Where you stand in AI answers, and why.
Everything on this side of the product is a read of what the engines actually said. Every number opens onto the answer that produced it, so nothing here is a figure you have to take on trust.
Visibility heatmap
Every buyer question you track, graded on every engine. One grid shows where you rank, where you are only mentioned, and where a rival won the answer outright.
Query fan-out
A buyer types one question and the engine runs a dozen searches behind it. Limelit captures those fan-outs, explicit and inferred, per engine, so you write for what AI actually asked.
Prompt demand signals
A banded reading of how much real demand sits behind each prompt you track, so you can rank a list of prompts by the ones worth winning.
New this week. Details below.
Trends, share of voice and sentiment
Tracked per engine and per prompt, over any window you pick, so a movement in the number always opens onto the answer that moved it.
Top cited sources
The pages and publications each model leans on in your category, grouped by source type, with the ones you own separated from the ones you do not.
Every answer, kept
The full text of every answer every engine gave, with citations pinned. Nothing is summarized away, so a claim can always be traced back to its run.
Which prompts are worth winning, without inventing a number.
No AI engine publishes how often a prompt is asked, and every count on the market is modeled from a tiny opt-in panel. So Limelit refuses to print one. Each prompt gets a band from very low to very high, and the badge tells you which signals produced it.
Search
Estimated monthly search volume for the prompt, priced from its own text when it carries no source keyword.
Referral
Back-solved from the AI referral sessions landing on the pages that prompt cites, weighted by your share of voice on it. This is the layer that needs data only Limelit holds.
Topic
The typical volume across the rest of the prompt's topic cluster, computed leave-one-out so a prompt is never averaged into itself.
A prompt we cannot score shows no badge at all.
That distinction is the whole point. Collapsing "we have no data" into "this prompt has no demand" is the one mistake a demand reading cannot afford, so a prompt with no signal is left blank rather than scored low.
A gap becomes a scored action and a drafted fix.
Other tools hand you a dashboard and wish you luck. Every finding in Limelit carries the next move, and the work that follows is written against the exact sources the models cite today.
Cross Check
Reads the claims a model makes about you and verifies each one against versioned Knowledge Sources you control. Verdicts pin the exact source version they read.
Corrections and drafts
A wrong claim or an unowned answer becomes a drafted fix, grounded in your own sources and brand kit, scored against the pages the model cites today.
Plan
Every gap worth closing as a scored opportunity with a status derived from live citation data, not a checkbox someone forgot to tick.
Site health and crawlability
Per-bot robots.txt results for GPTBot, ClaudeBot, PerplexityBot and the rest, plus an AI readiness score for how easily an engine can read, quote and cite your pages.
Approval inbox
Nothing Limelit writes ships on its own. Every draft, correction and outreach message waits for a human, and the record of who approved it stays with the item.
Search Console signals
Connect Google Search Console and classic search data is joined per page, next to citation share and retrievals, on the same screen.
Agents do the loop. You approve.
Limelit is agent-first. The screens are what the agents read and write, not the other way round, and every write stops at a human before anything reaches the world.
Agents
Describe the job in a sentence and the builder proposes governed steps. Agents run on a schedule, read your own data, and stop at every write for approval.
Tables and fan-out runs
Run one agent across a hundred rows, with the credit cost estimated before it starts and evidence attached per cell.
Skills and templates
A catalog of ready workflows to copy, mirrored one for one over MCP so an agent you run in the app behaves the same when you call it from elsewhere.
MCP and your own tools
Wire Limelit into Claude, Cursor, VS Code or Windsurf and drive the whole product from your own agent. Included with every account.
Schedules and automation
Weekly pulses, prompt refreshes and gap hunts that run while you sleep, with a spend cap that stops the work before a budget is exceeded.
Outreach drafting
Pitches and replies drafted with your evidence attached, then handed to your own mailbox. Limelit never sends them for you, deliberately.
Make it yours, and keep it inside a budget.
The parts that turn a tool into something a team runs every week: your own saved views, your own segments, a digest that arrives without being asked, and a cap that stops the spend.
Your own dashboards
Build a saved view from the metrics you already track, name it, and give the whole team the same screen. See what you can build.
New this week, on every account.
Segments
Slice every screen by persona, region or audience. The scope follows you across Overview, Rankings, Sources and Plan rather than resetting per page.
Reports and the weekly digest
A clean audit you can hand to a client or an exec, plus a weekly email digest of what moved, with one-click unsubscribe.
Credits, spend caps and billing
Prepaid credits with 1,000 free on signup, no card. A spend cap stops automation before it runs past your budget, and auto top-up is off until you turn it on.
Unlimited seats and properties
Bring the whole team and every domain you own. There is no per-seat billing and no engine locked behind an upgrade.
Free tools, no account
Five public checks anyone can run against a domain, plus a free AI search report emailed in minutes. Open the free tools.
Connect a domain. See where AI skips you.
1,000 credits on signup, no card. Or run the free report first and see your share of voice before you sign up for anything.