Services
What we do
We build the layer between raw data and business decisions: platforms your teams operate themselves, and models that run reliably in production.
Low-code data platforms
Self-service analytics workspaces and internal tools on the Instap low-code platform — your analysts configure dashboards, pipelines and reports without writing code, while we own the engineering underneath.
Time-series & data engineering
Ingestion, storage and processing of high-volume time-stamped data — sensor streams, device telemetry, transactions — with two-way device connectivity: we read from your equipment and send commands back, closing the loop between data and action.
Forecasting, ML & AI
Demand forecasting, anomaly detection and predictive models that don’t stop at a dashboard — they trigger alerts, adjust setpoints and automate responses, validated with reproducible backtests.
MLOps & managed operations
Deployment, monitoring, retraining and model governance. We keep models accurate as your data drifts — on our infrastructure or on-premise where data residency demands it.
Process
How we work
Step 1
Discovery
We audit your data sources, quality and history — and define what the system must predict or automate, in measurable terms.
Step 2
Design
Data architecture, model selection and interface — agreed and prototyped before full build, with accuracy targets set up front.
Step 3
Delivery
We don’t build from scratch. Delivery runs on the Instap low-code platform for time-series data, so a clickable prototype is in your hands within days, not months. From there we iterate on it — backtested models and versioned pipelines, validated against real data before release.
Step 4
Operation
Monitoring, drift detection and scheduled retraining keep forecasts accurate as your business — and your data — change.
About
Software for data where there is no room for error
Instap is a Polish technology company with a track record of building systems that process mission-critical data. We work where reliability and data security are requirements, not features — which is why we support on-premise deployment and full data residency. One team carries each project from discovery through production operation.