ADAM

Q: More out-of-the box data sources.

Pre-configured ingestion and data merge routinesDirect retailer dataSyndicated sources (e.g., NIQ, Circana)Enrichment sources (e.g., leaflets, causal data)Internal ERP, DP and TPM dataEnterprise data platforms (e.g., Snowflake)

Q: Data reflecting reality – not the theory.

Data improvementAuto flagging: shift, add missing, delete cancelled promotions or change promo length)AI Baselines/ Modelling: baseline aggregation, new sub-categories, distribution changes, output validationAllocation: event, quantities, rates, cost spreading down to PPG/ event level, sell-out period alignment

Q: Richer data, to maximize business value.

Data-automated enrichment, computation, and validationIncrementality, forward buying, cannibalization, P&Ls and KPIsHarmonization & mapping, group by week x promo couple, hierarchy commercializationValidation: check & fine-tune AI models, spot anomalies and missing data, high-level evaluation, holistic auto-flagging

AI-ready data, no effort required.

Meet ADAM, XTEL’s augmented data management solution. ADAM takes, transforms, improves, generates, stores and serves data leveraging the business knowledge injected in its advanced algorithms and AI models – so you can focus on leveraging that information for competitive advantage.

Any data source, ready to use

XTEL has more experience loading and understanding industry data than any other provider, so that you don’t have to reinvent the data management wheel.

Enriched, corrected, categorized, transformed for business value

XTEL employs advanced techniques like data augmentation, anomaly detection, and automated data validation to create a reliable and accurate data foundation.

Integrated into your data ecosystem

XTEL’s Qubes seamlessly integrate with all major cloud-based data platforms (Microsoft Fabric, Databricks, Snowflake…) to help you build a single system of record for downstream data.

Top Trends for Consumer Goods CIOs in 2026

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XTEL ADAM

Augmented data management solution.

What you can do with ADAM

More out-of-the box data sources.

Pre-configured ingestion and data merge routines

Direct retailer data
Syndicated sources (e.g., NIQ, Circana)
Enrichment sources (e.g., leaflets, causal data)
Internal ERP, DP and TPM data
Enterprise data platforms (e.g., Snowflake)

Data reflecting reality – not the theory.

Data improvement

Auto flagging: shift, add missing, delete cancelled promotions or change promo length)
AI Baselines/ Modelling: baseline aggregation, new sub-categories, distribution changes, output validation
Allocation: event, quantities, rates, cost spreading down to PPG/ event level, sell-out period alignment

Richer data, to maximize business value.

Data-automated enrichment, computation, and validation

Incrementality, forward buying, cannibalization, P&Ls and KPIs
Harmonization & mapping, group by week x promo couple, hierarchy commercialization
Validation: check & fine-tune AI models, spot anomalies and missing data, high-level evaluation, holistic auto-flagging