For Teams that value precision & results

Mathematically engineered credibility for the AI era.

Where AI meets authenticity. Citations that LLM models actually crawl, read, and trust.

We engineer editorial placements and authentic contributions that pass both human scrutiny and AI validation—ensuring your citations appear where models actually look.

AI‑crawlable by design

Authentic & natural

Measured outcomes

For Teams that value precision & results

Mathematically engineered credibility for the AI era.

Where AI meets authenticity. Citations that LLM models actually crawl, read, and trust.

We engineer editorial placements and authentic contributions that pass both human scrutiny and AI validation—ensuring your citations appear where models actually look.

AI-crawlable by design

Authentic & natural

Measured results

Trusted by teams that value precision and steady results

Focused for modern AI platforms

Signals structured for how contemporary models read and recall the web.

New

Launch your campaign in minutes

Meet the absmath App — a streamlined, self‑service experience to scope, order, and track citation engineering work. Transparent timelines, clear deliverables, and live status updates.

Guided ordering for the right citation type
Live status: processing, placed, validated
Clean delivery reports with key metrics

Core Values

Three pillars that define our approach to AI-era credibility

AI crawlable by design

Placements selected from pages with clean access, context depth, and entity fit. Easier to discover. Simpler to encode.

Natural and handcrafted

No marketplaces or spam. Editorial mentions, careful niche edits, and thoughtful forum conversations that read like they belong.

Measured, not guessed

Crawl and index signals verified. Ongoing observation for content change and link decay. Credibility maintained over time.

How it works

Discover

Mapping of brand entities, topics, and credible nodes across editorial hubs, MediaPR, and communities.

Model

Scoring of options by context depth, entity proximity, and likelihood of recall by AI systems.

Place

Earning of placements through editorial articles, niche edits within strong pages, and forum posting on Quora and Reddit with genuine value.

Validate

Confirmation of crawl and index status. Tracking of stability. Refresh or replacement when required.

Measured outcomes that matter

We track what actually moves the needle. Every citation is monitored for crawlability, context strength, and long-term stability.

+37%

pages with verified crawlable citations

+22%

inclusion in consensus and FAQ-style nodes

−18%

link decay within 90 days

Figures shown are examples from recent campaigns. Outcomes vary by site health, topics, and competition.

Our Services

Specialized solutions for AI-era credibility and visibility

Learn more

AI Citation Engineering

Handcrafted mentions across editorial articles, expert guides, and evergreen content. Selective niche edits where surrounding context supports the message. Forum posting on Quora and Reddit that reads like a genuine contribution.

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CrawlCred™ Audit

Clear reporting that separates AI-visible links from noise. Scoring across crawl access, context depth, entity alignment, stability, and duplication risk. Action plan ranked by impact.

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Transformer Visibility Boost

Campaign planning to increase inclusion odds in AI Overviews and LLM answers. Targeting of consensus nodes, FAQs, curated lists, and MediaPR opportunities that tend to surface.

Why absmath

Research-led practice focused on how models encode the web. Human language paired with engineered structure. Everything measured.

Credibility, engineered

Citations selected for clean crawl paths, strong context, and stable surfaces that models revisit.

Hacks

100%

Policy‑aligned

Measured

Outcomes

Measurement‑first

Crawl and index deltas, not vibes
Entity proximity & context scoring
Drift monitoring & replacement

Human + Machine

Editorial‑first language
Schema & surface‑form consistency
Answer‑engine‑friendly structure

Latest from the blog

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Sep 12, 2025

AI‑crawlable citations: from first principles to field practice

Placing references that modern answer engines can fetch, interpret, and resurface—without direct address or second‑person phrasing. Summary “AI‑crawlable citations” are references placed on web pages—owned or third‑party—that answer engines (search features, AI Overviews, conversational systems with browsing) can easily fetch, understand, store, and reuse as evidence. A simple model keeps work consistent: Access → Context […]

FAQ

Not part of the offering. Focus on authentic editorial mentions, selective niche edits, and forum posting on Quora and Reddit. Every placement reviewed for crawlability and persistence.

Credibility, calculated

Response within one to two business days.