Caso d'uso

AI for customer support

Triage, retrieval, and draft-and-review. Your support team gets faster and more confident — your customers keep talking to humans.

Per cosa ci scelgono i team

Tre lavori che i team supporto ci affidano

  • Ticket triage

    Route, tag, prioritize. Catch the urgent stuff.

  • Internal retrieval

    Agents query the kb in plain English, with cited sources.

  • Draft-and-review reply

    AI drafts in your voice. Agent edits. Sends.

Cosa costruiamo

Cosa costruiamo per i team supporto

  • Ticket triage

    Route, tag, prioritize. Catch urgent stuff that buried itself in the queue.

  • Internal retrieval

    Agents ask plain-English questions of your knowledge base, runbooks, and product docs. Answers cite their source.

  • Draft-and-review reply assistant

    AI drafts a response in your voice. Agent reviews, edits, sends. Quality up, time down.

  • Macro / template generation

    Surfaces repeated issues. Suggests new templates. Pruning the macros library that's grown 200+ entries.

Il tempo perso, reso visibile

Parti dalle ore che perde il tuo team supporto

Troviamo dove il team perde tempo, mostriamo quanto costa e costruiamo la soluzione. Tre servizi ti portano dall'individuare i lavori all'uso del risultato da parte del team.

  • Consulenza IA

    Capire dove l'IA rende: i lavori in ordine di priorità, quanto costa oggi ciascuno e da dove partire.

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  • Implementazione IA

    Metterla al lavoro e mantenerla attiva: l'IA fa il volume, una persona controlla il risultato.

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  • Formazione IA

    Far usare lo strumento al team: formazione per ruolo legata ai flussi che costruiamo.

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Domande

Domande frequenti

We tried a customer-facing chatbot once and it went badly — how is this different?

We don't build customer-facing chatbots by default. the work points inward: triage, retrieval, draft-and-review. agents stay on the phone or in the ticket; the ai sits behind them. customers keep talking to humans.

How is this different from zendesk ai, intercom fin, or the gorgias suggestions we already pay for?

Those tools work inside their own walls — your zendesk macros, intercom articles, gorgias replies. we build retrieval across the rest: 4 years of historical tickets, the product docs, the shipping policy pdfs, the engineering runbooks.

How do you handle the agents who think this is the first step to replacing them?

We say so on day one. the framing is 'helps agents, not replaces them' — and we measure it. the kpis we move are first-response time and resolution quality on complex tickets, not headcount. training sessions with the support team are part of the build, not an afterthought.

Dicci quale lavoro richiede più tempo.

30 minuti, senza preparazione. Ti diremo con onestà se l'IA può aiutare e da dove iniziare.