Tully Rinckey AI Market Strategy Report - Immigration Lawyers

Answer Capsule

Tully Rinckey holds no measurable presence in AI-generated recommendations for immigration lawyer discovery in September 2026. The benchmark shows the firm absent from all 79 qualified observations across the six tracked AI surface families, with zero mentions, zero valid recommendations, and no rank-eligible placements. The clearest weakness is total invisibility at the recommendation stage, meaning the firm is not part of the public evidence layer AI systems draw from when buyers ask for immigration legal help. The clearest opportunity is building a foundational citation and source footprint that allows AI systems to retrieve, reference, and ultimately recommend the firm in high-intent discovery prompts.

Who This Report Is For

This report is for marketing, business development, and firm leadership teams at Tully Rinckey responsible for understanding how AI-driven discovery is shaping client acquisition in the immigration legal category. AI market discovery is increasingly becoming the first filter for buyers seeking legal representation.

Report Card

Executive Summary

Tully Rinckey does not appear anywhere in the September 2026 AI Market Discovery benchmark for immigration lawyers. The firm recorded zero mentions across all 79 qualified observations, meaning no tracked AI surface surfaced the brand in response to relevant prompts. This is not a recommendation gap; it is a total absence from the AI-visible information environment.

The benchmark tracked 19 brands across six AI surface families, including ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. Tully Rinckey holds a 0.00% raw mention presence rate, a 0.00% valid recommendation coverage rate, and no positive, neutral, or negative sentiment classifications because the firm never appeared in any response. In the competitive landscape of AI search visibility for immigration legal services, the firm is structurally invisible.

The strongest cluster in the category is the brand recommendation cluster, which captured all 79 qualified observations. This cluster covers direct requests for immigration lawyers and firms. Tully Rinckey is absent from this cluster entirely, while competitors such as Upsolve at 16.5% coverage and Fragomen at 10.1% capture the recommendation slots.

The clearest platform signal is that no single platform surfaces Tully Rinckey. The firm has no presence on ChatGPT, Copilot, Gemini, Perplexity, Google AI Mode, or Google AI Overviews. The clearest gap is not platform-specific but structural: the firm lacks the search-visible source footprint and citation architecture that AI systems appear to rely on when forming recommendations in this category.

What Tully Rinckey Is Winning

The September 2026 benchmark data does not support any evidence-backed wins for Tully Rinckey. The firm recorded no mentions, no valid recommendations, no top-three placements, and no rank-one placements across any tracked platform or prompt cluster.

The absence of negative framing is the only neutral observation available, but this reflects total invisibility rather than positive positioning. Being absent from AI responses means the firm avoids negative mentions, but it also means the firm cannot be considered, shortlisted, or recommended when buyers ask AI systems for immigration legal help.

Where Tully Rinckey Has the Clearest AI Visibility Gaps

Tully Rinckey is absent from the entire AI recommendation environment for immigration lawyers. The firm does not appear in any of the 79 qualified observations, while the category leader Upsolve holds a 39.24% raw mention presence rate and Fragomen holds a 26.58% presence rate.

The most direct comparison comes from brands that converted presence into recommendation credit. Fragomen achieved a 10.13% valid recommendation coverage rate with an 8.86% top-three rate and an 8.86% rank-one rate. John T. Orcutt and Sasser Law Firm each reached 7.59% coverage. Tully Rinckey holds none of these positions.

The firm also shows no presence on any individual platform. Competitors appear across multiple surfaces, with Fragomen earning a 62.50% valid recommendation coverage rate on ChatGPT and John T. Orcutt earning a 20.00% rate on Google AI Mode. Tully Rinckey has no platform-level presence to compare.

The gap is best understood as a missing public evidence layer. AI systems in this benchmark appear to surface brands that have search-visible pages, citations, and source footprints they can retrieve and synthesize. Tully Rinckey does not appear in the observation set at all, which suggests the firm is not part of the retrievable information environment these systems draw from.

Biggest Opportunity

The single clearest opportunity for Tully Rinckey is establishing a foundational citation and source footprint that makes the firm retrievable in high-intent brand recommendation prompts. The benchmark shows that all 79 qualified observations fell into the brand recommendation class, meaning buyers are asking AI systems to name specific immigration lawyers and firms.

Competitors that win these prompts share a common pattern: they are present in the public evidence layer with content that AI systems can retrieve, cite, and synthesize into recommendations. Tully Rinckey needs to build that layer first, before any recommendation strategy can take hold. This means developing search-visible pages, authoritative content, and citation-worthy sources that align with the specific prompts buyers use when seeking immigration legal representation.

Competitive Landscape

Questions This Section Answers

• Where does Tully Rinckey rank against competitors in AI recommendation coverage for immigration lawyers?
• Which competitors hold the strongest top-three and rank-one recommendation positions in this category?

Upsolve and Fragomen hold the strongest recommendation-stage positions in the immigration lawyer category, with a cluster of regional firms following behind. Tully Rinckey sits outside the competitive set entirely, with no presence in the September 2026 observation set.

