Consult and build. One team, no handoff.
Where we go deepest: data & AI.
Our data and AI practice in detail. Each line is built around an outcome, and built to run in production.
Data engineering & data lakes
ERP, shop-floor, and IoT sources unified into one trusted, governed layer. Lineage built in from day one.
ERP-to-cloud ingestion
Direct OData, AppFlow, DMS, and Kinesis pipelines from SAP, Oracle, and WFX, covering SaaS, relational, and streaming.
Two-zone lakehouse
Raw and curated zones on S3 or ADLS, with Glue and Lake Formation for governance and cataloguing.
Warehouse & query layer
Redshift, Synapse, or Athena tuned for the performance-sensitive analytics that sit on top.
Governance & lineage
Security baselines, IAM, and lineage built in, not retrofitted under audit pressure.
Demand forecasting & inventory
SKU-level forecasts and automated replenishment, wired into the planning systems where the outcome lands.
New-SKU allocation
Parameter-based forecasts that fit subclass history to predict the first weeks of demand.
Daily demand sensing
DeepAR+, LightGBM, and ensemble models with regressors for stock-outs, footfall, price, and assortment.
Closed-loop replenishment
Forecasts wired straight into ARP and planning systems, so the number drives the order.
Working-capital impact
Tuned to the lever that matters: fewer stockouts, less inventory, fewer manual interventions.
Shop-floor & operational intelligence
OEE attribution, root-cause analysis, and preventive-maintenance triggers, built on the shop-floor data you already collect. No new hardware.
Real-time line monitoring
Critical KPIs across every line in near real-time, with custom machine-state definitions.
Root-cause attribution
OEE losses classified operational vs engineering, with severity scoring and alerts.
Preventive maintenance
Statistical-threshold triggers that replace reactive servicing before a line goes down.
Auto-insights
Anomaly, trend, and variance detection surfaced into engineering and operations playbooks.
Computer vision for quality
Defect classification at production speed, wrapping the cameras already on your line. No new hardware to install.
In-line defect detection
Classification at production speed across discrete and continuous lines.
Fabric & shade inspection
Texture, shade, and finish checks that catch what manual QC misses.
Wraps existing cameras
Models layered onto current infrastructure, with no hardware-replacement program.
MES integration
Results piped back into MES and quality workflows where action actually happens.
MIS modernisation & decision boards
Dozens of manual reports replaced by role-specific boards and exception alerts. Leadership sees only what moved.
Report consolidation
Sprawling manual reporting collapsed into a handful of outcome-based decision boards.
Exception-based alerting
Leadership sees only the metrics that deviated, via SNS, email, or chat.
One source of truth
A governed warehouse behind the boards, ending duplicated and conflicting reporting.
Cost-optimised
Incremental loads and off-hours scheduling cut both ETL time and cloud spend.
Multi-geography & scenario analytics
Margin attribution, pricing and tariff scenarios, and concentration risk, built for the decisions a CFO or MD owns.
Margin attribution
Profitability decomposed across countries, entities, channels, and products.
Tariff & pricing scenarios
Simulate duty, pricing, and trade-policy changes before they hit the P&L.
Trade-scenario modelling
AGOA-style and sourcing-shift scenarios modelled end to end.
Concentration risk
Customer and supplier concentration views for board and CFO oversight.
One system, from source to decision.
The lines above are not separate projects. They are stages of one architecture. Build the foundation once, and everything on top of it ships faster and cheaper.
Most of our case studies are some path through this diagram. The foundation is the leverage: seven separate analytics projects cost far more than the same seven built on one shared, governed layer.
Beyond data & AI, we build the rest too.
The same engineers behind our data and AI work also build the products, apps, and platforms around it. Fewer vendors, fewer handoffs.
Web & product engineering
From a one-page site to a full product with auth, payments, and dashboards.
Mobile & internal software
Native and cross-platform mobile apps, plus the internal tools that replace brittle spreadsheets and manual ops.
Cloud & infrastructure
Migrations to AWS, Azure, and GCP. Re-architecting legacy systems, CI/CD, observability, and cost-efficient infrastructure built to scale.
Strategy & market research
Technical strategy, architecture review, platform selection, and feasibility research, before a line of code is written.
Let’s build the thing you’re stuck on.
Thirty minutes with a principal. No decks, no sales script, just a straight read on whether we are the right team to ship it.