AI Agents & LLM Applications
Tool-using agents and grounded assistants that work with your knowledge, APIs, and business rules.
- RAG and knowledge assistants
- Multi-agent orchestration
- Evaluation and guardrails
Available for new builds
Muhammad Daniyal · AI Engineer
I design and ship the systems myself — agents, LLM applications, voice callers, and automations across n8n, Make, Zapier, and GoHighLevel — engineered around one thing: a measurable outcome for your business.
Top Rated freelancer · 70+ projects delivered · Working worldwide
What I build
Every engagement replaces a slow, manual process with a system that can think, act, and report.
Tool-using agents and grounded assistants that work with your knowledge, APIs, and business rules.
End-to-end operations across n8n, Make, Zapier, and GoHighLevel that route decisions and recover cleanly when an API fails.
Natural voice workflows that answer, qualify, book, and follow up while keeping your CRM current.
Focused prototypes and internal tools that turn an AI concept into software people can actually use.
Business websites built to the same standard as this one — immersive 3D, sharp motion, and pages engineered to convert, with your booking, forms, and automations wired in from day one.
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Inside the systems
Reference builds I design in the tools I work in daily — open one and inspect every node, route, and failure path. This is the standard your system gets built to.
Selected work
Every build starts with the operating problem, then connects models, logic, tools, and people around it.
Voice AI · Showcase build
A voice-first qualification system that answers property leads, structures the call outcome, scores intent, updates GoHighLevel, and alerts the right agent while the opportunity is still hot.
LLM automation · Client system
An AI content engine that turns spreadsheet records into listing copy, tracking links, and image variants, then writes every approved output back to the operating data layer.
LLM application · Technical demo
A decision pipeline that enriches a support request with customer context, validates the applicable policy, and produces a useful next action instead of an unsupported answer or generic refusal.
Operations automation · System build
A stateful document-chasing workflow that creates a client checklist, tracks received files, updates a live status layer, and notifies both the client and the internal team at the right moment.
Direct collaboration
I'm an AI engineer based in Islamabad, working remotely with clients worldwide. My background spans automation delivery, LLM systems, API engineering, and applied machine learning — and my motive is simple: use agents and automation to enhance how a business runs, whatever that business is.
Working with me directly means faster decisions, clearer ownership, and a system built around your operation — not a ticket in someone's queue.
Download my resumeDefine the bottleneck, users, data, success signal, and constraints.
Choose the model, tools, integrations, safeguards, and human handoffs.
Ship in testable milestones with real inputs, logs, and failure paths.
Deploy, document, train the operator, and support the live system.
Start a project
Share the workflow, the current tools, and what a successful result looks like. I'll respond directly with the next useful step.