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Dokko

No-code conversational AI platform for turning documents into a knowledge base.

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Dokko is a no-code conversational AI platform that turns documents into an actionable knowledge base. The official site presents it as a way to convert PDFs, Word files, and other resources into a chatbot experience that can answer questions, surface insights, and streamline communication for teams and customers.

The product is positioned around easy deployment and practical knowledge sharing. Dokko emphasizes quick setup, structured document ingestion, and use cases that range from customer support to onboarding and research. That makes it a strong fit for organizations that have information scattered across files and want a conversational layer on top.

Key Features

  • Upload PDFs, Word files, and other resources into a datastore.
  • Build and deploy chatbots without programming skills.
  • Connect with platforms such as GitHub and AWS S3.
  • Support for public or private access depending on the plan.
  • Pricing pages that show a 7-day trial and monthly plans.
  • Useful source traceability and knowledge-sharing positioning.

Use Cases

  • Customer support teams can answer common questions from internal documents.
  • Onboarding teams can surface policies, playbooks, and training docs quickly.
  • Research teams can centralize notes and get context-aware answers from large document sets.
  • Legal and IT teams can create a more searchable front end for recurring questions.

Pricing

The pricing page shows monthly plans, a trial, and access levels that vary by use case. That gives Dokko a clear path from small team experimentation to more public-facing knowledge sharing.

Why It Matters

Dokko works best when an organization already has useful content but lacks a simple way to expose it through search or chat. In that scenario, the platform becomes a bridge between static documents and the people who need answers quickly. That makes it practical for teams that already have the information, but need a more accessible front end so the knowledge actually gets used. It is a straightforward fit for knowledge bases that have outgrown manual search. It also works well when different teams need the same answers but do not want to keep repeating the same explanations, because the conversational layer turns existing files into something easier to ask and reuse. That can lower the overhead of support and onboarding because repeat answers live in one place instead of being copied across docs, tickets, and chat threads. That kind of reuse makes the platform a better fit for growing teams that need reliable answers without duplicating the same content in several places.

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