Snowflake vs Databricks in 2026: how to actually choose
The honest decision framework we use with clients — workloads, teams and total cost, not vendor marketing.
Lessons from real engagements — what works, what doesn't, and what's actually worth your attention in data and AI.
It's rarely the model. After a year of production deployments across finance and manufacturing, the pattern is unmistakable: evaluation discipline, data readiness and workflow integration decide who ships and who stalls. Here's the playbook we now run on every engagement.
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Data PlatformsThe honest decision framework we use with clients — workloads, teams and total cost, not vendor marketing.
GenAIGolden datasets, regression suites and LLM-as-judge — the QA discipline that makes copilots trustworthy.
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AutomationHow to evolve your UiPath estate toward AI agents without breaking the processes that already work.
FinOpsWarehouse right-sizing, query hygiene and storage tiering — the playbook we run in week one of every engagement.
GovernanceWhat India's data protection law means for your architecture — consent, lineage, retention and audit.
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GenAIA decision tree from 12 production deployments — and the hybrid pattern that wins most often.
AutomationWhy the highest-ROI automation is rarely the one the business asks for first — and how mining reveals it.
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