Faisal Khan

AI Automation

  • Automate repetitive workflows with AI agents and scripts
  • Connect tools via APIs, webhooks, and scheduled jobs
  • Free up hours by removing manual, repeatable tasks
What this covers

Automating tasks that currently require a person to manually check, decide, and act — systems that can take the action itself, not just flag it.

Tech stack

Python, LangChain, Hugging Face, the OpenAI API, and agentic AI frameworks.

Real examples

Workflow automation drawn from actual project history — connecting tools and removing repetitive manual steps.

Process

Process audit (what's actually being done manually today), automation design, build, monitoring and handoff.

The real difference

This page is about automating existing processes. AI Full-Stack Development is about building new AI-native products from the ground up.

Real project
The ERP

One of the systems I built for an oil company is a good example of what "full stack with AI" actually looks like in practice, not just as a phrase on a services page. It started as a custom ERP covering every operation an oil company actually runs on — inventory, orders, procurement, workflow, internal notifications — and grew from there into a full automation layer sitting on top of that data.

Ecommerce + workflow

The ecommerce store sits on top of the same ERP rather than next to it, so an order placed on the storefront lands directly in the ERP's order queue instead of needing someone to re-enter it. From there, the workflow system takes over automatically — order confirmations, internal approval steps, and stock-level checks all fire without anyone touching the order by hand, and the email system sends the right notification to the right person at each step, customer or internal team, instead of someone drafting and sending it manually.

The AI chatbot

The AI piece is an internal chatbot layered on the ERP's real data — someone on the team can ask it what's low on stock, how many units of a product are currently in or out, or what needs reordering, and get a real answer pulled straight from the actual inventory numbers instead of digging through a dashboard or asking around. Between the automated workflow, the automated emails, and the chatbot answering questions on demand, most of what used to be someone manually checking, deciding, and following up now happens on its own.

FAQ

Common questions

What kinds of tasks are realistic to automate with AI right now?

Repetitive decision-and-action tasks — the kind that currently require someone to check, decide, and act manually.

Does this replace employees, or take repetitive work off their plate?

It takes repetitive work off their plate, freeing time for higher-value tasks.

What tools/platforms do you typically connect (CRM, email, spreadsheets, etc.)?

CRMs, email, spreadsheets, and most tools with an API or webhook support.

How do you handle errors or edge cases the AI can't confidently resolve?

Edge cases get routed to a human review step rather than the system guessing.

Is this a one-time build, or does it need ongoing monitoring?

Ongoing monitoring is recommended and available after the initial build.

Pricing

Best plan offer

Basic

$200+/ project

Delivery: 2-3 days

  • Full-stack website, up to 5 pages
  • React/Next.js + Node.js + SQL/MongoDB
  • Database integration + API development
  • Fully responsive design
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Best value

Standard

$350+/ project

Delivery: 5-10 days

  • Full-stack website, 5-7 pages
  • React/Next.js + Node.js + SQL/MongoDB
  • Authentication system (JWT/Auth.js)
  • AI features integrated (chat, search, or content)
  • Custom UI components
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Premium

$1000+/ project

Delivery: 15-30 days

  • AI automation / agentic system, built to spec
  • Custom agent workflows (LLM-driven, tool-using)
  • Integrations with your existing tools/APIs
  • Task/process automation to replace manual work
  • Admin dashboard + monitoring
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Interested in working with me?

Let's connect and talk about your project.

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