Case Study
What do the case studies prove?
Use the case library to compare real workflow patterns: what slowed the team down, what system was built, which people used it, and which metric changed after launch.
The closest case is not always the same industry. Start with the workflow shape: inputs, approvals, integrations, review rules, and ownership. That tells you whether your project needs a dashboard, an automation, an agent, or a smaller pilot.
Sistema AI di analisi chiamate in tempo reale e sales coaching
Abbiamo integrato un layer di analisi AI direttamente nella telefonia aziendale del cliente. Ogni chiamata viene processata subito dopo la chiusura, dando ai manager feedback oggettivo quasi immediato e copertura QA sul 100% delle interazioni. Le metriche principali restano esplicite: 5, 100.
Sistema automatizzato di stima costruzioni e procurement intelligente
Abbiamo sviluppato una piattaforma end-to-end che automatizza le stime di progetto, individua i fornitori migliori e monitora i prezzi di mercato. I fogli di calcolo statici sono stati sostituiti da un modello costi dinamico e real-time.
Content Orchestrator: ecosistema marketing unificato per servizi linguistici
Abbiamo creato un ecosistema marketing intelligente per un gruppo di servizi linguistici. Gemini API, NotebookLM e n8n orchestrano ricerca, generazione, revisione e distribuzione dei contenuti su piu brand.
Audit AI di compliance legale e tecnica per progetti di costruzione
Abbiamo creato un motore automatico che verifica contratti di costruzione e capitolati rispetto a leggi, regolamenti locali e codici tecnici. L'AI segnala clausole rischiose e gap tecnici prima che diventino costi.
Sistema automatizzato per recruiting ad alto volume e deployment rapido
Abbiamo progettato un ecosistema di recruiting per un agenzia di manodopera. Aggrega candidati da piu fonti, usa AI per abbinare competenze e posizione, e automatizza la disponibilita per turni urgenti.
Sistema AI di apprendimento adattivo e performance audit
Abbiamo implementato un motore intelligente di audit per una scuola online privata. Analizza il progresso in tempo reale e adatta il percorso di apprendimento rispettando curriculum e scadenze ufficiali.
Piattaforma AI per onboarding rapido e compliance training
Abbiamo sviluppato un ecosistema di onboarding basato su RAG che trasforma manuali statici in mentorship interattiva. I nuovi dipendenti trovano risposte contestuali e si allenano sulla compliance con scenari realistici. Le metriche principali restano esplicite: 60.
Motore automatico di contenuti per marketplace globali e competitive intelligence
Abbiamo creato una pipeline di automazione per un retailer ad alto volume. Processa immagini prodotto in batch, genera descrizioni localizzate SEO-oriented e monitora i prezzi dei competitor. Le metriche principali restano esplicite: 10x.
Bot Messenger automatico per contractor management
Abbiamo implementato un bot Messenger centralizzato per outreach massivo ai contractor e tracking delle risposte. Il cliente ha sostituito messaggi manuali sparsi con un flusso unico di disponibilita.
Sistema AI per generazione proposte e compliance
Abbiamo automatizzato la preparazione di offerte commerciali per progetti industriali. Input tecnici grezzi diventano documenti PDF/DOCX strutturati, con controlli compliance e formattazione brandizzata. Le metriche principali restano esplicite: 5 hours, 20 minutes.
Reading the cases
How should buyers compare AI implementation cases?
What does the Maak.Digital case library show?
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What does the Maak.Digital case library show?
The Maak.Digital case library shows production AI implementation patterns rather than generic AI demos. Each case connects a business bottleneck, an AI-assisted workflow, and measurable operational results so buyers can compare the type of work, the affected team, and the business outcome.
Which AI implementation results are published?
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Which AI implementation results are published?
Published examples include AI sales coaching, content orchestration, recruitment automation, document-generation workflows, and operations automation. The strongest case pages expose the client type, problem, system architecture, launch checks, primary metric, and visible update date in server-rendered HTML.
How should a buyer read these case studies?
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How should a buyer read these case studies?
A buyer should look for similarity in the workflow, not only in the industry label. The useful comparison is whether the case has the same type of input, approval process, system integration, metric, and adoption challenge as the buyer’s own process.
Why do the case studies focus on metrics?
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Why do the case studies focus on metrics?
Metrics keep the case studies honest. Results such as QA coverage, feedback latency, script adherence, content throughput, or time-to-fill make it easier to compare a case with a real operational bottleneck instead of relying on broad productivity claims.
Which results are easiest to compare?
| Case | Team | Metric |
|---|---|---|
| Sistema AI di analisi chiamate in tempo reale e sales coaching | vendite e customer service | Aderenza allo script e velocita del feedback |
| Sistema automatizzato di stima costruzioni e procurement intelligente | construction technology | Riduzione costi procurement e velocita di stima |
| Content Orchestrator: ecosistema marketing unificato per servizi linguistici | EdTech, linguistica e content marketing | Efficienza produzione contenuti e coerenza brand |
Which evidence appears in each case?
| Signal | Meaning | Why it helps |
|---|---|---|
| Business bottleneck | The case explains the manual or slow process that justified AI implementation. | Helps a buyer understand the problem in one sentence. |
| Workflow architecture | The case lists how data, model output, review rules, and existing systems connect. | Helps buyers compare implementation complexity. |
| Measured result | The case states a primary metric instead of relying on vague productivity claims. | Helps the page stay evidence-led instead of marketing-led. |
Which case should a buyer read first?
| Buyer need | Best match | Compare by |
|---|---|---|
| Sales or QA visibility | AI sales coaching and call analysis cases | Coverage, feedback latency, script adherence, and manager workflow. |
| Content or marketing throughput | Content orchestration and prompt-system cases | Publishing volume, approval cycle, reusable templates, and campaign consistency. |
| Operations or document automation | Recruitment, proposal, and document-generation cases | Time saved, error reduction, handoff quality, and system integration depth. |
How should buyers use this case library?
- -Start with the case whose workflow resembles your own bottleneck.
- -Compare the input data, approval rules, system integrations, and team ownership.
- -Check whether the published metric matches the business result you need to improve.
- -Use the architecture section to estimate whether your project is a dashboard, workflow, or agent system.
- -Treat the case as a pattern, then scope a smaller pilot before automating the entire process.
Which AI references support implementation decisions?
Implementation decisions depend on model capability, retrieval quality, privacy requirements, workflow evaluation, and the ability to connect AI output to operating systems. These references help frame the technical choices behind the case patterns.
Technical notes
What context is kept for discovery and retrieval?
Which case-study details are exposed for search and retrieval?
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Which case-study details are exposed for search and retrieval?
Each case page includes a stable URL, client type, primary metric, challenge, architecture steps, implementation checks, visible update date, FAQ answers, Article JSON-LD, and FAQPage JSON-LD.
Why keep compact tables on case pages?
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Why keep compact tables on case pages?
Tables make the business bottleneck, workflow change, rollout stage, and measured result easy to scan for people. They also keep the evidence structured enough for search systems to summarize without guessing from visuals.