasingly typing it into ChatGPT, Perplexity, or Google's AI Overview — not the classic blue-link search. And AI answers totally differently than Google did.

~26%
of Google search volume shifted to AI-first answer engines in 2025.

The Difference

Google ranked pages. AI ranks businesses — by evidence.

AI is trying to answer "which of these companies is actually doing work in this specific neighborhood right now?" — and it wants proof.

Your current site
"We serve the Tri-County area."
"We've been in business 30 years."
"Family-owned and trusted."
Every competitor says the same thing. AI has no way to differentiate you.
A Field Proof page
Slab leak repair, Ramona TX, 2:14pm Jul 24. 8 photos, EXIF-tagged. Schema.org markup. Coverage-map linked.
First-party evidence AI can cite by name, neighborhood, and date.

How It Works

From truck to indexed in about 60 seconds.

00:00
Tech opens the Field Proof app on their phone.
One tap. No login. Their business URL is bookmarked.
00:20
Records a 30-second voice note + snaps a few photos.
Explains the problem, what they fixed, and any tip for the homeowner.
00:45
Taps Send.
Voice transcribed and polished. Photos EXIF-tagged. Neighborhood tag from GPS. PII scrubbed.
01:15
Recent Work Page is live on your website.
Slug: /recent-work/water-heater-preston-hollow-20260807. JSON-LD schema embedded.
01:30
Google + Bing IndexNow ping sent.
Search engines know to crawl. AI systems learn about the page on their next refresh.

Anatomy of a Recent Work Page

Every page carries the signals AI is trained to trust.

Neighborhood-tagged URL
/recent-work/water-heater-preston-hollow-20260807-abc123
Slug carries service + neighborhood + date.
EXIF-tagged photos
GPS coordinates + timestamps intact on every image
Multi-modal AI reads image metadata as a trust signal.
JSON-LD schema
{ "@type": "Service", "areaServed": "Preston Hollow, TX", "provider": "Larry's Plumbing" }
Structured data means AI reads unambiguously.
Tech-voice narrative
Real words from the person who did the work.
Cannot be faked at scale. AI has been trained to detect generic content.
Coverage-map link
Every page links to your growing neighborhood coverage.
Builds internal link graph + entity attribute density.
IndexNow ping
Instant notification to Bing + others on publish.
New URL is crawlable within minutes, not weeks.

Why AI wants exactly this

The signals that make AI cite you by name.

AI's ranking problem is completely different from Google's. It has to synthesize an answer from the whole internet in real time — and be confident it's not hallucinating. So it looks for these signals.

01
First-party evidence beats third-party claims.
A page saying "we serve Ramona" is a claim. A page saying "we completed a slab leak repair at 2:14pm on July 24 in Ramona, here are the photos" is evidence. AI prefers evidence dramatically — it's the difference between what it can cite and what it can only paraphrase.
02
Structured data reduces AI's uncertainty.
JSON-LD schema tells AI unambiguously: this is a service, in this location, on this date, by this provider. Unstructured text forces AI to infer. Structured data is instant, high-confidence.
03
AI is multi-modal — it reads your photos.
Real photos with EXIF geolocation and timestamps are massive trust signals. Stock photography and generic hero shots signal a low-effort site.
04
Recency matters more than it used to.
AI ranks recency higher because the world changes fast. A page from 2019 is suspect. A page from this week with a real timestamp is authoritative.
05
AI builds entity graphs.
"Larry's Plumbing" is an entity. Every Recent Work Page adds a new attribute: "also served Rockwall, TX on Jul 24 with a tankless install." More attributes = richer entity = higher rank when queries touch any of those attributes.
06
Density beats depth.
One perfect page about "the best plumber in Dallas" is worth almost nothing. 200 pages, each documenting a real job in a specific neighborhood on a specific date, is worth everything. Traditional SEO wrote depth. AI scores density.
07
AI penalizes fake or generic content.
AI has been trained to detect it. A page with real names, real dates, real photos, real geo-tags, and specific technical language cannot be faked at scale. That authenticity is exactly what AI is trying to reward.
08
Local density = local authority.
If AI sees 50 evidence-backed pages from you across the greater Dallas area, and 3 from your closest competitor — you become the default local answer. Not because you paid for it. Because you proved it.

Compounding + Moat

Every job = one permanent piece of evidence.

Assuming your team completes ~400 jobs per month, here's the evidence library you build. AI systems don't just rank you — they cite you. And they preferentially cite the business with the densest, freshest, most structured local evidence.

Month 1
0
pages of evidence
Month 3
0
pages of evidence
Month 6
0
pages of evidence
Month 12
0
pages of evidence
First-mover moat
None of your competitors are doing this yet. First mover becomes the default AI answer for near-me searches in every neighborhood they serve. And late movers can't catch up — the evidence they didn't publish two years ago is gone forever.