The case

zeb has built a migration and modernization factory on Databricks. This is not a "we did two good projects" submission it is a submission on the strength of a practice, engineered for repeatability and measured in volume.

The award criteria call for successful migrations, modernization of analytics and AI workloads, and customer benefits in performance and agility. Across 27 accounts we are answering all three at scale, while maintaining a consistent engineering pattern that makes each new engagement faster than the last.

Source systems displaced

The repeatable engineering pattern

Every migration follows a disciplined two-part structure: logic conversion (PL/SQL, T-SQL, stored procedures, Informatica mappings, Spark SQL) paired with data model remapping to a medallion-architecture Delta Lake governed by Unity Catalog from day one. Orchestration lands on Databricks Jobs with SDP-ready pipeline patterns built in, so customers inherit a platform their own teams can extend without us.

Marquee accounts and outcomes

ITS Logistics $259K combined consumption through DW migration; trailer optimization activated on landed data. MaintainX $120K FY26 Databricks lakehouse infrastructure build supporting workforce management, predictive maintenance, and product/process traceability. Flipp $110K cumulative consumption via UC migration enabling personalized retail recommendations and promotional-effectiveness analytics. McCain Synapse migration paired with production S&OP implementation spanning demand hierarchy, potato inventory, and distribution visibility. Canadian Tire combined UC and Synapse migration driving omnichannel customer analytics, inventory optimization across store network, and predictive pricing.

The case

zeb runs a production lakehouse delivery practice on Databricks 21 engagements deep. The submission is not about one showcase build; it is about depth of pattern and the fact that our customers renew into managed services because the work delivered in year one earns it.

Multi-year managed-service anchors

Amalgamated Bank has consumed over $108K combined across FY26 and prior years on a managed service covering lead prioritization, customer 360, CFO and treasury analytics, RFP and proposal management, and hyperpersonalization. FlexXray is in its third managed-service year, unifying QuickBooks, Salesforce, and warehouse data into a single analytics substrate spanning financial reporting, inventory optimization, and customer intelligence. BPM runs a 10-month managed service covering customer 360, hyperpersonalization, invoice reconciliation, and cash-flow optimization.

FY26 net-new build momentum

Fluent ($38K) and Anza Mortgage Insurance ($24K) completed Databricks-on-AWS jumpstarts activating lead prioritization and customer 360. Watlow ($21.6K) stood up a lakehouse supporting order fulfillment, predictive maintenance, and digital-twin use cases. Couchbase, Nift, NORC, EvolvCo, and Cenevo landed lakehouse builds with repeatable customer-360 and segmentation patterns. Metronome's lakehouse supports workforce management and predictive operations for a modern billing platform. Zachry's phase-two spans FP&A, project value tracking, workforce utilization, and HR analytics with policy context.

Why the platform sticks

The technical pattern we run is consistent across all 21 engagements: Delta Lake with medallion architecture, Unity Catalog governance from day one, Databricks SQL for transformation, and AI/BI Dashboards or Genie where customers want natural-language access. That consistency is the reason customers land on a platform their teams understand and extend not a bespoke build dependent on us in perpetuity.

The case

zeb has built a meaningful Digital Native Business practice on Databricks, serving 11+ DNB customers across the exact subverticals Databricks targets for this category. The roster spans AI-native software (Afresh, MaintainX), ad-tech and content intelligence (ShareThis), data enrichment (People Data Labs), modern fintech and platform infrastructure (Metronome, Couchbase, Cenevo), and mobility (Nauto, Route).

AI-native software anchors

Afresh the AI-native fresh-food inventory platform runs on a $94.8K FY26 managed service covering automated customer onboarding, KYC, hyperpersonalization, process optimization, and demand forecasting. MaintainX, a mobile-first maintenance software company, stood up a $120K Databricks lakehouse for workforce management, product and process traceability, and predictive maintenance the exact use cases their own customers need to see working inside MaintainX.

Ad-tech and data intelligence

ShareThis migrated content-recommendation and audience-segmentation workloads ($43.5K cumulative). Nauto migrated driver-behavior analytics and accident-prediction workloads ($58.9K cumulative). People Data Labs anchored a data-intelligence and enrichment workload at $186K cumulative.

