AI digital workers, part of your team
Digital workers take on the routine inside the tools your team already uses, so people can give their time to the work that needs them. Nothing changes until a person approves it.
AI digital workers at a glance
- What it is
- Agentic AI that carries out defined steps of a workflow, such as reading, checking and drafting, inside your existing systems.
- Who it is for
- Teams that handle large volumes of documents, requests or records.
- Where
- Organisations across Singapore and the region. Private AI, deployed in your own cloud account or a Singapore cloud region.
- How it starts
- A pilot for one workflow and one team, then scaled to more.
- Control
- AI governance from day one: permission-aware, human-in-the-loop approval before any change, full audit trail.
Your best people spend their best hours on routine work
In most organisations, skilled people spend a large part of every day on work that follows the same pattern: reading documents, pulling out the details that matter, checking them against a standard and writing the first draft of a reply or report.
Generative AI can now handle much of that pattern work. The hard part is making it useful inside a real team: connected to your systems, aware of who may see what, and never acting on its own authority.
That is where we come in.
Where teams start
Contracts and agreements
Extract key terms, compare them with your standard positions and flag exceptions for review.
Customer and supplier requests
Read incoming emails and forms, draft replies and route each case to the right person.
Reports and records
Turn operational logs, notes and data into consistent first-draft reports.
Compliance checks
Check submissions and documents against a checklist and record the result.
How a digital worker helps
Read and extract
Work through contracts, forms, emails and reports, and pull out the terms, dates, amounts and names your team needs.
Check and review
Compare documents with your policies, templates or past decisions, and flag what differs for a person to look at.
Draft
Prepare first versions of summaries, replies, reports and records in your format and tone.
Find and answer
Answer questions grounded in your own documents and data (RAG), with a link back to the source.
Hand over
Route work to the right person with the context they need, and record what was done.
Work inside your tools
Connect to the systems, file stores and chat channels your team already uses, instead of adding another app.
How we bring them into your team
- 01
Map the work
We follow one workflow end to end with the people who do it, and agree where AI saves the most time and where a person must decide.
- 02
Pilot with one team
Together we shape a digital worker for that workflow, connect it to real systems and measure it against how the work is done today.
- 03
Govern from day one
Human-in-the-loop by design: every action follows the user’s permissions, every change waits for approval and every step is logged for audit.
- 04
Scale what works
When the pilot proves its value, we extend it to more workflows and teams, and keep supporting it as your processes change.
What you can expect
- A map of the workflow and an agreed pilot scope
- A working digital worker connected to your systems
- Permission, approval and audit settings configured for your team
- Pilot results measured against the goals we agreed
- A plan for scaling to more workflows and teams
Built on what we already run
We put governed AI into our own platforms before offering it to clients.
An MCP server for operational data
A secure Model Context Protocol (MCP) server that lets AI assistants answer questions from a space-management database, with per-user keys that can be revoked at any time and every query logged.
An AI teammate inside a CRM
In easySales, our own CRM, an AI assistant finds records and drafts documents, follows each user’s permissions and asks before saving anything.
Applied AI in the field
Before generative AI, we integrated computer vision into access control and building systems. The same discipline of testing, privacy and integration carries over.
Questions we often hear
What is an AI digital worker?
Software that uses AI to carry out a defined part of a workflow, such as reading incoming documents and drafting a summary, inside your existing systems. It works for your team, not instead of it: a person reviews and approves its output.
How do you keep our data safe?
A digital worker only sees what the person it acts for is allowed to see. We can deploy in your own cloud account or a Singapore region, use AI services configured not to train on your data, and log every action for audit. We design with Singapore’s PDPA in mind.
How long does a pilot take?
A pilot covers one workflow and one team. We agree the scope, timeline and success measures with you before we start, so you know exactly what you will see at the end.
Which AI models do you use?
We are model-agnostic: we choose per use case and data requirement, working with the major cloud and model providers, so you are never locked into a single model.
Do we need to change our systems?
Usually not. Digital workers connect to the systems and file stores you already use. Where a system has no interface, we build the integration.
How do we start?
Tell us which workflow takes your team the most time. We will map it with you and propose a pilot.
Where could AI make a difference for your team?
It starts with a conversation. We’ll explore it with you.