AI Agents & Agentic Systems

AI Agents That Research, Decide and Act for Your Business

A chatbot waits for a question. An agent is given a goal, works through the steps, uses your tools and reports back. We build agents for Malaysian companies that want to hand over whole tasks, not just conversations.

agent-run.log
08:00:00goal: qualify overnight leads
08:00:0114 new enquiries pulled from CRM
08:00:04company websites and LinkedIn checked
08:00:09scored 14, 5 high priority
08:00:10draft replies written for review
08:00:10summary posted to Telegram
DONE10 seconds, sales team starts with the best five

An agent run from a real lead qualification setup. Humans still send the replies.

What We Build

Agents for the work that needs judgement

Simple automation handles the predictable. Agents handle the tasks where a person would normally have to read, compare and decide. We build them with guardrails so they act inside limits you set.

Research agents

Given a question, they search, read, cross-check and return a sourced summary. Market checks, competitor monitoring, supplier due diligence, all on schedule.

Lead qualification agents

Enrich every enquiry with company data, score it against your ideal customer, draft a first reply and route it to the right salesperson.

Document processing agents

Read invoices, contracts, tender documents or forms, extract what matters, check it against rules and file it in the right system.

Content operations agents

Turn one source into posts, captions, summaries and newsletters in your voice, queue them for approval and publish on schedule.

Internal knowledge agents

Answer staff questions from your SOPs, policies and past projects, with the source attached. Onboarding gets faster, senior staff get fewer interruptions.

Monitoring and alert agents

Watch your inbox, systems or the web for things that matter, decide if they are urgent and alert the right person with context, not just a notification.

How We Build Them

Your infrastructure, your data, your limits

Agents are deployed on a server you control, in Malaysia or Singapore or inside your existing cloud. Your data does not leave your environment to train anyone else's model. We work with the major model providers and open-weight models, and pick per task on cost, speed and accuracy.

Every agent has a defined scope, an approval step for anything irreversible and a log of every action. You can see what it did and why, and stop it at any time.

Model choice

Commercial and open models

n8n

Orchestration

PostgreSQL

Memory and records

Your VPS

Malaysia or Singapore

Telegram

Reports and approvals

Your tools

CRM, email, drive, APIs

How It Works

Scoped small, proven, then expanded

Step 1

Define the goal

One task, clearly described, with what "done" looks like and what the agent must never do on its own.

Step 2

Connect the tools

We give the agent access to only the systems it needs, with read access first and write access only where agreed.

Step 3

Run supervised

The agent works with a person reviewing every output. We tune prompts, rules and tools until the review finds nothing to correct.

Step 4

Release and monitor

Approval steps stay where the risk is. Everything is logged. We review the logs with you monthly and extend the scope.

Real Examples

Agents running for real businesses

AlphaX agent that captures, rewrites and posts crypto content on X

Content operations

Hourly posting on X, two taps of effort

AlphaX watches selected accounts, rewrites content in the creator's style, posts on a schedule and replies to comments. The creator approves in batches from his phone.

"Something I didn't even think was possible to automate." Eric, Crypto Content Creator

The Post Office social media content agent scheduling weekly Facebook and Instagram posts

Marketing operations

A week of social content from one brief

The Post Office takes a short weekly brief, drafts the posts, lays out the calendar and queues everything for approval. What used to take a day takes minutes.

See more work
internal tool

Internal research

A research agent on Telegram

An always-on research assistant that searches the web, reads full pages and returns sourced briefs to a Telegram chat. Used daily for market and technical research inside ETokina.

Ask for a demo

Common Questions

Before you get in touch

What is the difference between a chatbot and an AI agent?

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A chatbot responds to messages. An agent is given a goal and works towards it in steps: searching, reading, using tools, writing and checking, then reports back. Many of our chatbots have an agent behind them for the hard questions.

How do you stop the agent from making mistakes?

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Three ways. It only has access to the tools it needs. Anything irreversible, like sending an email or making a payment, waits for approval. And every action is logged so mistakes are visible and fixable, not hidden.

Which AI models do you use?

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Whichever fits the task. We work with the major commercial providers and open-weight models that can run on your own server. Cost, speed, accuracy and data residency decide the choice, and we explain it before building.

Can it run on our own servers?

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Yes, and we recommend it. Agents can run on a VPS you control in Malaysia or Singapore, or inside your existing cloud account. Your data stays in your environment.

What does an agent cost to run each month?

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Server cost plus model usage. For most single-purpose agents this is a few hundred ringgit a month. We estimate it before build and show you the actual usage once live.

Which task would you hand to an agent first?

Pick something that eats a person's morning: research, lead follow-up, document checking. We will tell you honestly whether an agent can do it well today.

Discuss an agent project

Related: workflow automation and AI chatbots for Malaysian businesses