Data & AI
Turn Your Data into Decisions
A manufacturing client was making production decisions based on gut feel, sitting on 5 years of untouched sensor data. We built a real-time predictive maintenance dashboard — equipment downtime dropped 60% in Q1.
0%
Avg Downtime Reduction
0.2M+
Waste Eliminated ($)
0+
Models Deployed
0B+
Records Processed
Our Process
From Raw Data to Real Impact
Data Audit
We map your data sources, identify quality issues, and define the business metrics worth predicting. Most clients are surprised by how much usable data they already have.
Model Development
ML engineers build and validate models on your actual data — not synthetic benchmarks. Every model is interpretable and tied to a specific business decision.
Deploy & Monitor
Production-grade pipelines with drift detection and scheduled retraining. We maintain what we build — models degrade, and we keep them sharp.
Real-World Results
How an FMCG company eliminated $1.2M in annual inventory waste
A consumer goods company was producing to historical averages and losing $1.2M per year to overstock write-offs and emergency restocking. Their ERP had three years of sales data — untouched and unanalysed.
We built a demand forecasting model that ingested sales history, regional promotional calendars, and weather data. The model predicted weekly demand per SKU per region with 89% accuracy. In the first year, overstock write-offs dropped 62% and emergency restocking costs fell by $340k.
“We went from monthly Excel reports to real-time dashboards the team actually uses. The ML demand model alone saved us over a million dollars.”
— VP Operations, FMCG company
What We Build
From data pipelines to production ML models — end-to-end data engineering and AI that generates measurable business value.
- Data warehouse & lakehouse design
- ETL/ELT pipeline engineering
- Business intelligence dashboards (Power BI, Looker)
- Machine learning model development
- Natural language processing & LLM integration
- Real-time streaming analytics
- Demand forecasting & predictive modelling
- Data governance & quality frameworks
“We had data scientists internally but no data infrastructure. Intrivik built us a lakehouse that consolidated six disparate systems into one queryable source of truth. Our analytics team went from spending 60% of their time on data cleaning to spending 80% on actual analysis.”
Nadia Parveen
Head of Data, logistics company
What could your data be telling you?
A 30-minute data discovery call will show you what insights are hiding in your existing systems — and what a pilot project would look like.
Book a data discovery call