Infrastructure-as-code, CI/CD, and observability built right from day one — so the platform doesn't slow the product down later.
What we deliver
Terraform / Pulumi infrastructure-as-code for AWS, GCP, or Azure — composed as reusable modules with per-environment overlays (dev / staging / prod) and promotion paths.
Deployment patterns fitted to the workload — ECS / Fargate, Kubernetes (EKS), or serverless (Lambda / Cloud Run) — chosen with the cost and ops trade-off in writing, not by default.
Singapore-Gov-aware architecture — GCC 2.0 / IM8-aligned VPC, IAM, and logging baselines for workloads that have to clear procurement security reviews.
Chaos and fault-injection drills — quarterly exercises against staging covering instance kill, dependency outage, and clock skew, with recovery times documented.
Backup and disaster-recovery drills documented and tested quarterly.
SLO dashboards and on-call runbooks for every paging alert.
When this fits
Your engineering team wants production-shaped infrastructure from day one, not bolted on later.
You're growing past a single instance and need to scale without a separate DevOps hire.
You need to demonstrate compliance and audit readiness to procurement teams.
Proven in practice
Reference builds from our own work that exercise this capability end to end.
Healthcare — hospital medical affairs
Clinical Education Operations Platform
The problem
Multi-institution clinical education ran on spreadsheets and email — manual tutor matching, untracked teaching hours, and sensitive trainee documents processed by hand. None of it was auditable, and student data crossed institutional boundaries it shouldn’t.
What we built
A unified platform for a hospital group’s clinical-education operations — managing students, tutors, and teaching-hour billing across multiple institutions, with AI-assisted document processing and matchmaking.
▸Three-tier LLM orchestration (Claude Haiku / Sonnet / Opus) routed per task class, with per-request and per-institution daily cost ceilings enforced in Redis.
▸Six-stage document pipeline that tokenises Singapore NRICs before any AI call, then routes by confidence — auto-commit above 0.90, human review between 0.70 and 0.90, blocked below.
▸AI-assisted matchmaking and a clinical-curriculum RAG that retrieves then LLM-re-ranks learning objectives, with every model output schema-validated.
▸Per-institution row-level security enforced in Postgres via a per-request session GUC, isolating tenants at the database layer.
▸PII-masked, append-only audit logging — every payload redacted and tenant-scoped before it is written.
NestJS 11
Next.js 15
PostgreSQL 16 + pgvector
Prisma
AWS Bedrock
BullMQ / Redis
Public sector — HR & recruitment
Multi-Tenant Recruitment Platform (Gov-Cloud)
The problem
Government hiring is slow, manual, and spread across disconnected tools — while strict data-isolation and in-country residency rules rule out most off-the-shelf recruitment platforms. Recruiters drown in resume screening that AI could triage.
What we built
A multi-tenant applicant-tracking SaaS for government agencies on government commercial cloud, with in-region AI for resume parsing and semantic candidate search.
▸Hard tenant isolation: a per-tenant database connection plus per-tenant KMS key aliases, with separate keys for general data, interview notes, and exports.
▸Enterprise SSO implemented end-to-end — SAML 2.0, OIDC (PKCE), SingPass NDI, and SCIM 2.0 directory sync — with SMS OTP and step-up MFA on sensitive actions.
▸In-region AI on Bedrock — resume parsing, semantic candidate search, and interview-note summarisation — each gated by a DLP scanner (NRIC / FIN / passport / contact patterns) before any model call.
▸Dual-control bulk export: a second approver and a step-up token are required, releasing a 15-minute presigned, tenant-key-encrypted download.
▸Fully Terraform-provisioned (17 modules) across multi-AZ, with a WORM audit bucket (S3 Object Lock, COMPLIANCE mode) and UUIDv7 time-ordered audit rows.
FastAPI
Next.js 15
PostgreSQL 16 + pgvector
Terraform
AWS GCC 2.0
AWS Bedrock
Education — school administration
School Operations & Timetabling SaaS
The problem
Building a school timetable by hand takes weeks and still produces clashes, and covering a sudden teacher absence means hours of frantic phone calls — with no guarantee the cover load is shared fairly.
What we built
A multi-tenant SaaS for school timetabling, relief-teacher planning, and mobile attendance, powered by a constraint-solving scheduling engine.
▸An OR-Tools CP-SAT solver generating clash-free timetables — enforcing teacher, room, and class non-overlap plus full curriculum coverage, while respecting teacher qualifications.
▸Automated relief-teacher allocation: approving a leave writes a transactional outbox event a worker drains within seconds to a solver that optimises for teaching continuity and fair workload balance.
▸Privacy-preserving mobile attendance (React Native / Expo): the on-campus check is computed on-device by haversine distance and only a boolean is sent — raw coordinates are never persisted.
▸Database-per-tenant isolation with per-tenant KMS keys; the scheduling engine connects read-only under a least-privilege, RLS-scoped role.
▸Transactional outbox (at-least-once, SELECT … FOR UPDATE SKIP LOCKED) and an append-only audit trail that HMACs the actor identity under a per-tenant key.