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iVedha and Databricks.
Databricks gives you the lakehouse. We make it pay off: platforms designed, pipelines rebuilt, costs brought under control, and the whole thing run for you as one service.
Our data practice works inside your Databricks account and your controls, so your data and what you learn from it stay yours.
At a financial trading services firm, in one 8-month engagement:
Lower Databricks bill
Legacy pipelines migrated
Pipeline visibility
Ongoing managed data service afterwards
Databricks builds the platform. We make it pay off.
| Databricks | iVedha | You | |
|---|---|---|---|
| The platform | Lakehouse, Unity Catalog, compute, the roadmap | Designs, builds and migrates your pipelines and workloads | Owns the account and the data |
| Day-to-day running | Platform availability and support | Runs pipelines, monitoring and cost control as one service | Sets priorities, approves changes |
| AI and agents | AI and ML tools on the platform | Governed agents that watch pipelines and spend, and AI use cases on your data | Decides what agents may do alone |
| Accountability | Consumption and platform terms | One SLA, outcomes agreed up front | Signs off outcomes, keeps the IP |
Your data stays in your Databricks account. Every agent action is logged on one governed record, on iVedha NexusOne.
How a trading firm cut its Databricks bill by 40%.
Design first
The target platform designed up front with agents drafting the detail and architects deciding.
Right workload, right place
Work that didn’t need Databricks compute moved to lower-cost storage, so spend went where it adds value.
Pipelines rebuilt
20+ unmaintainable legacy pipelines rebuilt as Airflow workflows, with no proprietary lock-in.
Agents on watch
Monitoring and first-line fixes handled by governed agents, with engineers on root causes.
Run as a service
The same team kept running it as an ongoing managed data service.
Get the results you bought Databricks for.
Start with a lakehouse assessment: where the spend goes, which pipelines are at risk, and where AI on your data would pay off first.