Nalu AI

ABOUT

Demand intelligence
that actually runs in production.

Nalu AI is an ML system built together with the customer — for demand planning and sales intelligence, on their infrastructure, for their data.

WHAT NALU AI IS

Not SaaS. Not a consulting project.

Nalu AI is a demand intelligence platform tailored to each customer. Forecasts, SCM recommendations and AI reports run on the customer's own infrastructure — no shared data, no external cloud, no black box. The platform is built on proven technology from production use: LightGBM and Temporal Fusion Transformer for forecasts, DuckDB for analytical queries, FastAPI as the API layer, Docker for deployment. What works stays — what matters in mid-market gets added.

Not generic.

Every implementation learns the customer's SKUs, seasonalities and ERP quirks — no standard templates.

Not dependent.

On-premise by design. No cloud lock-in, no subprocessor chain, no hidden APIs.

Not bloated.

One Docker Compose stack per customer. What is not needed does not run. What runs, runs fast.

Nalu ist Hawaiianisch für Welle — entstanden während eines Sabbaticals auf Hawaii, wo nebenbei ein Dive-Shop-System entwickelt wurde.

METHOD

How a project runs.

From the first conversation to production — typically a few weeks, depending on data quality and ERP complexity.

  1. 01

    Discovery

    Short workshop with the customer: ERP system, data structure, business logic, biggest pain points. Out of it comes a config.yaml — the heart of every implementation.

  2. 02

    Connector & Data pipeline

    Integration with SAP, S/4HANA, Dynamics, Proalpha, SQL or CSV — read-only, no changes to the source system. Data quality is validated automatically, gaps detected.

  3. 03

    Model training

    ML models are trained on the customer's real data. Forecast accuracy is transparently measured (MAPE, coverage) before anything goes into production.

  4. 04

    Deployment

    Docker stack runs on the customer's server. RBAC, 2FA, audit log and SSL are standard. Training for purchasing, planning and sales.

  5. 05

    Operations & maintenance

    Weekly retraining, automatic reports, monitoring. Updates, new features and support are part of the license — not an upcharge.

TECHNOLOGIE

ML & Forecasting
LightGBMPyTorch/TFTSHAPMLflowscikit-learnAnomaly DetectionOllama
Daten & ETL
DuckDBPostgreSQLParquetSAP R/3PyArrowSQL ServerDagster
Backend
PythonFastAPIFlaskCeleryRedisPydanticSQLAlchemyEntra ID SSO
Deployment
DockerNginxReactTypeScriptGitHub ActionsPrometheusGrafana
Visualisierung
RechartsDeck.glLeafletGeoPandas

PRINCIPLES

Four things Nalu AI measures itself against.

Data stays with the customer

On-premise is not a feature, it is a requirement. No cloud dependency, no subprocessor chain, no external model APIs.

No hype, just results

Forecasts, alerts and reports the team can use tomorrow. No generic AI buzzwords — confidence intervals, SHAP explanations, honest numbers.

Maintainable over clever

Deterministic pipelines, documented configuration, readable models. Whoever has to touch the system in three years should not have to guess.

Mid-market understands mid-market

Tight resources, legacy systems, pragmatic decisions. The platform is built for that — not for enterprises with their own data team.

Learn more.

No form. No funnel. Just an email.

aloha@nalu-ai.com

Typical investment: from €50,000 one-time, from €5,000/month — always individually calculated.