Fact Layer Setup — Starts at $999
Turn your audit into a controlled brand representation layer
Fact Layer Setup helps SaaS teams fix the pricing, positioning, comparison, FAQ, and evidence signals AI relies on most — so audit findings become repair-ready implementation, not just a report.
Best for teams that already know what is broken and are ready to fix the highest-impact AI representation issues.
Why this layer exists
Most teams do not need more explanation after an audit. They need a setup that turns identified gaps into a more controlled fact and evidence layer.
Recommendation Audit helps you understand where AI leaves you out, gets you wrong, or cites the wrong source. Fact Layer Setup is the next step — it helps you fix the pricing, positioning, comparison, FAQ, documentation, and evidence signals behind those problems.
Diagnosis shows you the problem. Fact Layer Setup helps you establish the repair-ready layer behind it.
What Fact Layer Setup actually is
Not a generic content package. Not a vague consulting retainer. Not “we will look into it.”
A controlled fact layer
Core brand facts AI needs to interpret correctly — positioning, pricing logic, use-case clarity, comparison signals, and evidence.
A high-impact repair scope
Focused on the pages and signal clusters most likely to affect how AI describes, compares, and cites your product.
A recheck-ready setup
Designed to make the next round of evaluation and monitoring meaningful by fixing the highest-impact inputs first.
This is the layer where diagnosis becomes controlled repair.
What gets fixed first
Fact Layer Setup does not try to fix everything at once. It prioritizes the signals AI is most likely to rely on.
Pricing signals
Plan structure, starting price clarity, pricing language, and outdated pricing references.
Positioning signals
How clearly your product category, use case, target user, and core differentiation are expressed.
Comparison signals
How your product is framed against alternatives, and whether comparisons reflect the right market context.
FAQ and docs signals
Whether your FAQ, documentation, and support surfaces answer the questions AI systems repeatedly infer from.
Evidence signals
Whether brand claims, product facts, and supporting sources are aligned well enough for reliable citations.
Recheck readiness
Whether repaired surfaces are clean enough to support the next round of audit or Sentinel monitoring.
Pricing and scope
Fact Layer Setup is scoped from the audit. You are not buying “more advice.” You are buying a scoped path from diagnosis to controlled repair.
Focused setups cover the most important pricing, positioning, FAQ, and evidence signals. Most setups land between $999 and $2,500 depending on page count, signal complexity, and implementation scope.
- Core fact layer setup for pricing, positioning, and product clarity
- High-impact page repair scope for FAQ, comparison, docs, and evidence
- Source and evidence cleanup for more reliable AI interpretation
- Recheck-ready implementation path for drift defense
Larger scopes (15+ pages, multi-product brands, complex comparison landscapes) are customized after the audit.
Recommendation Audit vs. Fact Layer Setup
Recommendation Audit
You pay to understand the problem clearly.
- — Deeper prompt analysis
- — Representation issues by engine
- — Gap classification
- — Priority repair roadmap
- — Recommendations for what to fix first
Fact Layer Setup
You pay to establish the repair-ready control layer.
- Scoped implementation priorities
- Fact layer structure
- High-impact signal repair scope
- Evidence and source alignment
- Recheck-ready setup
Audit tells you what is broken. Setup helps you fix what matters most.
Why Setup comes before Sentinel
Monitoring a broken representation without fixing it first is low leverage. If AI is already relying on weak pricing signals, outdated comparison context, or thin evidence surfaces, ongoing monitoring will mostly confirm the same problem more often.
Setup repairs the layer. Sentinel helps keep it from drifting back.
Best for teams that
- Have already completed a Recommendation Audit
- Already know AI representation problems are real
- Have pricing, product, FAQ, docs, or comparison surfaces worth repairing
- Want a more controlled and machine-readable representation layer
- Want to move from diagnosis to implementation
Probably not a fit if
- —You have not yet diagnosed the problem clearly
- —You mainly want more content output
- —Your site does not yet have core surfaces worth repairing
- —You are looking for passive monitoring without active repair
How the setup works
Start from the audit
We use Recommendation Audit findings to identify which signals and surfaces matter most.
Define the scope
We determine whether the priority is pricing, positioning, comparison, FAQ, docs, evidence, or a combination.
Build the repair layer
We shape the fact layer and page-level repair scope around the highest-impact gaps.
Prepare for recheck
We make sure the repaired layer is structured well enough for the next audit or Sentinel cycle.
Frequently asked questions
Do you implement fixes, or only define the scope?
Fact Layer Setup moves you from diagnosis to repair-ready implementation. Depending on scope, that can include structured guidance, collaborative planning, or more hands-on delivery support.
How is this different from Recommendation Audit?
Recommendation Audit helps you understand what is broken. Fact Layer Setup helps you establish the controlled repair layer behind those findings.
Can I skip this and go straight to Sentinel?
Most teams should not. Sentinel is much more useful after the highest-impact representation issues are already being corrected.
What affects pricing?
The biggest factors are page count, signal complexity, comparison depth, documentation scope, and how much implementation support is needed.
Do I need this if I already have strong SEO?
SEO helps your pages get discovered. Fact Layer Setup is about improving how AI interprets, compares, and cites the signals on those pages.
You already know what is broken. Now fix the signals that matter most.
Fact Layer Setup turns your audit into a scoped, repair-ready implementation layer for pricing, positioning, comparison, FAQ, and evidence signals.
Starts at $999