Most engineer portfolios are a logo wall and a list of frameworks. That tells you nothing about whether the person can ship a system that survives real traffic, real users and a real invoice from OpenAI at the end of the month.
So this page is structured the way I would want to read it if I were the one hiring: who I am, what I build, what the engagement actually looks like, what it costs, and how to check that any of it is true.
Who is Syed Husnain Haider Bukhari?
I am an AI engineer, data scientist and full-stack Python developer, and the founder of Revolutionary Technologies LLC. I build production AI systems and the data infrastructure underneath them for companies in the United States, the United Kingdom and the United Arab Emirates.
My name is written a few different ways depending on the paperwork: Syed Husnain Haider Bukhari in full, Husnain Bukhari in most working contexts, occasionally S. H. H. Bukhari on academic-style citations. They are the same person. This site, husnainbukhari.com, is the canonical one.
I came into LLM work from the data side rather than the prompt side. Before agents were a category I was writing Python services, Airflow DAGs and statistical models, which is why my instinct on any AI brief is to ask what the data looks like before asking which model to use.
The short version, in a form you can scan:
| Field | Detail |
|---|---|
| Full name | Syed Husnain Haider Bukhari |
| Also known as | Husnain Bukhari |
| Role | AI engineer, data scientist, full-stack Python developer |
| Company | Revolutionary Technologies LLC (founder) |
| Disciplines | Applied LLM engineering, AI automation, data engineering, machine learning, web apps |
| Clients served | United States, United Kingdom, United Arab Emirates |
| Working hours | Pakistan Standard Time, UTC+5, no daylight saving |
| Core stack | Python, FastAPI, React, PostgreSQL with pgvector, Supabase, Airflow, n8n |
| Model providers | OpenAI, Anthropic Claude |
What do I actually build?
Four categories, and almost every project I take on is one of them or a combination. I do not do brand design, paid media or mobile-first consumer apps, and saying so up front saves us both a call.
The work sorts cleanly into these buckets:
- Applied LLM systems. Agents, retrieval pipelines, structured extraction and scoring. Usually OpenAI or Anthropic Claude models behind a FastAPI service, with pgvector or Supabase holding the retrieval layer.
- Conversational and voice automation. WhatsApp on Meta's Cloud API, voice flows on Twilio, and CRM-side automation inside GoHighLevel, n8n, Make or Zapier.
- Data engineering and acquisition. Distributed scraping, Airflow pipelines, warehouse modelling, and the unglamorous cleaning work that decides whether an AI feature is useful or embarrassing.
- Analytics and internal tooling. Real-time dashboards, geospatial operations views, and the internal apps that operations teams actually live in all day.
If you are scoping something in the first two buckets, my AI engineering services page covers delivery in detail, and AI automation covers the workflow and integration side.
Which portfolio projects should you look at first?
Pick the one whose shape matches your problem, not the one in your industry. Architecture transfers between industries far more reliably than domain knowledge does.
The projects I point people to most often, and the reason each one is worth your time:
| Project | What it is | What it demonstrates |
|---|---|---|
| AgentFlow | Visual no-code builder for AI agents and call flows | Modelling branching conversation logic as data rather than hardcoded prompts |
| ProLeads | Natural-language B2B lead generation | Turning a plain-English request into a structured query over messy company data |
| AgenticAI | GPT-4o CV screening platform | Structured extraction and scoring against a rubric, with auditable outputs |
| AI Walay | Multi-tenant WhatsApp Business SaaS | Tenant isolation and messaging architecture on Meta's Cloud API |
| Synthicare | AI clinical decision support built for NHS constraints | How regulatory constraints reshape architecture rather than sit on top of it |
| DaulatAI | AI financial advisor for the Pakistani market | Grounding a model in PSX and SBP data, including Shariah-compliant options |
| Web scraping platform | Distributed scraping at 100K+ jobs per day | Queueing, retry and throughput engineering under real failure rates |
| Data pipeline analytics | Airflow pipeline handling 10M+ records per day | Batch orchestration and schema discipline at volume |
| Indonesia livestock dashboard | Real-time geospatial and AI operations analytics | Streaming data and mapping for field operations teams |
Two are worth opening even if they are nothing like your brief. ProLeads is the clearest example of how I decompose a vague natural-language request into deterministic steps, and there is a full teardown of how ProLeads was built if you want the reasoning rather than the screenshots. AgentFlow is the clearest example of building a tool that other people configure without me.
