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Aru Labs Pte. Ltd. Doc. AL-001 Rev. 2026.09 Singapore Accepting engagements

Applied AI engineering for business

Enterprise software, engineered at 100×

Aru Labs designs, builds and operates business-critical B2B applications with an AI-native engineering method. The rigor of a large firm, in a fraction of the time.

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Fig. 1Unit of work
Engineers001
Output×000
One engineer, directing AI systems. One hundred units of delivered work.
Headquarters
Singapore
Focus
B2B applications
Method
AI-native engineering
Accountability
Senior engineers, named
§01 Thesis

The unit of work has changed.

For fifty years, software has been built at the speed of typing. Teams grew to go faster, and slowed down as they grew.

We rebuilt the process around AI systems that write, test and document code, directed by senior engineers who specify, review and own every line. The result is software delivered with the discipline of a regulated industry, at a pace that changes what is worth building.

Not more engineers. Better leverage.
A symmetrical white clean-room corridor under a grid of ceiling lights
Fig. 2Controlled environments produce predictable results.
§02 Capabilities

What we build.

Systems that businesses run on. Specified precisely, delivered continuously, documented as they are built.

  1. CAP-01

    Internal platforms

    Operational systems, back offices and admin tooling your teams rely on every day.

  2. CAP-02

    Workflow automation

    Multi-step processes, approvals and document handling, automated end to end.

  3. CAP-03

    AI agents and copilots

    Domain-specific assistants integrated with your data, permissions and audit trail.

  4. CAP-04

    Data systems

    Pipelines, warehouses and reporting that turn operational data into decisions.

  5. CAP-05

    Client-facing products

    Portals, dashboards and applications for your customers and partners.

  6. CAP-06

    Legacy modernization

    Systematic migration of ageing systems, with parity tests at every step.

§03 Method

A controlled process.

Four phases, run continuously. Machines do the volume. People do the judgment.

P1

Specify

Requirements, constraints and acceptance criteria, written as an executable specification.

Output
Specification, architecture record
Owner
Engineer + client

P2

Generate

AI systems produce implementation, tests and documentation against the specification, in parallel.

Output
Working increments
Owner
AI systems

P3

Verify

Senior engineers review every change. Automated suites confirm behaviour against the specification.

Output
Test reports, review log
Owner
Engineer

P4

Operate

Deployed to your infrastructure or ours, monitored, and maintained to a defined service level.

Output
Runbooks, service levels
Owner
Aru Labs
§04 Comparison

Same standards. Different physics.

What changes when the cost of writing code approaches zero, and what doesn't.

ParameterConventional deliveryAru Labs
TeamScales with scopeSmall, senior, fixed
First releaseQuartersWeeks
DocumentationWritten afterwards, if at allGenerated with the code
Test coverageNegotiatedSpecified up front
Change requestsRe-scoped and re-pricedAbsorbed into the specification
AccountabilityDiffused across the teamA named engineer per system
Macro of a silicon wafer's grid of dies on a white surface
Fig. 3aPrecision at the smallest scale.
White modular blocks arranged on a grid, one slightly raised
Fig. 3bComposed from verified parts.
§05 Standards

Built for scrutiny.

Speed is only useful if you can trust what arrives. These are the controls on every engagement.

Human accountability

Every change is reviewed and owned by a named engineer. Nothing ships unread.

Data boundaries

Your data stays within agreed boundaries. Access is scoped, logged and revocable.

Traceability

Specifications, decisions and changes are recorded, versioned and auditable.

Tested by default

Acceptance criteria become automated tests before implementation begins.

A symmetrical white data center aisle
Fig. 4Operated to a defined service level.
§06 Engagements

Three ways to work with us.

Each begins with a specification, and a fixed understanding of what done means.

E-01

Build

A new application, from specification to production.

Suited to
New products, internal platforms

E-02

Modernize

An existing system, migrated and rebuilt without disrupting operations.

Suited to
Legacy estates, re-platforming

E-03

Operate

Continuous development and maintenance of systems already in service.

Suited to
Long-running platforms
§07 Company

An applied AI engineering company.

Aru Labs is headquartered in Singapore. We work with operators: the people responsible for systems that have to work on Monday morning.

Entity
ARU LABS PTE. LTD.
Registered in
Singapore
Address
68 Circular Road, Singapore
A precision laboratory instrument on a white bench
Fig. 5Instrumented, measured, repeatable.

§08 — Contact

Specify the system.We'll build it.

A briefing covers your requirements, constraints and a proposed path to production. NDA on request.

Request a briefing