Service
AI Agents & Workflow Automation
We design and build AI agents that read documents, make routine decisions and act inside your tools — automating the repetitive work that eats your team's day, with humans kept in the loop where it matters.
Illustration: one way an agent workflow can be shaped, with a person approving flagged cases.
In plain terms
What is an AI agent?
Think of an agent as a tireless junior colleague for one specific job. It reads what arrives, such as an email, a PDF or a ticket, works out what it means, and then takes the next step in your tools.
It follows the rules you give it, asks a person when it is unsure, and leaves a record of everything it did. The goal is to give your team their time back for work that needs judgment.
Use cases
Where agents help most
Repetitive, rules-heavy work that follows a pattern but still needs reading and understanding.
Document processing
Extract data from invoices, POs, contracts and emails into your systems.
Back-office operations
Reconciliation, data entry, report preparation and follow-ups.
Customer & internal support
Answer questions from your own knowledge base and hand off to people when needed.
Monitoring & triage
Watch alerts and inboxes, classify what arrives and route it to the right owner.
Safe and reliable
How we keep agents under control
Automation you cannot trust is worse than none. These are built into every agent we design.
Human-in-the-loop approvals
Sensitive or uncertain actions wait for a person to approve them before anything is changed.
Guardrails
Clear limits on what the agent may read, decide and do, with unclear cases sent to a human.
Audit logs
Every step and decision is recorded so you can see what happened and why.
Your data stays in your systems
Agents get least-privilege access to only what the task needs, inside the tools you already use.
Measured rollout
We start small, compare against the manual baseline and widen scope only when results hold up.
Example workflow
From inbox to ERP, with a person where it counts
An illustration of how a workflow can be shaped. Your own workflow will differ.
Invoice arrives by email
- Trigger
An email with an invoice attached arrives
- Agent
Extracts supplier, amounts and line items
- Check
Validates against the ERP and the purchase order
- Result
Matches are posted; mismatches are flagged for a person to review
Agents are only as good as the systems they can reach, which is why we also build platform integrations. We also build and run our own product in this space, NK Invoice, a toolkit for Vietnamese e-invoices.
What you get
Deliverables
A working agent, the evidence that it helps, and a team that can keep it running.
- Workflow discovery: find what is worth automating first
- Agent design with clear guardrails and approval steps
- Integration with your existing tools and data
- Measurable before/after on time spent
- Ongoing tuning and support
Process
Start with one workflow
- 01
Discover
We find the workflows worth automating and what a good result looks like.
- 02
Pilot
We build an agent for one workflow, with guardrails and approval steps.
- 03
Measure
We compare time spent and error rates against how the work is done today.
- 04
Scale
When the numbers justify it, we extend to more workflows and keep tuning.
FAQ
Common questions
What is the difference between an AI agent and a normal automation?
A traditional automation follows fixed rules and breaks on anything unexpected. An agent can interpret messy inputs such as emails and PDFs, then decide the next step within limits you set. For many workflows the best result combines both.
Will the agent make mistakes?
It can, which is why we design for it. Uncertain or high-impact cases are routed to a person, every action is logged, and we measure accuracy during the pilot before widening the rollout.
Where does our data go?
We design for your data to stay in your own systems, with the agent given least-privilege access to only what the task requires. We will walk through the data flow for your specific case before building anything.
Can an agent work with our existing ERP or other systems?
Yes, as long as there is a way in, such as an API, a database or a file export. This is also where our integration work helps: an agent is only as useful as the systems it can reach.
Which workflow should we start with?
Usually one that is repetitive, rules-heavy and easy to measure. Finding that workflow is the purpose of the discovery step.
Tell us what eats your team's day
Describe a repetitive workflow and we will tell you whether an agent is a good fit.