Dernières discussions
Five enterprise systems. Zero unified view.
Jarvis operates across multiple offices in Toronto, Montreal, and Calgary, with remote operating offices in Bosnia and Tunisia. Finance and operations data lived across separate enterprise applications, each with its own reporting layer and none with a shared model.
"Management would request ad hoc data, and it took too long to produce. Sometimes it was almost impossible because the data lived across systems. We needed a single platform that could bring everything together so leadership could make faster, more data-driven decisions."
Alisa Ryumkin • Director of Finance & Accounting
The Solution
A unified data platform on Databricks
As a Databricks Silver Tier partner and Delivery Provider, Jarvis drew on the same capabilities it delivers to enterprise clients across financial services, utilities, and regulated industries.
The Results
From a week to minutes
The operational impact has been substantial and quantifiable. Reports that previously required a full week of analyst time, involving data extraction from multiple systems, manual cleaning, and reconciliation, are now generated in minutes.
"Getting data is not a challenge anymore. We can self-serve at the manager level. Building a dashboard takes hours rather than days and weeks. The speed at which teams can move forward without being blocked by data is a fundamental shift in how we operate."
Hamza Ramzi • VP, Strategy & Operations
What's Next
AI, machine learning, and agentic automation
With the governed platform in place, Jarvis is now moving from descriptive reporting toward operational intelligence: surfacing patterns earlier, automating workflows, and bringing real-time decision support closer to the teams using it.
On the Roadmap
Databricks Lakebase
Another area of exploration is Databricks Lakebase, the recently launched serverless Postgres service that unifies transactional and analytical workloads on a single governed platform. The Jarvis team sees strong potential in using Lakebase to integrate operational HR data directly into the Lakehouse, eliminating the need for separate data movement pipelines and enabling real-time applications that sit closer to the data.
"The foundation is in place. Now we’re building AI agents on top of live operational data. Lakebase, agentic workflows, real-time decisioning. That’s the same roadmap our enterprise clients are on, and we intend to get there first."
Denton Cockburn • Senior Partner, Technology Advisory & AI
