STAGE 01
Define
A fixed set of context files — product intent, domain rules, architecture, constraints, definition of done. The thinking happens here, once.
Building the systems that build the products
Talha GhiasAI Systems Architect
- World-class AI systems, built from Lahore
- Multi-agent orchestration & agentic AI
- Engineering leader · 10 years, 30+ engineers
- Fractional CTO & AI transformation
- World-class AI systems, built from Lahore
Ten years learning how real systems break — banking platforms, healthcare networks, lending engines. Then I built my own orchestration engine: a spec goes in, a finished product comes out. I don't use AI. I architect it. And I'm building at a scale this region hasn't seen yet.
0Engineering, hands on
0Banks onboarded, 2022
0Health agencies in 60 days
0Engineers led
Available for select engagements
SCROLL
Who I am
Ten years of hard systems. Now pointed at AI.
I started where everyone starts — writing features. Then backend architecture, distributed systems, cloud. Then leading engineers, and the uncomfortable discovery that even excellent developers can't rescue a product when requirements, architecture and business goals are disconnected. That's when my attention moved from code to systems, and from systems to the organisations that build them.
Today I consult at GlobalTech — Center of Excellence, alongside independent engagements. My depth is in domains where being wrong is expensive: banking, lending, underwriting, healthcare, payroll. And I've turned that same architectural instinct on AI — not calling an API, but designing systems of agents that plan, retrieve, verify and ship.
Node.jsTypeScriptNext.js
Ruby on RailsLaravelPostgreSQL
MongoDBMicroservicesAWS
AzureRabbitMQLangGraph
RAGAgent orchestrationEvals
The flagship
The Orchestra: a spec goes in, a product comes out.
I built my own agentic development engine. It ships with the scaffolding every product needs — the roadmap, the stories, the architecture and context files. Fill those in, start the run, and the orchestra conducts Claude and Codex through the build until the product is standing.
STAGE 02
Plan
The engine expands the spec into a roadmap and story graph, with dependencies, acceptance criteria and the order of attack already resolved.
STAGE 03
Conduct
Work is routed to the right model for the job. Agents implement, review each other, run the tests and correct their own output.
STAGE 04
Ship
A working product with a coherent architecture, not a pile of generated files — because the structure was decided before a line was written.
What ships in the box
- Complete roadmap and story templates
- The context files every product needs, standardised
- Architecture and coding standards the agents must obey
- Review, test and correction loops between agents
- Model routing rules — which model, for which task
- Human checkpoints where judgement actually matters
Why it matters
Most teams use AI to write functions faster. That's a small win. The leverage is in encoding your architecture, standards and delivery process into the system itself — so quality stops depending on who is at the keyboard, and speed stops costing you maintainability. That's the difference between using AI and architecting with it.
Built with it
Products, not demos.
Systems I've designed and built end to end — each one a proving ground for the architecture behind it.
ORCHESTRATION ENGINE
The Orchestra
My agentic build system. Roadmap, stories and context scaffolding, plus a conductor that drives Claude and Codex through implementation, review and correction until the product is done.
HEALTHCARE AI
AI Doctor
A clinical reasoning system where a general medical agent takes the first pass and an orchestration layer escalates harder cases to specialist agents — with retrieval, memory, guardrails and a human escalation path built in from the start.
VOICE & WORKFLOW AI
AI Receptionist
An always-on front desk that handles enquiries, qualifies callers, books appointments and hands off cleanly to a human — the kind of automation that shows up on a payroll line, not a pitch deck.
The unglamorous edge
Knowing which model, and when.
Model choice is an architecture decision with a price tag attached. Most AI projects don't fail on capability — they fail on the wrong model doing the wrong job at the wrong cost.
Deep reasoning, one shot
Architecture, ambiguous specs, gnarly debugging. Pay for the strongest model here — this is where a bad answer costs weeks.
High-volume, well-defined
Classification, extraction, routine transforms. A fast, cheap model with tight prompts and evals wins on every axis that matters.
Long-context synthesis
Whole-repo reasoning and large document sets. Context window and retrieval strategy matter more than raw benchmark scores.
Agentic, tool-heavy work
Multi-step execution with real side effects. Pick for instruction-following and tool reliability, then wrap it in guardrails.
When not to use AI at all
Deterministic rules, financial calculations, anything auditable. A model is the wrong tool, and I'll say so early.
Evaluate, then commit
Every routing rule earns its place against a real eval set. Vibes are not an architecture.
Bring me the problem nobody wants.
A rebuild that keeps slipping. A team that's busy but stuck. An AI initiative that demos beautifully and ships nothing. That's the work I want.
Start the conversation
How I work with companies
What I do
Founders and technology leaders bring me in when a decision is about to get expensive to reverse — or already has. I take a small number of clients at a time, so the ones I take get the depth.