Average recommended rank covers rank-eligible recommendations only.

The table shows Tully Rinckey at the bottom of the competitive set with no top-three placements, no rank-one placements, and no rank-eligible recommendations. Fragomen converts all of its top-three placements into first position, while Upsolve holds the highest coverage in the category but concentrates its recommendations outside the top three. Tully Rinckey does not register on any of these dimensions.

Prompt Evidence

Google AI Mode / Brand Recommendation Prompt: "immigration lawyer for spouse visa" Result: Tully Rinckey does not appear in the response, while competitors with visible source footprints capture the recommendation slots.

ChatGPT / Brand Recommendation Prompt: "Who is the largest immigration law firm in the world?" Result: Fragomen earns recommendation credit with a 62.50% valid recommendation coverage rate on this platform, while Tully Rinckey is absent.

Google AI Overviews / Brand Recommendation Prompt: "best bankruptcy attorney dallas" Result: Allmand Law and Sasser Law Firm earn top-three placements, showing that regional firms can win recommendation credit when they have a retrievable source footprint. Tully Rinckey does not appear.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific high-intent prompts where Tully Rinckey should appear and identify which competitors currently capture those recommendation slots.

Phase 2: Recommendation Readiness Plan Define the practice-area pages, service content, and firm positioning needed to make Tully Rinckey a viable candidate for AI recommendation in immigration discovery prompts.

Phase 3: Owned Answer Layer Buildout Develop authoritative owned content that answers the specific questions buyers ask AI systems, structured so the firm can be retrieved and cited.

Phase 4: Citation / Authority Layer Development Build the backlink-supported evidence layer and external citations that help AI systems verify the firm as a credible source in the immigration category.

Phase 5: Monthly AI Visibility and Recommendation Tracking Measure presence, recommendation coverage, placement, and sentiment monthly to confirm whether the new source footprint is converting into AI recommendation credit.

Why This Matters

AI-generated recommendations are becoming the first filter in legal services discovery. When a buyer asks an AI system to name an immigration lawyer, the brands that appear in that response gain consideration before any traditional marketing touchpoint occurs. Tully Rinckey is currently invisible at that decision moment.

Presence alone is not enough, as the benchmark shows with brands like DebtStoppers holding 12.66% presence but 0.00% recommendation coverage. But absence is a harder problem. The next move for Tully Rinckey is building the prompt, page, and citation layers that allow AI systems to find the firm in the first place, then converting that retrievability into recommendation credit.

Core Metrics

Sentiment Score

Questions This Section Answers

• Why does Tully Rinckey's net sentiment score of 0.00 reflect absence rather than neutral positioning?
• Why is classified sentiment required before interpreting AI visibility for the firm?

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

Tully Rinckey has a net sentiment score of 0.00 because the firm recorded zero mentions across all 79 qualified observations. This score should not be read as neutral positioning. It reflects total absence from the AI response environment.

This matters because unclassified mention counts are misleading. A firm with zero mentions and a firm with balanced positive and negative framing can both show a zero score, but they occupy completely different competitive positions. Share of voice is a diagnostic metric, not a business KPI. A positive recommendation, neutral reference, cautionary mention, and competitor-displaced mention are not equal. Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility, and for Tully Rinckey the classification is clear: the firm is not present to be measured.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Tully Rinckey's AI visibility and recommendation position in the immigration lawyers category. It is not a client implementation case study.
2. The reporting window is September 2026, with July 2026 used as the baseline reference month where trend context is available.
3. The benchmark tracked six AI surface families: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode.
4. The September 2026 run began with 586 prompt-surface observations and 392 unique questions. Of those, 300 were relevant and 286 were irrelevant.
5. The public benchmark uses 79 qualified observations as the denominator for all brand-level metrics.
6. The competitor universe includes 19 tracked brands in the immigration lawyers category.
7. All qualified observations in September 2026 fell into the brand recommendation buyer-intent class. No qualified observations were recorded for pricing and value or multi-brand comparison clusters.
8. A mention is defined as any appearance of a tracked brand in an AI response, regardless of whether the brand is recommended.
9. A valid recommendation is defined as a qualifying recommendation where the brand is actively shortlisted or recommended in the response, distinct from a neutral reference or comparison anchor.
10. The September 2026 qualified set of 79 observations is smaller than the July 2026 set of 93, which affects the sensitivity of percentage movements. Brand-level rates should be read alongside absolute counts.
11. This public benchmark does not measure market share, attributable sales, every possible AI response, organic-search ranking, social mention volume, or causality from metric movement alone.
12. Source presence in benchmark observations is evidence about the information environment. It is not automatically proof that a source caused a recommendation.

See How AI Is Recommending Your Brand

The public benchmark shows where brands stand in AI-generated recommendations, but a company-level audit shows why. For Tully Rinckey, the question is which high-intent prompts should surface the firm, which competitors currently hold those recommendation slots, and what source footprint is needed to make the firm retrievable. A company-specific AI visibility audit maps those prompt, platform, competitor, and evidence-source patterns into a prioritized visibility strategy.