Vinci AI

Vinci AI

$1,000 in credits (higher allocations depending on revenue)

Worth up to $10,000 Visit website

Vinci AI replaces the ticket queue with resolution. Instead of routing a customer through a bot and then a human, it runs multiple retrievals against your connected knowledge, answers when the evidence is strong, takes the action the customer asked for, and closes the conversation. When the evidence is thin, it escalates instead of guessing.

The escalation is where most teams feel the difference. A human agent receives the intent, the conversation history, the fixes already attempted, the source links and a drafted reply. The customer never repeats themselves, and the agent starts solving instead of reading.

Vinci AI's second job is keeping itself accurate. It retrains on every resolved ticket and connects to your engineering workflow through MCP: your coding agent passes what shipped — merged code, closed issues, updated specs — and Vinci AI drafts the support article for your team to approve. Support docs update from shipping context, not from the third customer who complains.

It installs either way round. Run it as the AI layer on top of Zendesk, Intercom or Freshdesk and keep your current stack intact, or run support entirely on Vinci AI's native ticketing platform. Either way, setup takes minutes rather than an implementation project.

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Features

  • End-to-end ticket resolution

    Vinci AI runs multiple retrievals per question and answers only when the evidence clears its threshold. It closes conversations instead of deflecting them, so your resolution rate reflects problems solved rather than problems avoided.

  • Context-complete escalation

    When a human should step in, Vinci AI hands over intent, history, attempted fixes, source links and a drafted reply. Agents pick up mid-problem instead of restarting the conversation, and customers never repeat themselves.

  • Self-improving knowledge base

    Vinci AI drafts its own documentation updates from every teaching signal it gets: what your team ships (merged code, closed issues and updated specs, passed over MCP from your coding agent), the corrections your operators make, the conflicts and duplicates it finds across existing articles, and the gaps it hits when a question has no good answer. Nothing goes live until an authorised reviewer approves it, so the knowledge base keeps pace with your release cycle without anyone owning a documentation backlog.

  • Native ticketing platform

    Vinci AI is not only an add-on. It includes a full ticketing platform with inbox, routing, macros and reporting, so startups can run support entirely on Vinci AI instead of paying for a separate helpdesk underneath it.

  • Per-product knowledge scoping

    Multi-product and multi-brand businesses get separate knowledge silos with brand-aware routing. A question about one product never gets answered from another product's documentation.

  • Continuous retraining

    Every resolved ticket feeds back into the agent, and confidence is surfaced per response. Accuracy holds six months in, instead of quietly sliding while the dashboard still looks healthy.

  • Actions, not just answers

    Vinci AI changes billing details, pays invoices, generates exports and completes the tasks customers actually asked for, with confirmation steps where they matter. Customers get the outcome rather than instructions for reaching it themselves.

  • Support-to-engineering ticketing

    When a customer reports a bug or requests a feature, Vinci AI gathers context, checks existing knowledge, creates the internal ticket and routes it to the right team. Support, product and engineering stay aligned without copy-paste work.

Pricing

  • AI resolutions

    $0.59 per completed resolution

    Charged only when Vinci AI closes the conversation without a human

  • Seats

    $29 per user per month

    • Full inbox
    • AI copilot
    • Ticketing access

Pros and cons

Pros

  • Resolves end to end: The agent closes conversations rather than routing them to a queue
  • Live in five minutes: No migration, no implementation project, no professional services fee
  • Knowledge that maintains itself: MCP turns shipped code into drafted support docs
  • Predictable unit economics: $0.59 per resolution, so the bill scales with value rather than against it

Cons

  • Younger native ticketing: Teams with heavily customised legacy helpdesk workflows may prefer to start with Vinci AI as the AI layer
  • Voice is not live yet: Web chat, email, WhatsApp, Telegram and Slack today, voice coming soon