It knows the internet, not you
A general model has read everything and none of your files. It cannot quote your policy, follow your process or name your people.
Custom-built · Sovereign by design
AI built for one institution — yours.
Built for your institution, not for the internet — trained on your documents, wired into your systems, shaped around how one department actually works. Your hardware. Your data. Your model. Your rules.
The brain, inside
Egress closed_
Reads Connects Reasons
The problem
Generic AI does not know your institution. And it does not stay in your building.
It never fits the work
A chat box bolted beside the systems your teams actually work in. Configuration is not the same as being built for you.
And it goes outside
Your files leave the building to be read on someone else's servers, under someone else's terms.
What it does
Three jobs. One brain.
It learns the institution before it says a word.
01
Reads
Every manual, contract, judgment and report the institution holds.
02
Connects
Plugs into the systems you already run, on the network you already have.
03
Reasons
Answers, drafts and forecasts — from your documents and nothing else.
The platform
One brain. Many faces.
The same engine, pointed at a different function each time. Six faces of one brain, each trained on the corpus of the team it serves.
Vakel AI
Less time searching. More time arguing.
Statutes and judgments in the corpus. Every answer cites law you can click.
Ustad
Curricula that keep up. Exams you can trust.
Checks courses against current standards. Sets and grades to one rubric.
RCS
One brain. Every secretary.
Schedules without clashes, answers live KPI questions, tracks every decision.
AATS
The plant floor, finally answering back.
Manuals, incidents and sensor history in one memory. Forecasts failures.
E-Office
Drafting, in the file you are already in.
A drop-in for the document system you already run. Notes and replies in the house voice.
Shahid
A witness on every corner.
Runs on the camera itself. No streaming, no cloud, no blind gate.
Your department · Your corpus · Your name on it
Ventures
Built by a team that ships platforms.
Mulazim comes out of Liwa Labs. The same engineers have taken these ventures from concept to launch across FinTech, Web3, AI and mobile.
Vakel AI
Statutes and judgments, cited and clickable
Oro Gold
Gold-backed on-chain ecosystem
Liquid Prop
Fractional US real estate on-chain
ZAR
Cash to digital dollars, Visa cards
Honeycomb
Core utilities for Solana projects
Sol Patrol
Real-time multiplayer strategy
RFRSH
Portfolio and wallet analytics
Callwala
AI representative for contact centres
Eve
Anti-harassment technology stack
Aitells
Conversational AI, built before the LLM wave
The pattern
Same brain. Every domain.
Drop in a new corpus, connect a new system, and Mulazim becomes the next thing your institution needs. Nothing leaves the perimeter to make it happen.
Controls
What your security office asks for.
Weights, prompts and logs sit on your storage. There is no outbound call to make.
Directory integration, role-based permissions, per-department segregation.
Every prompt, retrieval and response is recorded and exportable for review.
Runs with the network cable out. Updates arrive as signed media on your schedule.
Questions
Questions your team will ask.
Where does Mulazim AI run?
On your racks, in your private cloud, or fully air-gapped. Weights, prompts, logs and retrieved documents all sit on your storage. It runs with the network cable out, and updates arrive as signed media on your schedule.
Does our data ever leave the building?
No. There is no outbound call to make. Nothing is sent to a third-party API, nothing is used to train anyone else's model, and your corpus never becomes someone else's product.
How is this different from ChatGPT, Copilot or Gemini?
Those are general models that have read the internet and none of your files. Mulazim is built around one institution's corpus and one department's process, so it can quote your policy, follow your procedure and name your people — because that is all it was trained and wired to do.
What does it need to learn our institution?
The documents you already hold — manuals, contracts, judgments, SOPs, board minutes, case files. We scope which corpus comes first during the briefing, along with the systems it needs to connect to.
Does it work in Urdu?
Yes. Urdu and English, including mixed-language documents and queries.
Who can see what?
Access follows your directory. Role-based permissions and per-department segregation are set at deployment, and every prompt, retrieval and response is recorded and exportable for review.
What happens in a briefing?
Ninety minutes with your technical and legal teams. No slides — a working session. We scope the work, the documents it would run on, and the hardware your build would need. Under NDA on request, in Karachi or at your site.
Next step
Bring us one department.
Ninety minutes with your technical and legal teams. We scope the work, the documents it would run on, and the hardware your build would need.
No slides · A working session Under NDA on request Karachi or your site