Reporting is slow or disputed
Teams spend more time reconciling numbers than deciding what to do next.
Malaysia-based data & automation consultancy
Modernise critical data. Automate the work.
Senior-led data engineering, migration, intelligence, and automation for organisations with complex operations.
Engineers with 20+ years of industry experienceMalaysia · Hybrid · Remote
From problem to production
DiscoverUnderstand workflow, data and constraints
EngineerDesign platforms, integrations and controls
DeliverDeploy, hand over and improve
Operational outcomes
Dependable dataFaster operationsMeasurable outcomes
Built for complex operations across
SME operationsBanking & financial servicesGovernment & GLCsOil & gasAutomotive & manufacturingWhat we deliver
Services shaped around the problem—not a product catalogue.
We work from the operating outcome backward, then use the right data, integration, reporting, and automation tools for the environment.
01
Data Platforms & Engineering
Build dependable data foundations that connect operational systems to trusted analytics and AI-ready workflows.
Explore capability 02Migration, Modernisation & Performance
Move critical data and workloads with controlled validation, measurable performance, and less operational disruption.
Explore capability 03BI & Decision Intelligence
Turn governed data into reporting, dashboards, and decision support that teams can understand and trust.
Explore capability 04Intelligent Automation
Reduce repetitive work by combining workflow redesign, RPA, document understanding, APIs, and practical AI.
Explore capability 05Custom Data & Operational Platforms
Purpose-built multi-tenant and internal systems for specialised workflows, data products, and operational needs.
Explore capabilityWhere clients get stuck
The warning signs are usually operational.
A critical platform must change
Legacy workloads, unclear dependencies, and weak validation make migration risky.
Manual work no longer scales
People rekey, reconcile, route, and chase information across systems every day.
AI ideas do not reach production
Use cases remain demos because data, integrations, ownership, and adoption were never designed.
Evidence from delivery
Delivery scenarios, measured and explained.
Our client agreements require anonymity. These examples show different operating problems, Monic’s engineering responsibility, delivery scale, and verified outcomes.
Automotive · workflow automation
Reducing a multi-day payroll document process to one hour
Automated generation and delivery of password-protected employee documents from an established enterprise workflow.
3 daysprevious cycle
~1 hourautomated cycle
2000+of employees
Insurance · data engineering
Redesigning ETL workloads for at least 50% better performance
Re-engineered established insurance data-processing jobs to improve throughput by at least 50%, stability, maintainability, and production operability.
50%+performance improvement
Paralleljob redesign
Improved stabilityproduction operability
Power & utility · business intelligence
Building management dashboards across utility departments
Designed the data marts, ETL flows, and IBM Cognos dashboards needed to support management reporting across multiple business units.
3department projects
Data martsreporting foundation
VP-levelreporting
Enterprise data platform
Modernising a large-scale data platform for production migration
A controlled migration of hundreds of ETL workloads and enterprise data assets from a legacy data lake to HPE Data Fabric Software.
500+ETL workloads
500+tables
100 TBdata estate
Insurance · change data capture
Implementing CDC for near-real-time data ingestion
Established full-load and incremental data flows from legacy systems, with data-quality remediation, testing, monitoring, and production support.
Oracle + DB400source systems
Full + deltaload patterns
Near-real-timedownstream updates
Credit bureau · data replication
Replicating legacy DB2 data into a big-data platform in real time
Implemented production replication and streaming from an AIX DB2 estate into modern DB2, Cloudera Hadoop, and AWS targets.
AIX → Red HatDB2 migration
2production environments
DB2to Hadoop and AWS
Focused AI & automation pilot
Forward-Deployed AI & Automation
Turn a high-value AI or automation idea into a production workflow.
One accountable lead engineer works alongside your business and technology teams, backed by Monic data, automation, and software specialists.
Explore the FDE pilotGoverned enterprise knowledge & RAGIntelligent document workflowsAgentic workflow automationData and analytics agentsMigration and integration accelerators
How we work
Senior-led from discovery through adoption.
Discover
Understand the workflow, data, users, risks, and measure that matters.
Design
Define the architecture, delivery boundary, validation, and adoption path.
Deliver
Build, integrate, test, migrate, and prepare the solution for production.
Adopt
Enable users, monitor outcomes, transfer knowledge, and improve what runs.
Practical thinking
Useful answers before a sales conversation.
AI & automation · 11 min read
RAG, AI agents and RPA: choosing the right automation approach
A practical decision framework for choosing governed retrieval, AI-led judgement, API automation, RPA, or a controlled combination.
Read insightData engineering · 10 min read
When change data capture becomes a modernisation problem
A production checklist for CDC covering snapshots, ordering, deletes, schema change, recovery, reconciliation, monitoring, and ownership.
Read insightMigration · 10 min read
Eight questions to answer before migrating a critical data platform
A readiness framework for inventory, dependencies, validation, security, performance, cutover, rollback, and operational ownership.
Read insightStart with the work
Bring us the operational problem.
We will help determine whether the right next step is data engineering, migration, automation, or a focused AI pilot.