Multi-model answer capture
We run your prompts on the same providers your buyers use — and we keep historical runs so you can see what changed when a model updated.
How it works
From invisible to cited, in four steps.
Intendity is an end-to-end AI search optimization workflow — from monitoring every answer ChatGPT, Claude, Gemini and Perplexity generate, to telling you the exact content and citations that will move the needle.
The four steps
- 01
Add your brand
Drop in your brand name, your domain, and the competitors you care about. We pre-fill descriptions and category from public sources so you can move fast.
Setup is intentionally minimal — most teams are running their first prompts within five minutes. You can add as many brands as your plan supports and re-use prompts across them.
- 02
Define the questions buyers ask AI
Comparison prompts, evaluation prompts, problem-solving prompts. We seed a starter set based on your category and competitors; you refine to match how your buyers actually phrase things.
Prompts are organised by intent — research, evaluation, decision — so you can see exactly where in the funnel you're winning or losing. Bulk import is supported.
- 03
Run across every model in parallel
ChatGPT, Claude, Gemini and Perplexity answer the same prompts at the same time. Every answer is captured, tagged, and scored — no manual screenshots, no copy-paste.
Runs can be triggered on-demand or scheduled. We capture model versions, regions and language so you can compare like-for-like and watch trends across releases.
- 04
Get prioritized recommendations
Specific content to publish, structured-data fixes, and PR moves — ranked by impact and tied to the actual citations driving each gap.
Every recommendation links back to evidence: the prompt, the answer, the cited source, and the competitor that's currently winning. Hand it to your content team and ship.
What's under the hood.
Six capabilities that make AI visibility measurable, comparable and improvable.
Citation extraction
We surface the URLs each model cites — Wikipedia, Reddit, trade press, listicles — so you know exactly which sources you need to win.
Visibility & sentiment scoring
Mention rate, share-of-voice and sentiment, scored per prompt and per model. Trended over time and benchmarked against competitors.
Competitor benchmarks
Track named competitors automatically. See exactly which prompts they win, how they're being described, and which sources are driving the gap.
Locale & language splits
AI answers vary by region and language. We capture each locale separately so localised PR and content work can target real visibility gaps.
Actionable playbooks
Every score comes with a recommended next move — content, citations, structured data — sorted by expected lift.
How fast you'll see movement.
Visibility data is instant. Visibility gains follow a predictable curve.
- Day 1
Your first run captures answers across ChatGPT, Claude, Gemini and Perplexity. You see exactly where you appear and where you don't.
- Week 1
Recommendations rank by expected impact. Most teams pick 3–5 plays — a Wikipedia source, a category roundup, a structured-data fix.
- Week 2–6
Models pick up new sources as they're crawled and re-indexed. You'll see net-new mentions appear and sentiment shift on tracked prompts.
- Quarter+
Compounding wins. Each citation you secure becomes input for adjacent prompts, expanding share of voice across your category.
Ready to see your AI visibility score?
Free during beta. First brand set up in under five minutes.