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Pardeep Kaushik.

AI Integration

AI Integration for Websites and Web Apps That Need More Than a Chat Box

The most useful AI features are usually small and specific: summarising a support enquiry, drafting product descriptions from a spec sheet, answering questions from your own documents, or sorting incoming leads. I build features like these into existing websites and web apps using the OpenAI and Claude APIs, along with the unglamorous parts that make them safe to run: API keys kept on the server, usage limits, sensible fallbacks when the model is slow or wrong, and logs so you can see what it's doing. It works with WordPress, WooCommerce and Shopify sites as well as custom Next.js and Node.js applications.

AI Integration Services

Specific, dependable AI features added to the site or app you already have, with the server-side handling, limits and logging that production needs.

  • OpenAI and Claude API features added to an existing site or app
  • Answers from your own documents and data (retrieval-augmented generation)
  • AI-assisted search across products, articles or help content
  • Content tools for your team: drafts, summaries, rewrites, tagging
  • Enquiry and ticket triage: classify, route and summarise
  • Server-side key handling, rate limits and cost controls
  • Fallbacks and human review where a wrong answer would matter
  • Usage logging so you can see what the AI is actually doing

Technologies

  • OpenAI API
  • Claude API
  • Next.js
  • Node.js
  • PostgreSQL
  • Vector search
  • WordPress
  • REST APIs

Problems I solve

  • • Staff spending hours on repetitive writing or sorting
  • • Visitors who can't find answers buried in your content
  • • AI experiments that work in a demo but aren't safe to put live
  • • API keys exposed in the browser or costs nobody is watching
  • • Not sure which tasks AI is actually good enough for

Development process

  1. Step 1

    Pick the right task

    Start with one job where AI saves real time and a wrong answer is easy to catch. Agree what good output looks like before writing code.

  2. Step 2

    Build and test with your data

    Wire the model into your site or app, test it against real examples, and tune prompts, retrieval and limits until the results are dependable.

  3. Step 3

    Launch with guardrails

    Ship behind usage limits and logging, with a fallback path, then review real usage and adjust.

Why work with me

You work directly with the developer wiring AI into your site, so the model, the data it reads and the code around it are understood by one person. Based in India; working with businesses worldwide. After delivery, you own the project files and source code handed over unless otherwise agreed.

Frequently asked questions

Which AI models do you work with?

Mainly OpenAI's models and Anthropic's Claude through their APIs. The choice depends on the task, cost and how much text the feature needs to handle. Your account and API keys stay in your name.

Can AI answer questions using our own documents?

Yes. This is called retrieval-augmented generation: your documents are indexed, the most relevant passages are found for each question, and the model answers from those. It's far more reliable than asking a model to answer from memory, and it can cite where an answer came from.

Can you add AI to a WordPress or Shopify site?

Yes. The AI calls run on a server, never in the visitor's browser, so your keys stay private. For WordPress that can be a small custom plugin or an API endpoint; for Shopify, usually an app proxy or a separate service the theme talks to.

What does running an AI feature cost each month?

Model providers charge by usage, so it depends on traffic and how much text each request handles. I'll estimate it from your expected usage before building, and set limits so a busy day can't produce a surprise bill.

Will the AI ever give wrong answers?

Sometimes, and anyone who says otherwise is overselling. Good integrations reduce it by grounding answers in your data, limiting the feature to tasks it handles well, and adding human review where a mistake would matter.

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