--- title: "Enterprise AI Case Studies: How to Read Them, Plus 6 We Can Stand Behind" date: 2026-05-04T02:32:00.000Z author: Milan Tahliani url: https://truehorizon.ai/news/enterprise-ai-case-study description: "Six enterprise AI case studies that shipped to production with hard numbers, plus the 5-question framework for evaluating any AI consultancy's case studies before you sign. " --- # Enterprise AI Case Studies: How to Read Them, Plus 6 We Can Stand Behind > Six enterprise AI case studies that shipped to production with hard numbers, plus the 5-question framework for evaluating any AI consultancy's case studies before you sign. _True Horizon has published six enterprise AI case studies. All six shipped to production with hard numbers you can verify on a reference call. This page walks through how to read them, and how to evaluate any AI consultancy's case studies before you sign a contract._ ## Key Insights - Most "case study" pages list logos. The good ones tell you what was built, what broke, and what the verifiable ROI actually was. - There are five questions every enterprise buyer should ask before trusting an AI consultancy's case studies. - All six True Horizon case studies shipped to production, with client sign-off and numbers we can defend on a reference call. - The hard numbers behind the portfolio are specific and falsifiable. Inbound call answer rate from 40% to 100% at Topgolf. Approximately 230,000 man-hours reclaimed across 8 departments at Avalara. 250+ finance hours per month and 99.9% extraction accuracy at Iyuno. Decision time from weeks to seconds at Pierpont Holdings. - Case studies tell you what's been shipped. The AI Readiness Assessment is the right next step if you want to see what shipping at your organization would actually look like. ## Why most enterprise AI case studies fail the sniff test Open any Big Four firm's AI case study page and count the logos. Accenture, Deloitte, BCG, EY all run the same template: hundreds of logos, half-paragraph write-ups, a cascade of "we helped a Fortune 500 company realize significant value through AI-powered transformation." Pages like that are built to close deals that were already 70% closed before the prospect landed. They don't tell you anything useful about what was shipped or whether any of it is still running. The production rate makes it worse. Per MIT NANDA's [_The GenAI Divide: State of AI in Business 2025_](https://nanda.media.mit.edu/), [95% of enterprise generative AI pilots fail to deliver measurable P&L impact](https://nanda.media.mit.edu/), which means the vast majority of "case studies" you'll read describe pilots that were alive when the press release went out and quietly dead by the next fiscal year. Stanford HAI's [_2025 AI Index Report_](https://hai.stanford.edu/ai-index/2025-ai-index-report) documents the same pattern at the industry level: enterprise adoption of generative AI surged through 2024-2025, but the gap between pilot announcements and production deployments widened, not narrowed. > "You can usually tell within thirty seconds whether a case study describes a system that's still running. The ones that aren't will use words like 'unlocked' or 'transformed.' The ones that are will tell you exactly how many users it serves today, on which infrastructure, and who's on call when it breaks." > — Milan Tahliani, Founder & CEO at True Horizon AI The real question for an enterprise buyer isn't which consultancy has the most logos. It's which consultancy has shipped AI systems that stayed shipped, and can prove it on a reference call. ## How to read enterprise AI case studies Run any case study you read through these five questions before trusting it. The same five questions apply to True Horizon's case studies and to everyone else's. **1. Did it actually ship to production?** "Shipped March 2024. Serves 400 daily users. Runs on GCP, 99.9% uptime SLA." Names who runs the system today, how it's monitored, what breaks. "Successfully demonstrated the potential of AI." "Significant productivity gains across the pilot cohort." Almost certainly describes a system that no longer exists. **2. How long ago did it ship?** Deployment is six months to three years old, and the firm can walk through how the system has evolved since launch. 2023 deployment read in 2026 with no update story. Models, infrastructure, and problem space have all moved since. **3. What are the hard numbers?** "Reduced invoice processing from 3 days to 6 minutes." "Reclaimed 250 finance hours per month." "99.9% extraction accuracy across 1.2 million documents." Specific enough to be falsifiable on a reference call. "Significant time savings." "Meaningful cost reduction." "Improved customer experience." Could describe any company in any industry. **4. What didn't work?