Beyond the table there is AgenticAI for CV screening, TubeQueue for YouTube bulk scheduling out of Google Drive, a 24-stage lead funnel CRM for APAC awards programmes, a GoHighLevel AI calling and SMS suite, VisaMatched for UK sponsorship analytics, a YOLO-based detection API, and site generation systems that have run at 1M+ Google Sites and 3000+ Next.js sites.
"A portfolio is not proof of skill. It is proof of finishing, which is the rarer thing."
How does an engagement with me actually run?
In five stages, with a paid, scoped starting point rather than an open-ended discovery phase. The goal of the first two weeks is to make the project cancellable with something useful already in your hands.
The sequence I run on almost every build:
- 1Scoping call. Sixty minutes, free. I want the workflow as it exists today, the volume it runs at, and who breaks if it fails.
- 2Written scope and fixed quote. Deliverables, exclusions, integrations, data access needed, and a delivery window. If I cannot write it down, I do not understand it yet.
- 3Thin vertical slice first. One real path end to end on real data, not a demo on sample data. This is where most estimates get corrected, and it is cheaper to correct them in week two.
- 4Build in weekly increments. You get a working environment and a written update every week. No month-long silences followed by a reveal.
- 5Handover and optional retainer. Repository in your organisation, documented runbook, and a walkthrough. Retainer only if there is genuine ongoing work, and I will tell you when there is not.
Code lives in your GitHub organisation from the first commit, and intellectual property assigns on creation rather than on final payment. Access control prevents ownership disputes far more cheaply than contract clauses resolve them.
What does it cost to work with Syed Husnain Haider Bukhari?
It depends on shape, not on hours. I price three ways, and which one fits is usually obvious within the first call.
How each pricing shape works and when it is the right choice:
| Shape | How it works | Best when |
|---|---|---|
| Fixed-scope build | One written scope, one price, staged payments against milestones | The outcome is clear and the integrations are known |
| Monthly retainer | A fixed block of capacity each month across a backlog | Ongoing iteration, several small systems, or an evolving product |
| Paid discovery sprint | One to two weeks producing an architecture, a prototype and a real estimate | The problem is real but the solution is genuinely unclear |
One thing worth understanding before you budget: my fee is the labour line only. Model tokens from OpenAI or Anthropic, telephony minutes from Twilio, WhatsApp conversation charges under Meta's pricing, and hosting are billed to you directly at global USD list rates and do not change because the engineer is in Pakistan. Running cost scales with tokens per call multiplied by call volume, so check the current numbers on each vendor's own pricing page rather than trusting a figure in a blog post.
Where do I work from, and does the time zone matter?
I work remotely from Pakistan Standard Time, which the IANA time zone database records as UTC+5 with no daylight saving. That fixed offset matters more than people expect, because your overlap with me never shifts twice a year.
What the overlap looks like in practice:
- UAE and the Gulf: one hour apart. Effectively a shared working day, which is why Dubai and Abu Dhabi clients get near-synchronous delivery.
- United Kingdom: four to five overlapping hours depending on British Summer Time. Morning UK calls work well all year.
- United States: little to no natural overlap on a standard day. I hold early-morning slots for US clients and run everything else on written asynchronous updates.
The honest version is that asynchronous discipline matters more than overlap. Weekly written updates, a shared backlog and a working environment you can open yourself beat a daily call that neither side prepares for. If you are evaluating this trade-off seriously, the buyer's guide to working with an AI automation expert in Pakistan walks through the contracting, payment and verification questions in full.
Why hire one engineer instead of an agency or an in-house team?
Because for a first AI system, coordination cost usually exceeds capacity cost. A single engineer who scopes, builds and ships removes the translation layer between the person who understood the problem and the person writing the code.
The honest limits: I am one person, so I am wrong for a project needing four parallel workstreams, and I am wrong for a team that wants permanent institutional knowledge on payroll. If you are weighing that specific decision, the comparison against building an in-house AI team lays out where each option stops making sense.
How do you verify any of this before hiring me?
Ask for the failure story, not the success story. Anyone can narrate a project that worked; only the person who actually built it can tell you which assumption broke in week three and what they changed.
Checks I would run on myself if I were the buyer:
- Ask which parts of a named project were hardest, and listen for specifics about data quality, rate limits or model behaviour rather than generalities.
- Ask what the system costs to run per month at your expected volume, and whether the answer is broken into tokens, telephony and hosting.
- Ask for a walkthrough of a live environment rather than a slide deck.
- Ask what happens when the model returns something wrong, and expect an answer involving validation, fallbacks and logging.
- Ask for the scope document from a previous engagement with the client details removed. Scope quality predicts delivery quality better than any portfolio image.
