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AI applications

Add useful AI features to your website, dashboard, or product.

Webxhives builds AI-powered features such as document search, copilots, assistants, recommendation flows, internal search, and customer support experiences.

Plan an AI featureSee all of AI and Automation
  • Onefeature, one clear user job
  • Sourcescited back to your own content
  • Testedon real questions before launch
  • Trackedusage, cost and errors

An AI application is an AI feature built into software people already use: a search box that understands questions, an assistant inside a dashboard, a tool that reads and sorts documents. Webxhives builds the feature and the guardrails around it, so answers come from your own sources, refusals and handoffs follow rules you set, and usage and cost stay visible. A demo takes a weekend. A feature your users can trust needs testing, limits and monitoring, and that is part of the build.

What we ship

Everything under one roof.

  • Copilots and Assistants

    In-product assistants that help users find information, complete tasks, and understand next steps.

  • RAG and Semantic Search

    Search over your documents, website, knowledge base, or internal files with better answers.

  • Document Intelligence

    Extract, classify, summarize, and organize content from PDFs, forms, contracts, and documents.

  • Guardrails

    Rules, source citations, refusal logic, approval points, and safe handoffs.

  • Cost and Monitoring

    Usage tracking, token control, logs, and alerts for unusual behavior.

How we build

Tested before launch, not after the complaint.

Every AI feature ships with the checks that keep it working. Those checks are part of the deliverable, not an extra.

  • Test set

    A list of real questions with the answers they should get, agreed with you.

    Trigger
    Before launch, and after any change to prompts, data or models.
    Output
    A pass or fail with the wrong answers named, fixed before release.

  • Source check

    Confirms answers come from your content and cite where they came from.

    Trigger
    When new content is added or the search setup changes.
    Output
    Answers grounded in your sources, with gaps in the content flagged.

  • Misuse check

    Tries prompt injection, off-topic requests and attempts to pull private data.

    Trigger
    Before launch and after major changes.
    Output
    A list of weak spots, fixed with rules, limits or refusals.

  • Usage alerts

    Watches usage and token spend against the limits you set.

    Trigger
    Runs continuously once the feature is live.
    Output
    An alert when usage or cost jumps, before the invoice arrives.

If a user reports a bad answer, we can look at the log behind it and fix the cause.

How we work

How the work actually runs.

  1. 01

    Pick one feature

    One user, one job, one clear way to tell if it works. Other ideas wait until this one proves itself.

  2. 02

    Prepare the data

    We gather and clean the documents, pages or records the feature will use, and agree the test questions.

  3. 03

    Build and test

    We build the feature with its guardrails, then test it against real questions and misuse attempts.

  4. 04

    Launch and monitor

    We release to a small group first, watch answers, usage and cost, then widen it.

Who we serve

Who this is for.

  • SaaS companies
  • B2B service businesses
  • Healthcare clinics
  • Ecommerce brands
  • Startups and founder-led brands

Questions buyers ask us.

  • A chatbot is a conversation window, usually on your website. An AI application is a feature built into your product or internal system, such as smart search, a copilot inside a dashboard or a tool that reads documents. Some features include a chat interface, many do not.
  • Yes, that is the usual case. We work inside your existing codebase and release process, and we tell you early if your data needs work before an AI feature can give good answers.
  • Answers are grounded in your own sources with citations, the feature refuses or hands off when it cannot find a good answer, and a test set of real questions catches wrong answers before release.
  • Whichever model answers your test questions well at a cost and speed that make sense. We keep the model choice easy to change, so you are not locked in to one provider.
  • You do. The code goes into your repositories, the feature runs in your accounts, and your documents and test set stay yours.

Further reading

Guides behind AI search and documents.

The rest of the line.

All of AI and Automation

Ready when you are

Ready to start AI applications?

A 15-minute call. We look at your goal and what already exists, then tell you what should be done first.

Book a 15-minute callSend us the goal instead