AI Implementation & Automation · Portfolio

Fareeha
Saif

AI Implementation & Automation Specialist

I build, ship and run AI agents in production, and I close out whatever is stuck. Everything I send has been read first.

Based in
Abu Dhabi, United Arab Emirates
Hours
US Pacific or UTC, remote
Experience
9 years
Portrait of Fareeha Saif
Portfolio

Live demos

Selected work

Production AI, judged by what it finishes

I run an autonomous AI agent at a US law firm that completes client case files over SMS and email, in English and Spanish. Client details stay private, so the demos rebuild the same ideas on invented data.

A case file that completes itself

Problem
Staff spent their days chasing clients for contracts, repair orders and photos, one text at a time.
What I built
An agent that takes each file from first request to complete: it asks, collects, checks each document and follows up, in English or Spanish.
Result
Staff step in only for flagged exceptions. Records, messages and documents stay in sync across HubSpot, Gmail and Google Drive.

Rules the agent cannot talk its way past

Problem
An agent that texts real people has to respect opt-outs, quiet hours and do-not-contact lists every single time.
What I built
Opt-out and do-not-contact checks before every send, an hourly do-not-contact sweep, quiet hours, a 1,500 a day cap, duplicate prevention and human escalation for sensitive cases.
Result
The rules sit outside the model, so a clever message cannot switch them off.

Shipping daily without breaking trust

Problem
A live agent needs constant improvement, and every change touches real conversations.
What I built
CI-gated deploys, automated tests, guard hooks on AI coding agents, uptime monitoring and scheduled health reports.
Result
15 production changes in a single day, each verified live within 10 minutes, with weekly results reported to the firm owner.
In numbers

From the work

14,000+

client messages read and classified by the agent

1,500/day

send cap, with opt-out, do-not-contact and quiet hours enforced

15

production changes shipped in one day through CI-gated deploys

10min

to verify each change live after it ships

Ask about me

Answered from my resume, and nothing else

If the answer is not in my resume, it says so instead of guessing. That is the same rule my production agent follows.

Try to break it

Attack the guardrails

Type the kind of message that breaks AI agents: an injected instruction, hidden characters, a request for other people’s data, a fake admin. It goes to all three agents on this page, and you see which guard caught it and what each agent did.

These are rules, not a live model. That makes them easy to test and impossible to talk into anything, and it also means a new trick can slip past. When one does, the result says so.