Business AI Solutions Singapore
AI that answers from your own documents, handles routine customer questions and reads the paperwork your team types up by hand. Built on Google Vertex AI and Gemini, starting with one clear job.
- Answers grounded in your own documents
- Hands over to a person when unsure
- Usually live in about a month
- Use cases deployed
- 101+
- Typical time to launch
- 1 month
We build on Google's Vertex AI with retrieval-augmented generation (RAG), so answers come from your documents rather than the model's general knowledge.
- Gemini
- Vertex AI
- RAG
- Google Cloud
Trusted by innovative teams worldwide
What Business AI Can Do for You
Each of these starts as one focused assistant, built on your own documents and data.
Knowledge assistant for your team
Staff ask questions in plain English and get answers drawn from your SOPs, policies and product sheets, with a link to the document each answer came from.
Customer support assistant
Answers routine questions on your website or messaging channel from your own content, and passes anything it cannot answer to your team with the conversation attached.
Product and sales assistant
Knows your catalogue, specifications and pricing rules, so customers and sales staff get accurate answers without searching through files.
Document processing
Reads invoices, forms and PDFs, pulls out the fields you need and writes them into your system, with anything unclear set aside for a person to check.
Drafting in your house style
First drafts of product descriptions, customer replies and internal reports, written from your own material for your team to review and edit.
Forecasts from your own data
Trends from your sales, bookings or support history, to help plan stock, staffing and promotions.
How We Keep It Reliable
An AI assistant is only useful if your team can trust its answers. This is how we build that trust.
Grounded in your data
Answers are drawn from the documents you choose and show their source, so your team can check them.
A person stays in the loop
When the assistant is unsure, or the request is sensitive, it hands over to a member of your team instead of guessing.
Tested before it goes live
We test against real questions from your business, including awkward ones, and fix the gaps before launch.
One clear job first
We start with a single, well-defined use case, prove it works, then extend it. No sprawling AI projects.
From One Question to a Working Assistant
Five steps, from choosing the job to a live assistant your team trusts.
- 1.
Pick the job
We agree one task for the AI to do, who will use it, and what a good answer looks like.
- 2.
Gather the sources
We collect the documents and data the answers should come from, and leave out anything that should stay private.
- 3.
Build and ground
We set up the model on Vertex AI, connect it to your sources with RAG, and add the rules for when it should hand over.
- 4.
Test with real questions
Your team tries it with real questions. We measure where it is right, where it is wrong, and tune it before launch.
- 5.
Launch and monitor
It goes live where your team or customers already are, and we review its answers and update the sources as your business changes.
Frequently asked questions
It is software that uses a language model to do work that needs reading or writing: answering questions, summarising documents, pulling details out of paperwork or drafting text. For a business, the useful versions are the ones tied to your own information and checked by your team.
RAG stands for retrieval-augmented generation. Before the model answers, it looks up the relevant passages in your documents and answers from those. That keeps answers specific to your business and lets each one show where it came from.
Any language model can give a wrong answer, which is why we ground it in your documents, show the source, and set it to hand over to a person when it is unsure. We test it against real questions before launch so you know how it behaves.
Google’s Vertex AI terms state that customer data is not used to train its models. We set up access so only the people and systems that need your data can reach it, and we walk you through the settings before launch.
We design around the PDPA from the start: the assistant only sees the data it needs, personal data is kept out of the sources where possible, and access is limited and logged. We agree the approach with you during scoping.
A single, well-defined use case is usually live in about a month. Larger projects are built in stages, one use case at a time.
It depends on the job, how many sources it draws from and where it needs to run. After a free consultation we send a written plan with the scope, timeline and price before any work starts.
Business automation moves a fixed process between your tools: when an order comes in, create the invoice. Business AI handles work that needs reading or judgement, such as answering a question or reading a document. Many projects use both, and we scope them separately.
Tell us the question your team answers every day
Describe the task and where the answers live today. We will tell you honestly whether AI is the right fit.