Google's own guidance on helpful content puts first-hand experience at the centre of what makes a page trustworthy, and the same standard is a reasonable one to hold a vendor to. Every project referenced above has its own page on this site with the architecture written out.
How to hire me
Send the problem, not the solution. The most useful first message describes the workflow that is currently painful, the volume it runs at, and the deadline you are working against.
What to include so the first call is productive:
- 1The workflow as it runs today, including the manual steps and who performs them.
- 2Volume: records, conversations, calls or documents per day or month.
- 3Systems it must touch, such as your CRM, warehouse, WhatsApp number or telephony provider.
- 4Constraints that are non-negotiable, including data residency, compliance regime and budget ceiling.
- 5What success looks like in a sentence a non-technical stakeholder would accept.
If the answer to your problem is an off-the-shelf tool rather than a build, I will tell you on the first call and point you at the tool. That is the least expensive advice I give and the reason most of my work arrives by referral.
Key takeaways
- Syed Husnain Haider Bukhari is an AI engineer, data scientist and full-stack Python developer, and the founder of Revolutionary Technologies LLC.
- The work sorts into four categories: applied LLM systems, conversational and voice automation, data engineering, and analytics tooling.
- Engagements start with a written fixed scope and a thin end-to-end slice on real data, not an open-ended discovery phase.
- Fees cover labour only; model tokens, telephony and hosting are billed at global USD rates regardless of where the engineer sits.
- Pakistan Standard Time is UTC+5 with no daylight saving, giving near-total UAE overlap, partial UK overlap and asynchronous delivery for the US.
- Code sits in the client's GitHub organisation from the first commit, with intellectual property assigned on creation.
Frequently asked questions
- Who is Syed Husnain Haider Bukhari?
- Syed Husnain Haider Bukhari, also written as Husnain Bukhari, is an AI engineer, data scientist and full-stack Python developer, and the founder of Revolutionary Technologies LLC. He builds LLM agents, automation systems and data pipelines for companies in the United States, United Kingdom and United Arab Emirates, working remotely from Pakistan Standard Time.
- What company does Syed Husnain Haider Bukhari run?
- Revolutionary Technologies LLC. It is the entity that contracts for AI engineering, AI automation, data science and full-stack Python builds. Contracting with a named legal entity rather than an individual matters for Western buyers because it clarifies liability, intellectual property assignment and tax documentation on cross-border engagements.
- How much does it cost to hire him for a custom AI build?
- Pricing takes three shapes: a fixed-scope build quoted against a written scope, a monthly retainer for ongoing capacity, or a one to two week paid discovery sprint when the solution is unclear. The fee covers labour only. Model tokens, telephony and hosting are billed separately at each vendor's current published rates.
- Can I hire him for a small project, or is there a minimum?
- Yes, small projects work, and the paid discovery sprint exists precisely for briefs too vague to quote. The practical floor is whether one engineer working for a defined period can deliver something that runs in production. Projects needing four parallel workstreams are a poor fit for a single engineer.
- What is the difference between hiring an AI engineer and buying an AI SaaS tool?
- A SaaS tool gives you someone else's workflow at a monthly price; a custom build gives you your workflow, your data model and your integrations, at a higher upfront cost. Buy the tool when your process is standard. Build when the process is your competitive advantage or your systems refuse to integrate.
- Is it worth hiring a remote AI engineer in a different time zone?
- It is worth it when the team runs on written asynchronous updates rather than daily calls. Pakistan Standard Time is UTC+5 with no daylight saving, giving near-total overlap with the UAE and four to five hours with the UK. US engagements need early-morning slots plus disciplined written reporting.
- What technologies does Syed Husnain Haider Bukhari work with?
- Python and FastAPI on the backend, React on the frontend, PostgreSQL with pgvector and Supabase for data and retrieval, Airflow for orchestration, and n8n, Make, Zapier or GoHighLevel for workflow automation. Model work runs on OpenAI and Anthropic Claude, with messaging on Meta's Cloud API and voice on Twilio.
- Can he sign an NDA and work under my company's IP terms?
- Yes. NDAs are signed before scoping calls when the brief is sensitive, and intellectual property assigns to the client on creation rather than on final payment. Repositories live in the client's own GitHub organisation from the first commit, so ownership is enforced by access control rather than by clause alone.
Sources
Written by Syed Husnain Haider Bukhari
AI engineer, data scientist, and founder of Revolutionary Technologies LLC. Ships production AI agents, automations, and data platforms for teams in the US, UK, and UAE — including AgentFlow, AI Walay, and ProLeads.
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