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Success Stories

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Challenge

A digital-native business faced fragmented customer journey data across marketing, CRM, digital, contact center, and dealer ecosystems, with unexplained conversion drop-offs, inconsistent attribution, and no predictive visibility into which leads were likely to convert.

Solution

Hoonartek unified funnel events from impression to sale in Delta Lake, created a Golden Lead ID through identity resolution, built funnel KPIs and cohorts in Databricks SQL, and deployed MLflow for lead scoring and drop-off risk prediction with real-time anomaly alerting and Unity Catalog governance.

Results

10–20%

Higher lead-to-conversion rates through better funnel visibility

15–25%

Lower wasted marketing spend through smarter attribution

25–40%

Faster decision-making with near real-time funnel insights

Challenge

A retail loyalty platform faced manual invoice verification delays, growing invoice volumes with seasonal spikes, fraudulent and duplicate submissions, inconsistent image formats across submissions, and limited visibility into processing failures, all undermining loyalty point crediting and customer satisfaction.

Solution

Hoonartek built an AI-powered invoice processing pipeline combining OCR and LLM reasoning with a confidence layer, deterministic and fuzzy dedupe fraud checks, and automated downstream integration with loyalty systems via audit-ready APIs.

Results

~13,000

Invoices processed per month with peak-time scalability

~95%+

Extraction accuracy with 100% invoice coverage

~75%

Reduction in invoice processing time from hours/days to minutes

Challenge

A digital-native e-commerce platform struggled with fragmented personalization across channels, leading to inconsistent user experiences, low engagement, high decision-making effort for users, and an inability to scale AI-driven recommendations under privacy and governance constraints.

Solution

Hoonartek consolidated user signals into Delta Lake, built a governed User Preference and Context Profile using Unity Catalog, and leveraged LLMs, Vector Search, and MLflow to deliver context-aware, next-best-action recommendations with near-real-time personalization orchestrated across all business systems.

Results

10–18%

Higher engagement and conversion through personalized guidance

20–35%

Reduction in user effort and decision time

25-40%

Faster personalization cycles via real-time signals and feedback loops

Challenge

A logistics operator faced limited visibility into shipment disruptions across carriers, warehouses, and logistics partners, with manual exception handling creating slow response times, missed SLAs, and fragmented coordination between operations and customer service teams.

Solution

Hoonartek deployed Agentic AI to continuously monitor shipment milestones, carrier feeds, ETA changes, and warehouse events, enabling automated detection of exceptions and AI-driven root cause analysis with next-best-action recommendations – while keeping humans in control of critical decisions.

Results

25–35%

Reduction in shipment exception resolution time

10–18%

Improvement in on-time delivery performance

30–40%

Reduction in manual tracking effort for operations teams

Challenge

A marine logistics operator faced fragmented planning processes for route optimization, maintenance scheduling, crew rostering, and fuel management, with limited real-time visibility into vessel sensor data and fleet asset health.

Solution

Hoonartek built a cloud-based fleet intelligence platform on Snowflake, deploying ML models for predictive maintenance and fuel consumption and offering the solution as an internal tool as well as a SaaS product for third-party fleet operators.

Results

3X

Improvement in route planning efficiency and cost per nautical mile

5X

Reduction in safety and compliance incidents

30%

Uplift in port turnaround time, on-time delivery, and anchorage efficiency