SINGAPORE

Enterprise automation that runs itself

We build AI systems that replace manual work. Faster than your team, cheaper than a hire, reliable enough to leave overnight.

See what we build

What We Do

We find the workflows that cost finance and investment teams the most time, then build the systems that run them without supervision. Two practices. One engineering standard.

Finance

Finance Automation

Quarterly reporting, reconciliation and data pipelines that finish overnight instead of running for weeks.

Finance automation →
Investment

Investment Infrastructure

Private fund data, portfolio query and forward-looking reporting for family offices and asset managers.

Investment infrastructure →

How We Work

01

Discovery

We map the current workflow — where the friction is, what breaks, and what “done” looks like. Observation, not assumptions.

02

Build

The system is engineered inside your firewall, designed to run without hand-holding. Working software in weeks, not months.

03

Deploy

Integrated with your existing stack, your team trained, the keys handed over. We monitor for the first 30 days.

04

Maintain

Continuous monitoring, iteration and improvement. The systems evolve as the business does.

What We Build

Finance

Finance Automation

Enterprises still process quarterly reports by hand across dozens of spreadsheets, and finance teams reconcile billing data week after week. We replace that with systems that run overnight.

  • Quarterly report processing
  • Finance workflow automation
  • Data pipeline engineering
Learn more →
Investment

Investment Infrastructure

Family offices manage multi-asset portfolios across disconnected platforms. Reconciliation is manual and risk reporting looks backwards. We build the unified layer that helps you think forward.

  • Private fund data platforms
  • Investment decision tools
  • Custom reporting systems
Learn more →

Why AI Automation Matters Now

What once needed enterprise budgets and six-month implementations now deploys in weeks. For finance and operations teams in Singapore, the question is no longer whether the tooling exists, but who captures the productivity gap while competitors are still evaluating vendors.

What changes when the pipeline runs itself
WorkflowBeforeAfter
Quarterly reporting 2–3 weeks per quarter, assembled by hand Narrative, figures and compliance checks produced in one overnight run
Portfolio data Positions spread across five or more platforms One query surface over funds, ledgers and trackers, answered in minutes
Document intake Statements, invoices and PDFs keyed in manually OCR and extraction producing pre-filled drafts at 90%+ field accuracy
Availability Business hours, single-threaded, capacity capped by headcount 24/7, and better on every run as the system is iterated

Problems We Solve

Singapore’s regulatory environment demands precision: data residency, audit trails and maker-checker controls are the baseline, not a feature. Most overseas AI tooling does not meet that bar, so we build to it from the first design session.

Quarterly reporting takes weeks
Data aggregation, MD&A drafting and compliance checks in one pipeline that runs overnight.
Portfolio data trapped in silos
A unified intelligence portal over fund administrator portals, legacy ledgers and spreadsheets, with natural-language query.
Document processing bottlenecks
OCR and structured extraction on your own infrastructure, producing pre-filled drafts for review.
Maker-checker friction
Dual controls embedded in the workflow itself, so entry and approval happen in one place with full audit trails.
Data sovereignty
Local LLM inference for sensitive documents: the data stays on your premises, and no API metering runs behind your back.
Legacy systems without APIs
Automation layered over spreadsheet workflows, email approvals and PDF chains. No rip and replace.
Multi-market complexity
Different fiscal years, reporting standards and languages handled natively across the region.
Talent constraints
Systems deploy in weeks, where hiring a specialist finance or operations role in Singapore takes months.

Our Systems in Action

Reporting pipeline: source data feeds AI processing, human review, then the filed package.
Fig. 1 — Quarterly reporting run
Intelligence portal architecture: encrypted sources into local inference, then a query and reporting layer.
Fig. 2 — Intelligence portal architecture
Two zones split by a boundary: cloud layer for interface, access control and filing output; your infrastructure for source documents, local inference and the audit trail.
Fig. 3 — Data residency boundary
2–3 weeks → overnight Quarterly reporting cycle, end to end. Read the memo
90%+ field accuracy Structured extraction from financial PDFs. Read the memo
68s → 17s Per document, measured on a four-page sample. Read the memo

Who We Work With

Family Offices & Asset Managers

Multi-asset portfolios spread across fund administrator portals and legacy ledgers. We build the unified layer: on-demand positions, reporting that looks forward rather than back, and answers in minutes.

Enterprises & SMEs

Finance and operations teams whose reporting, reconciliation and document intake still run on manual effort. We remove the manual steps and leave the controls exactly where compliance expects them.

Engagements start with a scoping workshop Working software in weeks Client identities are never published

Who We Are

We’re a two-person core. That’s intentional — small enough to move fast, experienced enough to know when to say no. We partner with specialists for delivery and keep the overhead low so we can invest in engineering quality.

Systems architect

Leon Oh

Builds the automation engines that run behind the scenes. Former finance practitioner who got tired of watching people do manual work.

Senior engineer

Dang Luong

Full-stack engineer. Turns system designs into working software, with a focus on reliability — these systems have to run without hand-holding.

Two engineers Singapore-based Delivery with named specialists No sales layer

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