Ayesha Ahmed

Ayesha Ahmed | AyeshaAppDev

AI Engineering & Integrations

Practical AI features inside your mobile apps, websites and business software — integrated through secure backends, not custom foundation-model training.

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AI integration services

I help teams add AI capabilities to products they already run or are building. Work is scoped around your users, data boundaries and chosen AI API providers. I do not train proprietary or foundation models; integrations use established third-party AI services where appropriate.

AI API integrations

Connect your app or admin panel to AI APIs with server-side calls, authentication, rate limiting and error handling agreed in scope.

LLM-powered features

In-product assistance such as guided flows, summarisation or structured responses when requirements and prompts are defined with you.

Chatbots & assistants

Lightweight support or enquiry chat experiences embedded in web or mobile surfaces, aligned with your content and escalation paths.

Workflow automation

Reduce repetitive manual steps with automation that can include AI-generated steps where it genuinely saves time.

Chatbots, RAG and document Q&A

Chatbots and assistants can answer common questions, collect enquiry details or route users to the right next step. Copy, tone and fallback behaviour are defined with you before build.

RAG-style document question answering (retrieval plus AI responses over your approved content) is available when you provide source documents, access rules and privacy requirements. Chunking, retrieval and API calls are implemented to match that scope; this is an integration service, not a claim about past client RAG launches on this portfolio.

AI in Flutter, React Native, React and Next.js

AI features need a home in your existing stack. Typical work includes:

For the app or site itself, see mobile app development and web development. For operational records and admin workflows, see business software.

Integration process

  1. Define the use case. Who uses the feature, what they should achieve, and what data may be sent to an AI provider.
  2. Choose architecture. Provider selection, server-side integration pattern, auth and environments.
  3. Implement and test. UI, backend routes and realistic scenarios including failure cases.
  4. Handover. Documentation, key management boundaries and support expectations as agreed in the project.

Related software experience

Portfolio work demonstrates full-stack integration skills that AI features build on — APIs, admin panels and multi-platform products. These case studies are not presented as AI or LLM client projects:

Helpnaw platform overview · Admin panel work · Dental clinic SaaS · Real estate website (React/Next.js)

Frequently asked questions

Do you train custom or foundation AI models?

No. Work focuses on integrating established AI APIs and services into your product.

Can AI be added to an existing app or website?

Often yes, when scope includes the necessary backend changes and UI updates for the agreed feature.

Where are API keys stored?

Typically on the server or in secure environment configuration, not in public client code — exact approach is agreed per project.

Can you work with our documents for internal Q&A?

Yes, when you define which documents are in scope, who may access answers, and how data is handled before implementation.

How is pricing handled?

Same as other services: requirements, integrations and timeline are agreed before quoting.

Based in Islamabad. Available remotely.

Based in Islamabad, serving businesses in Islamabad and Rawalpindi, across Pakistan, and remotely in the USA, UK, UAE, Canada and worldwide.

Explore development services

Mobile app development · Web development · Business software · AI engineering