Check availabilityAI systems architecture
Agentic workflows, multi-agent orchestration, RAG and context engineering, model routing, evals, guardrails and observability — designed around a business number that has to move.
Fractional CTO
Senior technology leadership without the full-time hire. Strategy, architecture, hiring, engineering process, roadmap, and the calls that are painful to unmake.
Engineering assessment
A structured audit of architecture, code, security, cloud cost, technical debt, DevOps and team structure — with prioritised recommendations and what each one is worth.
Startup technology rescue
For teams missing every deadline, burning infrastructure budget, or scaling on architecture that was never designed for the load it's now carrying.
AI-accelerated delivery
Put the Orchestra behind your roadmap. Your architecture and standards encoded into the system, then products built at a pace a traditional team can't match.
Receipts
Ten years of systems that carry real weight.
Money moving, patients treated, payroll running. Domains where approximately right isn't good enough.
BANKING · FINTECH
Bank onboarding platform
Engineering on a financial platform built to onboard banking institutions. Around 22 banks were onboarded on it during 2022.
HEALTHCARE
Home-care agency platform
MERN microservices for healthcare agency workflows, with WebRTC consultations and government reporting. Around 35 agencies onboarded inside two months.
LENDING
Automated underwriting
Lending systems that automate application processing and decisioning, and analyse repayment behaviour to sharpen risk decisions.
MULTI-PRODUCT SAAS
Signage, WiFi music & hospitality
Principal engineering across three product lines — and I founded and grew two of them, on containerised backend services built to scale.
CURRENT
GlobalTech — Center of Excellence
Consulting on architecture, technical governance, engineering process and delivery standards — alongside independent consulting engagements.
ENTERPRISE
HR, payroll & enterprise platforms
HRMS and payroll systems, telehealth, digital signage and SaaS infrastructure across a decade of product and platform engineering.
The path
Developer to architect to AI systems.
GlobalTech — Center of Excellence
Consultant · current
Architecture, technical governance and engineering standards, alongside independent consulting and AI engagements.
Neon
Principal engineer / engineering manager
Digital signage, WiFi music and hospitality product lines — founded and grew two of them on containerised AWS infrastructure.
Giggle Finance
Lending & automation
Automated underwriting, application processing and repayment-behaviour analysis.
Finstreet / 10Pearls
Senior engineering, banking platforms
Banking systems on Node.js, Rails, Next.js, AWS, Azure, MySQL and RabbitMQ. Around 22 banks onboarded during 2022.
CareSnap
Healthcare technology
MERN microservices, WebRTC consultations, agency workflows and government vaccination reporting.
Earlier
Techverx · People · PayPerfect · Emerald Labs · Logicon · Strategic Systems International
Product and platform engineering across HR, payroll, enterprise and SaaS systems.
PUCIT
Software Engineering, 2016
Where it started.
How I think
Non-negotiables
Requirements before implementation
No team reliably delivers something nobody has clearly defined. Most "engineering problems" start here.
Architecture before scale
Technical debt compounds like financial debt, and the interest is paid in delivery speed forever.
Evidence over assumptions
Decisions rest on the code, the metrics and the tests — not on whoever argued hardest in the meeting.
Process should free engineers
It exists to create predictability and quality. The moment it becomes paperwork, it's failing.
AI has to earn its place
Bolting an LLM onto a product doesn't make it an AI product, and it doesn't make it better.
Engineers should know the business
The strongest ones understand exactly which economic problem the software exists to solve.
Where this is going
I'm building for scale, and I'm not being quiet about it.
The ambition is simple: build technology that reaches millions, from Pakistan, and prove that the engineering coming out of this part of the world competes with anyone's. Consulting funds it. Products compound it. Here's what I'm aiming at.
Fewer catastrophic decisions
Help founders dodge the architecture calls that quietly cost a year of runway.
Teams that actually ship
Turn busy-but-stuck engineering groups into ones that deliver predictably.
Work machines should do
Automate expensive manual process, and apply AI only where it visibly pays for itself.
Systems people depend on
Healthcare, lending and business systems where correctness affects someone's real life.
Engineers who can lead
Mentor engineers here into people who own architecture and delivery anywhere in the world.
Products and IP, not just hours
Move from selling time, to selling expertise, to owning software that scales without me.
Available for select engagements
Tell me what's breaking.
Architecture review, a stalled rebuild, an AI initiative that needs a real plan, or a product you want built fast and built right. Send the short version — I'll tell you what I'd look at first.
Based inLahore, Pakistan — working with teams in the US, UK, Europe and the Gulf
LinkedInTalha Ghias - LinkedIn
Opens your mail app. To capture messages directly, point this at a form service — see the comment in the code.