For teams that want to own their data platform — we build it, migrate it, enable it for AI, and train your people to run it.
Our managed platform is the fastest path to a production-ready AI data platform — but it's not the only path. For organizations that want to own and operate their data infrastructure in-house, our Services practice brings the same architecture, engineering depth, and AI expertise directly to your environment and your team.
Whether you're starting from scratch, migrating off a legacy architecture, or looking to layer AI onto an existing platform, our services are focused on one outcome: a governed, AI-ready data platform your business can rely on — built on a foundation of security and data ownership that never wavers.
We design and build your AI data platform from the ground up — data lake on your cloud provider of choice, transformation and compute layer, semantic layer, and governance framework — all deployed in your environment with your security model in place from day one.
Already have a data platform that's outgrown itself — or a legacy architecture built before cloud-native tooling existed? We migrate your existing data infrastructure to a modern, governed data platform without disrupting the reporting and workflows your business depends on today.
Your data platform is the foundation. AI is what you build on top of it. We help you design and deploy the AI layer on your existing or newly built data platform — custom agents for your business functions, AI-powered analytics, anomaly detection, and the governance framework that keeps AI outputs trustworthy.
A data platform is only as powerful as the people who use it. We design and deliver hands-on training programs that teach your analysts, engineers, and business users how to work with your specific platform — so they can query it, build on it, govern it, and get value from it independently.
Every service engagement — whether a platform build, a migration, or a training program — is built around the same three pillars.
We don't build data platforms that need to be rearchitected when you're ready for AI. Every platform we build — and every migration we execute — is designed with AI consumption in mind: clean data models, semantic layers that speak natural language, and vector-ready unstructured data pipelines.
Data governance isn't a phase at the end of a project — it's a design decision made at the start. We build governance into the platform architecture: lineage from source to dashboard, data contracts, quality monitoring, and access controls that enforce your business rules automatically.
Your data platform inherits your security model — not a parallel one you have to maintain separately. We wire your identity provider, access policies, and compliance controls into the platform from day one, so your security team manages one consistent security posture across your entire stack.
Every engagement includes knowledge transfer — not as a checkbox, but as a core deliverable. When we're done, your people understand the architecture, can operate the platform, and are equipped to build on top of it. We measure success by your team's independence, not your dependence on us.
The right choice depends on whether you want to own and operate your data platform in-house, or have us run it for you as a managed product. Both deliver the same architecture and the same outcomes.
Choose Services if you want to own your data infrastructure — in your cloud account, governed by your security team, operated by your engineers. We build it, hand it off, and train your team to own it. Your data stays entirely within your perimeter and your control.
Choose our managed Platform if you want a production-ready AI data platform without the overhead of running data infrastructure in-house. We build it, operate it, and continuously improve it — in our cloud or yours. Your team gets the platform's capabilities without owning the stack underneath.