Yes. A significant portion of our work is structured as partnerships with PR, public affairs, and investor relations firms. Many leading agencies refer clients to Five Blocks for specialized digital reputation work that falls outside their core competencies. We are experienced at operating as a white-label partner or as a named specialist alongside an agency team.

Pre-IPO engagements have a defined timeline working backward from the expected pricing date, and the work front-loads in the six to twelve months before the offering becomes public. The structural deliverables: a complete Wikipedia article for the company and for the CEO, CFO, and other named executives where notability supports them, conducted under disclosed COI through standard Talk-page processes; Knowledge Panel claimed and populated through Wikidata and verified-source paths; comprehensive executive infrastructure with Person schema, sameAs links, refreshed bios; Wikidata entry for the company with full property coverage and accurate relationships to subsidiaries, products, and key people; AIQ™ monitoring baselines so the offering window can be tracked against pre-announcement state; refreshed corporate site content optimized for the offering narrative and for retrieval by analyst-facing AI engines. The work continues through the offering window and into the post-IPO period as the company adjusts to public-company reputation expectations.

The category distinction matters because reputation work depends substantially on infrastructure that a boutique cannot replicate. Proprietary technology at scale: IMPACT™ tracks 100M+ daily data points across 50,000+ keywords in 23 languages and 69 countries; AIQ™ polls eight AI engines across thousands of prompts; WikiAlerts™ monitors millions of Wikipedia articles in real time; GeoSearch enables location-specific SERP capture in any of hundreds of cities. A boutique cannot build or sustain that. Deep Wikipedia expertise requires years of work under disclosed COI rules and a track record with the editor community that takes a sustained presence to develop. AI engine source attribution requires both the tool and the analyst pattern recognition across many clients. Methodological depth comes from running hundreds of engagements across categories and observing what holds up across algorithm changes, AI engine launches, and market shifts. A boutique can produce useful tactical work; the structural layer is a different discipline.

Hedge fund and asset manager work runs across three tightly integrated layers. Firm-level entity accuracy: the firm’s Wikipedia article (where one exists), Wikidata entry, Knowledge Panel signals, and the strategic decision about Wikipedia presence for firms that have not yet been written about. Principal-level reputation: the founder and CIO each with their own structural infrastructure, because allocator and journalist research concentrates on the principals as much as the firm. Allocator and journalist AI narratives: AIQ™ topics covering the firm, the principals, and the strategy categories the firm operates in, with prompts calibrated to how institutional allocators actually research managers. The work integrates with the firm’s IR and communications functions and respects the regulatory constraints of the category (Reg D limitations on public communications by private funds, marketing rule constraints for registered advisors). Most engagements run at significant scale and are coordinated through senior account leadership.

Public-company crises have their own structural requirements driven by disclosure obligations, market sensitivity, and the scale of stakeholder attention. The rapid diagnostic in the first 24 hours: full IMPACT™ read of the SERP and SERP composition shift since the crisis broke; AIQ™ polling across the eight engines to see how each is absorbing the story and which sources are driving each engine’s framing; WikiAlerts™ on the Wikipedia article because contested coverage attracts hostile editing. Content strategy in the days that follow: authoritative content placed in credentialed outlets coordinated with the client’s PR firm, source-level correction requests where the coverage contains factual errors, Wikipedia accuracy maintenance on the supportable record. Engagements typically run weeks to months at heightened intensity, then transition into rebuilding work over the following year.

Standard communication cadence is designed to give clients confident visibility into the program without consuming meaningful client time. Weekly updates: a written summary covering what moved on the program in the previous week, what is in flight, and any pattern shifts in the monitoring data that the comms team should be aware of. Biweekly to monthly calls: strategy discussion, decisions on upcoming work, coordination with the client’s PR firm or counsel where relevant. Detailed monthly reports: written assessment of program progress against agreed KPIs, IMPACT™ and AIQ™ data summaries with full underlying data available on request, recommendations for the upcoming period. Ad hoc alerts during active situations: same-day or same-hour communication when something meaningful shifts in search, AI, or Wikipedia layers, with assessment and recommended response. The discipline is responsiveness with restraint – clients are kept informed without being overwhelmed by reporting overhead.

Law firm partnerships are a recurring pattern with their own working dynamics. The scenarios where the partnership produces the most value: search-result management around active litigation where coverage is shaping public perception in ways the matter requires addressing; defamation response where a digital remedy is part of the relief sought; pre-litigation diligence on adversaries and witnesses; reputation rebuilding after settlement or favorable outcome. The work is conducted under the law firm’s direction and within the constraints of the underlying matter, with counsel governing what is said publicly. AIQ™ monitoring across the AI engines during litigation is now routine because the engines often retain framings even after media coverage has shifted; source-layer work corrects those framings without contradicting counsel’s public-statement strategy. Engagements are typically structured under the firm’s engagement letter as a subcontractor to maintain privilege where appropriate.

Industry breadth matters in reputation work because the structural patterns differ substantially: the AI engines weight different sources for different categories, the SERP composition for a hedge fund query differs from a consumer brand query, the Wikipedia community treats articles in regulated industries differently than articles in general business, and the stakeholder audiences each have category-specific behaviors. We have deep engagement history across financial services (banks, hedge funds, asset managers, private equity), professional services (law firms, accounting firms, consulting), regulated industries (healthcare, pharmaceutical, energy, utilities), consumer brands (retail, food and beverage, hospitality), technology (enterprise software, consumer technology, fintech), public-sector adjacent work (government affairs, public-private partnerships), nonprofits and foundations, and individual reputation across categories. The methodology – Track / Analyze / Impact – applies across all of them; the execution adapts to category-specific dynamics.

Real estate clients have a structural reputation layer that differs from most other categories because the business is geographically distributed and locally consequential. The work runs across several layers. Local search through GeoSearch monitoring of every market where the firm operates, because the Google SERP for the firm name varies substantially by city. Google Business Profile management for individual properties where it applies, including review monitoring and response. Tenant-facing AI narratives because tenant research now routinely includes AI engine queries about the landlord. Investor-facing AI narratives because institutional capital due diligence covers digital reputation. Wikipedia and Knowledge Panel presence for the firm and principals, with the firm’s portfolio and key principals each represented appropriately. AIQ™ topics for the firm name, the principals, and major properties or markets. The configuration is heavier than most categories because the layer is broader, and it is one of the more active engagement types we run.

Private equity engagements typically have three layers and the strongest programs run all three coordinated. Firm-level reputation: the GP’s own Wikipedia article, entity layer, AI narrative monitoring, and search reputation, with attention to the institutional audiences who allocate capital. Principal reputation: the founder and senior partners, each with their own structural infrastructure (Person schema, Wikipedia where notable, sameAs links, AIQ™ topics), because the firm’s reputation flows substantially through the principals. Portfolio company support: many GPs now extend Five Blocks engagements to portfolio companies as a value-add service, with the firm covering reputation infrastructure work as part of the operating partnership. The coordinated configuration is most efficient because the same methodology, technology, and account team work across all three layers, with appropriate information barriers where required.