** Names the moments something broke (hallucination, integration at scale, a governance review that killed a feature) and explains how the team got through it. Only tells the wins. The failures are where the actual learning lives, and a case study that hides them is lying by omission. **5. Can you talk to the client?** Firm arranges reference calls with qualified prospects, with proper scheduling and NDAs. Client named by permission. All case studies anonymized to "Fortune 500 financial services company." No reference call available. The case study isn't structured for verification on purpose. A case study that passes all five is rare. A consultancy that publishes case studies passing all five for every named client is rarer still. ## The six case studies Each of the six below is a production AI deployment that shipped, stayed shipped, and produced verifiable value for the client. The summaries here are short. Click through for the full story. ### Iyuno: invoice automation with 99.9% accuracy A global localization services provider processing thousands of finance documents per month across multiple currencies and languages. The finance team was losing hundreds of hours to manual data entry and routing. True Horizon built a voice agent architecture that ingests invoices, extracts structured data, validates against vendor records, and routes for approval. The system runs in production today, serving Iyuno's global finance operation. **Outcome:** 250+ finance hours reclaimed per month. 99.9% extraction accuracy across all invoice types. Processing time cut from days to minutes. [Read the full Iyuno case study →](https://www.truehorizon.ai/customers/automate-invoice-processing-ai) ### Avalara: AI deployed across 8 departments, ~230,000 hours reclaimed Avalara is the global leader in tax compliance software. They were evaluating how to layer AI-enabled workflows into their existing enterprise stack without disrupting compliance operations that customers depend on. True Horizon built and delivered an integration architecture that let AI-driven enhancements sit alongside the existing systems without introducing new failure modes into compliance-critical data flows. **Outcome:** AI initiatives deployed across 8 departments in under 6 months. Approximately 230,000 man-hours reclaimed. [Read the full Avalara case study →](https://www.truehorizon.ai/customers/avalara) ### Topgolf: inbound call answer rate from 40% to 100% Topgolf needed a consistent, reliable customer-facing voice interface that could handle high inbound call volume across dozens of locations. Off-the-shelf solutions either broke at scale or produced experiences that hurt the brand. True Horizon designed and deployed an AI voice receptionist purpose-built for Topgolf's operational profile. It handles reservations, inquiries, and routing, at the volume and voice quality the brand requires. **Outcome:** Inbound call answer rate increased from 40% to 100% across multi-venue operations. [Read the full Topgolf case study →](https://www.truehorizon.ai/customers/topgolf) ### Augustine Institute: enterprise AI for a mission-driven organization Augustine Institute is a Catholic education and media organization with content governance requirements that don't bend. They needed AI capabilities aligned with those standards and their specific audience. True Horizon built systems tuned to the organization's editorial standards and audience profile. **Outcome:** Production AI deployment aligned with mission-critical content governance. [Read the full Augustine Institute case study →](https://www.truehorizon.ai/customers/augustine-institute) ### DKF Recruitment: AI in high-trust talent workflows DKF operates in a category where AI-assisted workflows have to enhance, not replace, the high-trust human decisions at the core of the business. The challenge was integrating AI intelligence into a workflow where candidate trust and recruiter judgment are the product. True Horizon delivered AI systems that support recruiter judgment instead of trying to automate it away, preserving the trust relationships DKF's business depends on. **Outcome:** Recruiter-assistive AI deployed in production, supporting judgment rather than replacing it. [Read the full DKF Recruitment case study →](https://www.truehorizon.ai/customers/dkf-recruitment) ### Pierpont Holdings: time-to-decision from weeks to seconds Pierpont Holdings needed AI capabilities to support operations across their investment and holdings portfolio, where data governance, access control, and reliability are non-negotiable. True Horizon built systems that meet enterprise-grade governance requirements and deliver operational leverage across the portfolio at the same time. **Outcome:** Time-to-decision on multi-million-dollar, data-backed operational decisions reduced from weeks to seconds. [Read the full Pierpont Holdings case study →](https://www.truehorizon.ai/customers/pierpont-holdings) ## What these six have in common The six span localization, tax compliance, hospitality, mission-driven