Visibility monitoring
Continuous tracking of citation coverage, share of answer and brand representation across AI platforms, instead of periodic manual checks.
AI automation, applied to search
Build the AI search system that gets sharper over time
The goal is not more AI output. It is a connected loop that captures buyer signals, maps answer patterns, turns evidence gaps into action, then rechecks what changed.
100% REFUND GUARANTEEMiss the agreed result by the agreed date. Get every fee back.↓AI-search operating flywheel
DESIGN → VALIDATE → STANDARDIZE → AUTOMATE → REPEAT
The problem this solves
AI visibility changes faster than manual teams can track it
Semrush's 2026 AI Visibility Index found that only 9% of marketing leaders have the tools to track their brand's visibility across every relevant AI platform. Manually monitoring citation coverage, buyer-question gaps and competitor representation across multiple AI engines isn't a sustainable workload for most in-house teams.
03 / A clearer category
Automate the work. Keep the judgment.
We automate repeatable signal, research and reporting work. Positioning, evidence standards, truth claims and public-facing changes remain founder-owned because volume is not a decision.
AI content volumecitation.ly automation
AI content volumeMore output treated as the goal
citation.ly automation→Better research, evidence and decision cadence
AI content volumeUnowned agent output
citation.ly automation→Named decision gates for claims, priorities and publication
AI content volumeDisconnected tools and reports
citation.ly automation→A connected workflow from buyer question to measurement
AI content volumeAutomation used to replace expertise
citation.ly automation→Automation used to give expertise more useful coverage
Where we apply automation
Where automation supports the system — and where it doesn't
Research at scale
Automated buyer-question, competitor and cited-source discovery that becomes a prioritised action queue — not unedited output.
Measurement and reporting
Connecting visibility data to consideration and commercial indicators without manual spreadsheet work.
Protected decisions
Positioning, evidence standards, truth claims and publication approval stay with your team. The workflow can surface a pattern; it cannot decide what your brand should claim.
What the system makes tangible
Make the work easier to learn from, not just faster to produce
The workflow carries a signal through research, evidence and action so each recheck informs the next priority — not a retrospective report.
- 01
Input
Buyer questions, market evidence, site signals and representation observations enter one working system.
- 02
Decision gate
A named founder checks the evidence, claim and commercial priority before anything changes publicly.
- 03
Recheck
Visibility and citation changes feed the next research and action queue.
05 / Systems in practice
Systems compound, not funnels.
We build self-reinforcing workflows that turn buyer-question signals into source-backed action briefs, then recheck what changed across answer surfaces. Founders approve claims, priorities and public-facing changes.
06 / Proof before promises
Results that speak for themselves.
Selected results show the commercial work and evidence standard behind the systems we build.
more monthly organic clicks
3,760 → 15,378 clicks per month
more organic impressions
79,710 → 1.07M impressions per month
weekly active users built
0 → 430,000+
07 / Operator-led terms
AI-based leverage, with human-based accountability & judgement.
Dhanur Sehgal and Chandan Chaudhary lead the diagnosis, strategy and critical reviews. Before work begins, we put the result, baseline, evidence source, timeframe and shared responsibilities in writing.
- 01Operator-led diagnosis, strategy and critical review; no junior hand-off.✓
- 02An agreed starting point, evidence source and timeframe before execution begins.✓
- 03Scope and shared responsibilities written down before a result is judged.✓
08 / A good fit is specific
Ready to turn scattered SEO work into a system?
This is for teams with recurring research, content, monitoring and reporting work that would become more useful if the right data and decisions moved through one accountable workflow.
- 01A real search, content or growth operation with repeatable work to improve✓
- 02Sources of truth such as Search Console, analytics, CRM or a research process✓
- 03A team willing to name who approves evidence, claims and public-facing changes✓
- 04A need for better decision speed, not simply more published output✓
Questions before we start
Before we build, let’s be clear.
01What should be automated and what should not?+
Repeatable discovery, monitoring and reporting work can be systematised. Positioning, truth claims, strategic trade-offs and final public-facing judgment remain human decisions.
02Do we need a large data stack first?+
No. We start with the data and operating constraints you actually have, then identify the first useful loop. The point is to make the next decision better, not create infrastructure for its own sake.
03Does automation replace SEO, AEO or GEO?+
No. It is the operating layer that helps those disciplines learn and execute with more consistency. The underlying discovery, information and authority work is still essential.
04How do you keep quality under control?+
Every workflow names its inputs, evidence requirements, claim approvals and recheck measures. It can surface a pattern; it cannot decide what your brand claims or publishes.
The next useful step
Find out where automation could remove your team's bottleneck
We'll flag where manual monitoring or reporting is limiting your visibility as part of the benchmark.
Plan your first automation loopOperator-led work, a visible baseline and a defined next decision — before any engagement begins.