Proven at Enterprise Scale

Every case study represents a real engagement with measurable impact. No hypotheticals, no generic success stories.

Proven at Enterprise Scale

Real engagements. Measurable outcomes. Enterprise clients who raised the bar.

All Case Studies
Pharma · Governance

Enterprise Governance Modernization

Challenge

A global pharmaceutical company had fragmented data governance across 12 business units, creating compliance risk and slowing clinical data access by weeks.

Solution

Designed and deployed a unified governance framework on Unity Catalog with automated policy enforcement, role-based access, and end-to-end lineage tracking.

92%
Reduction in access request latency
100%
GxP audit trail coverage
14→2 days
Data access provisioning
Databricks Unity CatalogAWSPythonTerraform
Financial Services · AI

AI Knowledge Platform

Challenge

A tier-1 investment bank needed to surface institutional knowledge across 40TB of internal research documents, enabling analysts to query complex financial data in natural language.

Solution

Built a production RAG architecture with multi-modal vector search, fine-tuned retrieval models, hallucination guards, and full audit logging for compliance.

85%
Analyst research time saved
40ms
Average query latency
98.4%
Answer accuracy (evaluated)
OpenAIPineconeLangChainAzurePython
Healthcare · Observability

Enterprise Observability System

Challenge

A national healthcare provider had no visibility into their 300+ data pipelines, leading to weekly silent failures that corrupted care delivery reports used by clinical leadership.

Solution

Implemented a comprehensive data observability platform with anomaly detection, freshness monitoring, schema drift alerts, and automated incident routing.

99.9%
Pipeline SLA achieved
95%
MTTD improvement
0
Silent failures post-deployment
Great ExpectationsDatabricksPagerDutyKafka
Retail · Data Platform

Data Platform Transformation

Challenge

A global retailer was spending $4M/year on a fragmented Hadoop-era data estate that couldn't support real-time decision-making or modern AI use cases.

Solution

Executed a full platform migration to a Databricks Lakehouse architecture, rebuilding 120+ pipelines, implementing Delta Live Tables, and enabling sub-second BI queries.

$2.1M
Annual infrastructure savings
12x
Query performance improvement
120
Pipelines modernized
DatabricksDelta Live TablesdbtTerraformAWS

Types of Engagements

From rapid architecture sprints to multi-year platform partnerships.

2–4 weeks

Architecture Sprint

Rapid architecture design, review, and recommendations document. Ideal for planning a major initiative.

8–24 weeks

Platform Build

Full greenfield or brownfield implementation of a data or AI platform from design to production.

6–16 weeks

AI Deployment

Production RAG, LLM orchestration, or agentic system deployment with governance and monitoring.

Ongoing

Platform Partnership

Long-term embedded engineering post-launch — optimizations, new features, and operational excellence.

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