We help FinTech teams get cited and recommended by AI answer engines. AI search is not a lighter version of SEO.
The difference is where the data lives.
AI search is not a lighter version of SEO. Search is turning into a brand channel, where the winner is whoever the model trusts enough to name. That trust is earned off your own website, in the sources AI actually reads, and it compounds for whoever moves first.
The measurement layer runs inside your environment. Platforms get consented, hashed conversions and model scores — never the underlying records. We audit the signal you are actually collecting, harmonize it into a warehouse-native single customer view, engineer the server-side and identity layer on top, then activate it: hashed conversions to Meta and Google via CAPI, and model scores as audiences.
Know exactly how AI engines answer your buyers, tracked straight to revenue. We run the real prompts your buyers use through ChatGPT, Perplexity, Gemini, and Google AI Overviews to baseline citation rate, share of voice, and sentiment accuracy. Ongoing reports track those metrics plus LLM referral conversions, tied to revenue, with a clear read on what changed and why.
We shape content so models quote you first. We restructure content the way models read it: definition-first sentences, self-contained sections, and dense verifiable facts. AI cites specific passages rather than whole pages, so we optimize at the passage level, the exact unit a model can lift and attribute without guessing.
One foundation that pays into Google rankings and AI answers. Models reason about entities, so we make it unambiguous who you are and what you sell: schema, structured data, clean internal linking, and open crawl access for the AI search crawlers. The same technical SEO and topical authority work lifts your Google rankings and feeds the models.
Most of the win is earned off your own domain. AI trusts credible sources, so we build presence where the models look: earned press, authoritative review platforms, community discussion, and the third-party rankings engines quote back verbatim. Every placement is structured so a model can extract and attribute it cleanly.
We lead with architecture here rather than a logo. Our named public cases sit in adjacent high-consideration B2B — the transferable part is the measurement layer, and our Segment Select, Google and Meta partner status is the signal of data maturity that matters in this vertical.
We map the prompts your buyers actually use across the funnel, then test them against every major AI engine to benchmark your citation rate and share of voice. In parallel we audit your content, entities, and technical setup for what is blocking retrieval. You leave this phase with a scored baseline and a ranked list of where the fastest wins are.
We clear the technical blockers first: schema, structured data, crawl access for AI bots, and clean internal linking so models can parse who you are. This is the SEO and entity groundwork everything else stands on. It also lifts your traditional rankings while the AI work compounds.
We build and rewrite the pages, answers, and FAQs that target your highest-value prompts, structured passage by passage for retrieval and citation. Where a topic needs real expertise, a human writes it; where scale helps, we use AI with governance and QA so nothing off-brand ships. Every piece is written to be quoted and attributed.
We earn the third-party signals models weigh most: press, reviews, community presence, and inclusion in the third-party rankings AI quotes back. This is the supply chain for AI citations, and it is where durable advantage is built. Placements are structured for both machine extraction and human readers.
We track citation rate, share of voice, sentiment, and LLM referral conversions, and feed what we learn back into the next cycle. AI search is an always-on program, so we run it on a steady deploy-and-measure rhythm. As your authority builds, the results compound and your lead becomes harder for competitors to close.
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