Estudos de Caso
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 de analise de chamadas em tempo real e coaching de vendas com IA
Implementamos uma camada de analise por IA integrada a telefonia corporativa do cliente. Cada chamada e processada logo apos o encerramento, dando aos gestores feedback objetivo quase imediato e cobertura de QA para 100% das interacoes. Mantemos as métricas principais: 5, 100.
Sistema automatizado de estimativas de construcao e compras inteligentes
Criamos uma plataforma ponta a ponta que automatiza estimativas de obra, identifica fornecedores ideais e monitora precos de mercado em tempo real. A equipe trocou planilhas estaticas por modelagem dinamica de custos.
Content Orchestrator: ecossistema unificado de marketing para servicos de idiomas
Desenvolvemos um ecossistema de marketing inteligente para um grupo de servicos de idiomas. Gemini API, NotebookLM e n8n orquestram pesquisa, geracao, revisao e distribuicao de conteudo para varias marcas.
Auditoria juridica e tecnica de compliance com IA para projetos de construcao
Criamos um motor automatizado que verifica contratos de construcao e termos de referencia contra leis, normas locais e codigos de obra. A IA sinaliza clausulas de risco e lacunas tecnicas antes que virem custo.
Sistema automatizado de recrutamento em alto volume e alocacao rapida
Engenhamos um ecossistema de recrutamento para agencia de mao de obra. Ele agrega candidatos de varias fontes, usa IA para cruzar habilidades e localizacao, e automatiza a disponibilidade para turnos urgentes.
Sistema de aprendizagem adaptativa e auditoria de performance com IA
Implementamos um motor inteligente de auditoria para uma escola online privada. O sistema analisa progresso em tempo real e adapta a trilha de aprendizagem sem violar curriculo e prazos oficiais.
Plataforma rapida de onboarding e treinamento de compliance com IA
Desenvolvemos um ecossistema de onboarding com RAG para transformar manuais estaticos em mentoria interativa. Novos colaboradores encontram respostas contextualizadas e treinam compliance em cenarios reais. Mantemos as métricas principais: 60.
Motor automatizado de conteudo para marketplace global e inteligencia competitiva
Criamos um pipeline de automacao para varejista de alto volume. Ele processa imagens de produtos em lote, gera descricoes localizadas otimizadas para SEO e monitora precos de concorrentes. Mantemos as métricas principais: 10x.
Bot Messenger automatizado para gestao de contratados
Implementamos um bot centralizado no Messenger para disparo em massa a contratados e rastreamento de respostas. O cliente deixou de coordenar ofertas manualmente por mensagens soltas.
Sistema de geracao de propostas e compliance com IA
Automatizamos a preparacao de propostas comerciais para projetos industriais. Entradas tecnicas brutas viram documentos PDF/DOCX estruturados, com verificacoes de compliance e formato de marca. Mantemos as métricas principais: 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 de analise de chamadas em tempo real e coaching de vendas com IA | vendas e atendimento ao cliente | Aderencia ao script e velocidade do feedback |
| Sistema automatizado de estimativas de construcao e compras inteligentes | tecnologia para construcao | Reducao de custos de compras e velocidade de estimativa |
| Content Orchestrator: ecossistema unificado de marketing para servicos de idiomas | EdTech, linguistica e marketing de conteudo | Eficiencia de producao de conteudo e consistencia de marca |
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.