AI agent development for Singapore teams, built to reach production

An AI agent is software that uses a large language model to plan and complete a multi-step task with limited supervision. It decides what to do, calls tools or APIs to take real actions, observes the result, and continues until the task is done. Unlike a chatbot that only replies with text, or a RAG assistant that only answers from your documents, an agent can read context, retrieve data, and act inside your systems.

We ground the agent in your real data with retrieval and citations, scope its tool permissions so it can only do safe things, add human-in-the-loop checkpoints before high-risk actions, and build an evaluation suite that measures accuracy on real cases before launch. Guardrails, fallbacks, and production monitoring catch the rest. This evaluation layer is what separates a reliable agent from a demo, and it also produces the audit trail your risk and compliance teams need.

We measure cost per task during the pilot, then route simple steps to smaller models, cache repeated context, set token budgets, and track spend in production. That keeps cost predictable as usage grows, and tells you before launch what each completed task will cost.

It covers one real workflow, built and running on your own data; an evaluation set that measures accuracy before launch; and the cost per task with a production rollout plan. We also map the data and compliance requirements that apply to that workflow. It is a fixed-scope first step, so you decide whether to take the agent to production based on measured results, not a demo.

Yes. When Singapore data residency matters, we deploy on AWS ap-southeast-1, the Singapore Region with three availability zones, and keep your application data and vector store in-country, with prompts minimised so third-party LLM API calls carry only what the task needs. If your data must never leave the country, we can self-host open models on Singapore infrastructure. We design the data flow, model choice, and logging so you can answer exactly where your data goes.

Yes. Modern frontier models handle English and Mandarin very well, Malay well, and Tamil increasingly well, so we build agents that converse, read documents, and act in the languages your customers actually use, with retrieval, prompts, and evaluation designed per language rather than translated as an afterthought. We test accuracy separately in each language, because an agent that is reliable in English but merely plausible in Mandarin fails real Singapore customers.

Both depend on scope: how many systems the agent must integrate with, how sensitive the data is, what compliance requirements apply, whether it must work in more than one language, and how much evaluation the risk level demands. We start with a fixed-scope Agent Pilot Sprint on one workflow, then give you a written estimate for the production build, billed in SGD via Stripe, so you decide before committing.

Build in-house when you already have senior AI engineers with spare capacity. A Singapore agency gives you on-site workshops and a team in your city, and is the right call when your engagement demands a permanent on-site presence. We are the third path: a team that has shipped production software for 12+ years, with AWS ap-southeast-1 (Singapore) data residency, SGD billing, and an evaluation-first build process that gets agents past the pilot stage.

Yes. You own all source code, prompts, evaluation suites, and intellectual property we produce. Everything is committed to your repositories as we build, with no lock-in, so you can run, extend, or bring the work in-house at any time.