Retail Data Integration for CPG: AI-Powered Third Party Data Operations
DS Stream designs, builds and operates AI-driven data integration platforms that automatically collect, harmonize and govern POS, distributor and syndicated market data from hundreds to thousands of sources — replacing error-prone manual pipelines with intelligent, self-healing automation that delivers trusted data at scale.
Retail Data Integration for CPG: AI-Powered Third Party Data Operations
DS Stream designs, builds and operates AI-driven data integration platforms that automatically collect, harmonize and govern POS, distributor and syndicated market data from hundreds to thousands of sources — replacing error-prone manual pipelines with intelligent, self-healing automation that delivers trusted data at scale.
Retail Data Integration for CPG: AI-Powered Third Party Data Operations
Automate 70–85% of CPG third party data operations and onboard new sources up to 70% faster — with zero disruption to existing data flows.
AI-Driven Data Integration: Agentic Automation for CPG Data Operations
Agentic AI Architecture
Task Expert Agents for onboarding, mapping, quality, auto-remediation and monitoring
AI Anomaly Detection
24-48 hour early warning before data issues impact downstream systems
Automated PII Masking
Enforces data compliance across all sources
Self-Healing Pipelines
75-95% automated remediation without human intervention
AI-Driven Data Integration: Agentic Automation for CPG Data Operations
Foundation (Weeks 1–4)
Databricks platform configuration, auto-provisioning infrastructure, data architecture design and PoC validation with 5 test sources fully automated.
Intelligent Ingestion (Weeks 5–8)
TEA-Onboard and TEA-Mapping agents deployed, auto-code generation validated across 5 retailer format types.
Quality and Compliance (Weeks 9–12)
TEA-Quality and TEA-AutoFix deployed with ML anomaly detection delivering 24-48 hour early warning.
Autonomous Operations (Weeks 13–16)
Full agent suite live including TEA-Resolve, TEA-Comms, TEA-Monitor and TEA-Config.
AI-Powered Migration (Weeks 17–30)
All existing sources migrated in four tranches using AI-powered migration that learns from each tranche.
How We Work: From Discovery to Production in 30 Weeks
Meet our results
What our clients say
Paweł Korczak
CEO, Iliada
Gen Yang
Data Science Manager, Kpler
Sandra Lemańska
Category Manager, Lorenz Polska
Selected Clients
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Business Impact Metrics
30–50% total cost of ownership reduction over five years compared to manually scaled data operations
Business Impact: Quantified Outcomes from AI-Driven Retail Data Integration
Cost Reduction
30–50% reduction in telephony and infrastructure costs by moving from legacy lines to cloud VoIP and SIP.
Retailer Onboarding Speed
70% faster retailer and distributor onboarding removing data operations as a constraint on partnership strategy
Issue Resolution Speed
95% faster issue resolution through automated anomaly detection, root cause analysis and self-healing remediation
Error Rate Reduction
Error rates reduced from 5–10% to under 1% through ML-powered validation, format detection and automated correction across all ingested data
Compliance Assurance
Zero compliance violations through automated PII masking enforcing global privacy regulations consistently across every source and every load
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Architecture and Technical Building Blocks
Databricks Foundation
Databricks Lakeflow for end-to-end pipeline orchestration with auto-scaling and built-in observability
Unity Catalog for centralized metadata management, access control, data lineage and audit logging
Delta Lake for ACID transactions, time travel and efficient incremental processing
Smart Model Routing
Reduces AI compute costs by 40–50%
Optimizes model selection based on task complexity
Multi-Protocol Ingestion
Supports SFTP, REST APIs, cloud storage (S3, Azure Blob, GCS)
EDI networks and email attachment parsing
Real-time streaming ingestion alongside batch processing
Zero-Disruption Migration
Existing pipelines continue operating while new AI-powered pipelines are validated in parallel
Cutover only after full validation
Let’s talk and work together
We’ll get back to you within 4 hours on working days (Mon – Fri, 9am – 5pm CET).
Service Delivery Partner
Our AI agents automate 80–90% of configuration that standard ETL requires manually — and adapt automatically when sources change.
Unlike generic tools, it includes CPG-specific harmonization logic built in
AI agents automate 80–90% of that work
Adapts automatically when sources change
Yes — built on Databricks, it connects natively with Snowflake, Synapse, BigQuery, Redshift, Tableau, Power BI and Looker via standard APIs and SQL.
Four weeks, 5 real sources from your environment, fixed price of $25–30K credited toward full implementation.
Four weeks duration
5 real sources from your environment
Fixed price of $25–30K
Credited toward full implementation
Delivers a working prototype and validated business case before any further commitment
ML detects structural changes within hours — common changes are corrected automatically, breaking changes trigger prioritized alert with recommended remediation.
ML detects structural changes within hours
Common changes (column additions, renamed fields, date format shifts) corrected automatically
Breaking changes trigger prioritized alert with recommended remediation
Typically resolved in hours not days
Scales to 1,500+ sources with near-linear cost growth — a 600–1,000 source environment runs on ~$1M/year in infrastructure and support.
Scales to 1,500+ sources with near-linear cost growth
600–1,000 source environment runs on ~$1M/year in infrastructure and support
Operated by 2–3 FTE versus 8–10 FTE for manual operations at the same scale
PII masking is applied at ingestion enforcing GDPR, CCPA, LGPD and PIPL across every source with zero compliance violations in production deployments.
PII masking applied at ingestion
Enforces GDPR, CCPA, LGPD and PIPL across every source
Data residency controls and immutable audit trails built in
Zero compliance violations in production deployments