Data Stack Partners
The 9 data and AI platforms we ship in production: Tableau, Power BI, Snowflake, Databricks, Microsoft Fabric, Azure, AWS, Google Cloud, and dbt.
Technology partners
Open standards, not just platforms.
Tool fit beats tool preference, every time.
Not sure which stack fits your environment?
Semantic model design, Direct Lake mode, Copilot in Power BI, and dataset governance for Microsoft shops.
The platforms we ship in production. Multi-tool consulting, no vendor lock-in.
The Model Context Protocol is the open standard for connecting AI agents to tools and data. We build narrow MCP servers scoped to one capability, keep read access separate from write access so the read half can be approved on its own, and log the tool call with its arguments rather than only the outcome. That is the shape that gets through a security review.
Most integration work is against an API that already exists and already has rules. We build with it rather than around it, including the retries, the back-off and the idempotent writes, because the interesting part is never the call and always what happens when it fails.
We don't pick a platform on principle. We pick what fits your existing tooling, your skill mix, and the workloads you actually run. Below are the platforms we've shipped in production at mid-market and Fortune 500 clients, grouped by the role each one plays best.
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These are specifications rather than partnerships. We work to them because the agents our clients run have to reach real systems safely, and a standard is what stops every connection being a bespoke one.
The right platform depends on three things: the workload (BI vs. warehousing vs. ML vs. real-time), the existing stack (Microsoft shops should default to Fabric + Power BI; Salesforce shops to Tableau), and the team you've to operate it. We've shipped cross-platform stacks where Snowflake handles SQL warehousing, Databricks handles ML, and Power BI sits on top, and we have shipped single-vendor stacks where Microsoft Fabric covers everything end-to-end. Both are correct for the right context.
If you're deciding between two or three of these platforms, the comparison content we've published is the right starting point. Or skip ahead to the 30-day Analytics Truth Audit and we will recommend the stack that maps to your environment, with the cost math and a 90-day implementation plan.
Start with a 30-day Analytics Truth Audit. We map your current data estate, recommend the platform mix that fits, and ship a 90-day implementation plan with the cost math.