AI Consulting
Where AI belongs in your operation, ranked by payback, after the check that says whether you are ready for any of it.
We build the systems your business runs on.
An AI-native software house in Jakarta, with delivery partners in Japan and Hong Kong.
One working system, at a fixed price and a fixed timeline, put where the work already happens.
You are not behind. You are busy.
Work we turn down
A company with no data does not need a model. Asked for a credit scoring engine by a client holding no usable data, the answer was no, and the answer stays no. If the operation needs digitalising before it needs AI, we say so and we digitalise first.
The field moves every week or two. Nobody running a two hundred person business is tracking it, and nobody should have to. That gap is the whole of the problem, and it is a reading problem before it is an engineering one.
So we are not going to build you a model. We do not compete with the labs and we would lose. We orchestrate what already exists, and we put it inside the group chat, the portal or the call your team is already in.
Six practices, one delivery team.
Most engagements start in one of these and grow into a second. They are listed in the order they usually happen, not in the order we would like to sell them.
AI Development
Agents that answer the message, systems that read the document or the photograph, connected to what you already run.
Software Development
The core operating system for a business that has outgrown its spreadsheets, and the portals hanging off it.
Websites and Presence
Company profiles and campaign sites, built to be handed over rather than rented back to you.
IoT and RFID
Gate level tracking for stock that walks, and maintenance called before the machine stops.
Data and Machine Learning
The unglamorous half. Pipelines, governance, and the dashboard that agrees with finance.
The claim is checkable, so check it.
Every software house says it is fast. Here are four things you can hold us to in writing.
3
hour change SLA
Against an industry typical twenty four.
Inside working hours. A portal takes the request, the AI does the work immediately, and nothing deploys without an engineer approving it. Speed from the first half, safety from the second.
In force on live client work
0
new tools to learn
Change requests happen in the group chat you already have.
The agent sits in your own WhatsApp group. You tag it, describe the change in your own words, and it opens the work. Running today on a live client site.
Running on live client work
1
designer, not a queue
Design to production is an agent, not a hand off.
An agent reads the design file and builds it to match. Designers get hired for the system and the taste, not for redrawing the same page at three widths.
Figma to production, in use
2
numbers fixed up front
A fixed price and a fixed timeline, both before we start.
An internal project burns unknown manpower on something that may never ship. At the end of a fixed timeline you know whether it works. Even the worst case has an answer in it.
Standard commercial terms
How an engagement runs.
The same six steps every time, in this order. Two of them can end it before anything is built, which is the part that makes the other four worth paying for.
Find where AI actually belongs
We map the operation first: who touches what, and where the paper stops. The technology comes after that, or not at all.
We map the operation first: who touches what, and where the paper stops. The technology comes after that, or not at all.
Check you are ready for it
No data, no model. If the business needs digitalising before it needs AI, we say so and we digitalise first.
No data, no model. If the business needs digitalising before it needs AI, we say so and we digitalise first.
This step can end the engagement
Rank by payback, not by hype
Every candidate use case is scored on feasibility and on what it returns, before a line is written.
Every candidate use case is scored on feasibility and on what it returns, before a line is written.
So can this one, if nothing clears the bar
Build one working system
Fixed price, fixed timeline, one thing in production. Not a pilot deck and not a proof of concept that never ships.
Fixed price, fixed timeline, one thing in production. Not a pilot deck and not a proof of concept that never ships.
Put it where the work already happens
Inside the group chat, the portal or the call your team is already in. Adoption is a placement problem more often than a product one.
Inside the group chat, the portal or the call your team is already in. Adoption is a placement problem more often than a product one.
Stay after it ships
We monitor what we handed over, we fix what breaks, and we grow the part that is already working.
We monitor what we handed over, we fix what breaks, and we grow the part that is already working.
Where the systems have gone.
Six sectors, and in every one of them the deliverable was a system somebody uses on a Monday morning rather than a report.
Media and broadcast
Subtitling and dubbing that translates against the story rather than line by line, plus the analytics on top.
Banking and multifinance
A credit interview copilot that flags a spoken claim contradicting the uploaded document, and appraisal from photographs.
Logistics and distribution
Systems that were never meant to speak, joined. Plus RFID at the gate for stock that walks.
Outsourced customer service
A live listener feeding the human agent the answer mid call. The client did not want AI facing customers, so it does not.
Internal operations
A system mirroring the WhatsApp groups a team already lives in, chasing deadlines and answering in the thread.
Climate and physical risk
Asset level hazard modelled against financial exposure, on open data and published method rather than a black box.
Selected clients
Built on
Tell us what is slow.
Not what you want built. What is slow, or manual, or getting missed. The first conversation is about your operation and it costs nothing, and if the honest answer is that you do not need us yet, that is the answer you will get.
Arah AI
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