Modern fintech and platform infrastructure

Metronome's modern billing platform runs predictive operations and workforce management on a Databricks lakehouse. Couchbase's DWH implementation supports lead prioritization and customer 360. Cenevo's jumpstart activated customer 360 and hyperpersonalization. Flipp modernized personalized retail and promotional-effectiveness analytics via UC migration ($110K cumulative). Route brought supply-chain visibility and predictive maintenance off Snowflake onto Databricks ($20K FY26).

The case

zeb's AI practice on Databricks is anchored by two production engagements and one platform-native product. The deeper argument: AI is embedded in nearly every engagement across our portfolio because our default architecture assumes AI workloads will be activated on the landed data.

Production AI engagements

Afresh AI-native fresh-food inventory company runs a $94.8K FY26 managed service where zeb delivers automated customer onboarding, KYC, hyperpersonalization, process optimization, and demand forecasting. All built on Databricks primitives so the AI work lives on the same governed substrate as the customer's operational data. Grant Street Group $48K FY26 DWH implementation including customer onboarding and process-traceability AI workloads engineered for auditability from the outset.

DocumentIQ — a Databricks-native AI product

DocumentIQ is a Databricks-powered contract redlining solution purpose-built for the Commodities, Metals, Energy, and Gas (CMEG) vertical an industry where contract complexity, regulatory exposure, and counterparty risk make every clause consequential. It is not a generic LLM wrapper. DocumentIQ is engineered on the Databricks Data Intelligence Platform so retrieval, evaluation, governance, and model serving all live on the same lakehouse as the customer's analytics and compliance data. Golden-template behavior, confidence thresholding, and document-size handling were scoped as first-class V1 decisions, not afterthoughts.

AI embedded across the portfolio

Beyond the two anchor engagements, AI use cases show up in nearly every migration and DWH delivery summary because our architecture assumes it. Mode is activating agentic customer support. Mesirow is building trading execution and portfolio management AI. Cipher Mining runs predictive maintenance for mining infrastructure. BCIM automates claims processing and fraud detection. Central Insurance runs ML-driven proactive actions and ML-based segmentation. Cineplex runs predictive analytics for demand forecasting and customer journey optimization.

The case

zeb's Databricks practice is not "early in the journey" by tenure it is early in the journey by where the curve is heading. The data shows a partner that started small in 2023 and compounded faster than any comparable C&SI in the same window. Databricks Partner Manager-validated metrics: $3.1M in DBU consumption across 75 joint customers, 33 live use cases producing $140K, and 107 use cases in pipeline at $852K with 16 partner-sourced.

The ramp curve

2 accounts in 2023. 9 in 2024. 28 in 2025. 14 net-new customers already in FY26 with the year not half over. That is roughly 14× scale in 24 months and the curve is still steepening. FY26 consumption from 2025-started accounts alone is $518K, proving customers expand after landing rather than staying single-engagement deals.

Why the velocity is repeatable, not lucky

We productized the delivery pattern early. Every engagement runs the same stack: Delta Lake with medallion architecture, Unity Catalog from day one, Databricks SQL or PySpark for transformation, AI/BI Dashboards and Genie for consumption, MLflow-ready AI workloads where relevant. That consistency is why a small focused team can stand up a customer lakehouse in weeks and convert it into a managed-service or expansion engagement inside 12 months.

FY26 marquee new logos

Canadian Tire (UC + Synapse migration; omnichannel 360, inventory optimization, predictive pricing). McCain ($60K FY26; Synapse migration plus production S&OP). Hexion ($16K FY26; FP&A, plant maintenance, supply chain). Mode ($20K FY26; agentic customer support, demand forecasting, predictive maintenance). BCIM ($14K FY26; Azure SQL MI to Databricks; claims automation, fraud detection). Central Insurance ($13K FY26; ML-driven proactive actions, ML segmentation). Plus Lululemon, CNRL, PFG, Gibraltar, Metronome, Petronas, Stefanini.

Why "Emerging" is the right frame

Emerging Partner of the Year should reward the partner whose curve is steepest, whose pipeline is deepest, and whose delivery pattern is most ready to scale into the next year. zeb is that partner measured in joint-customer count, DBU consumption, pipeline depth, partner-sourced contribution, and the breadth of verticals already covered.