Solutions

Data Intelligence

ML pipelines, anomaly detection, demand forecasting, and real-time analytics integrated into your existing infrastructure.

What we build

Intelligence that runs on your data, in your environment

Most analytics projects stop at dashboards. We go further — building ML pipelines that actively detect anomalies, surface predictions, and trigger actions based on what the data shows, not what a human happened to notice.

The systems we build integrate with your existing data sources — databases, APIs, event streams — so intelligence lives where your operations already happen.

Anomaly detection

Statistical and ML-based detection of outliers in operational, financial, or sensor data.

Demand forecasting

Time-series models that predict inventory needs, staffing requirements, or demand patterns.

Real-time pipelines

Event-driven architectures that process and analyze data as it arrives, not in batch.

Semantic search

Vector embeddings and RAG pipelines that make unstructured data queryable and actionable.

Tech stack

What we use

Modeling
scikit-learnXGBoostPyTorchstatsmodels
Pipelines
CeleryApache KafkadbtAirflow
Storage
PostgreSQLRedisElasticsearchpgvector