media, recruitment, and capital operations. Wildly different industries on the surface. The pattern is underneath. Every one of these engagements was with an organization that couldn't afford to get AI wrong. Iyuno's finance team operates under audit scrutiny across jurisdictions. Avalara can't introduce new failure modes into customer tax filings. Topgolf's customer-facing voice operations are a brand asset, not a cost center. Augustine Institute's editorial standards are non-negotiable to the mission. At DKF Recruitment, the trust relationships between candidates and recruiters are the entire product. At Pierpont Holdings, data governance and access control sit at investment-grade requirements. That's the through line. True Horizon is the enterprise AI partner for organizations that can't afford to fail. The case studies don't reflect industries we specialize in. They reflect the buyer who reaches out in the first place: the buyer whose AI project has to work, because something important breaks if it doesn't. > "We publish six case studies instead of sixty because the sixty-case-study page is selling. The six is showing. Enterprise buyers can tell the difference, and they pay more for it." > — Milan Tahliani, Founder & CEO at True Horizon AI ## What to do next If you've read through the six and want to see what a True Horizon engagement would look like for your organization, the AI Readiness Assessment is the right starting point. It takes about 10 minutes and scores your organization across five dimensions: strategic alignment, data readiness, technical capabilities, organizational readiness, and governance maturity. At the end you get a scored readiness report plus a preliminary view of what an AI roadmap for your organization could look like. [Start the AI Readiness Assessment →](https://www.truehorizon.ai/assessment) If you'd rather have a direct conversation first, [book a discovery call](https://www.truehorizon.ai/contact). We'll walk through the case studies, your specific context, and whether we're the right partner for what you're trying to build. ## FAQ ### What is an enterprise AI case study? An enterprise AI case study is a documented record of an AI system built for and deployed at a specific enterprise client. It should describe the problem solved, the architecture used, and the measurable outcomes. Strong case studies describe what shipped to production, not just what was piloted. ### How do I evaluate an AI consultancy's case studies? Ask five questions. Did it ship to production, or stop at pilot? How recent is the deployment? Are the numbers specific and verifiable? Does the case study include what didn't work? Can you talk to the client directly? A case study that can't answer those is more marketing than proof. ### What is the difference between a pilot and a production AI deployment? A pilot is a limited proof of concept, usually running on sample data against a narrow use case. A production deployment is an AI system embedded in day-to-day operations with real data, real users, and real accountability. Roughly 95% of enterprise generative AI pilots fail to deliver measurable P&L impact ([MIT NANDA,](https://nanda.media.mit.edu/) [_The GenAI Divide: State of AI in Business 2025_](https://nanda.media.mit.edu/)), which is why production evidence is what actually matters. ### How do I know if a case study's numbers are real? Verifiable case studies use specific figures like "250+ hours saved monthly" instead of "significant time savings." They name the client by permission, reference a time period, and offer reference calls with qualified prospects. Vague percentages and default anonymization are signals to slow down before signing anything. ### What do True Horizon's case studies have in common? All six shipped to production, have client sign-off, and include verifiable numbers. They span voice agents, invoice automation, integration ROI, AI receptionist work, and governance-sensitive deployments across finance, hospitality, education, recruitment, and investment. The through line is the client profile: organizations where the AI project had to work. ## Related reading - [Why 90% of AI Projects Fail: It's Your Architecture, Not Your Model](https://www.truehorizon.ai/news/why-ai-projects-fail-architecture-not-models) - [The Real Cost of Waiting on AI Implementation](https://www.truehorizon.ai/news/the-real-cost-of-waiting-on-ai-implementation) - [Introducing the Enterprise AI Readiness Assessment](https://www.truehorizon.ai/news/introducing-the-enterprise-ai-readiness-assessment) _True Horizon is the enterprise AI partner for organizations that can't afford to fail. Strategy, implementation, and managed AI services delivered to production._ [_Start the AI Readiness Assessment_](https://www.truehorizon.ai/assessment) _or_ _[book a discovery call](https://www.truehorizon.ai/contact)._ Source: https://truehorizon.ai/news/enterprise-ai-case-study