Probe
Fixed geo-local prompts across major assistants — same wording, logged models, scheduled runs.
Local AI discovery ops
Many assistants. One accord for every location.
Measure how ChatGPT, Claude, and Perplexity recommend you — fix what they get wrong — and prove dispersion drops week over week.
Live probe
Best matcha · West Village, NYC
Dispersion
0.74
Mention rate
38%
Fact errors
2
The gap
A matcha bar in the West Village loses foot traffic when Claude omits you, Perplexity ranks you fourth, and ChatGPT lists the wrong hours. Operators need per-place visibility — not one logo on a national chart.
New York City · prompt pack
“Best matcha in the West Village”
Workflow
Fixed geo-local prompts across major assistants — same wording, logged models, scheduled runs.
Ranked lists, citations, and factual claims → mention rate, dispersion, competitor share.
Tasks tied to directories, reviews, and listicles models actually cite — not generic SEO.
Weekly re-probes and location reports operators can act on — and investors can trust.
Outcomes
↓ 40%
Dispersion index
Cross-engine disagreement on rank and presence.
38%
Mention rate
Prompts where your location appears at all.
0
Fact errors
Wrong hours, address, or category — tracked to zero.
3.2
Mean rank
Average position when you land in the recommendation set.
Technology
We probe several assistants to capture platform drift. The Anthropic Claude API structures extraction, scoring, recommendations, and weekly location reports — with evals tuned for model updates.
We're not selling another mention chart. We bring every engine into accord — lower dispersion, correct facts, for every pin on the map.
Pilot program
New openings and multi-location F&B in New York City — baseline probe, fix queue, weekly re-probes, and a final dispersion report for operators and investors.
Early access
Share your brand and location count — we'll reply with cohort availability and onboarding steps.
Prefer email? hello@getaccord.com