Holistics vs Hex
Side-by-side trajectory, velocity, and editorial themes.
Holistics leans into analytics-as-code with agentic dev workflows and a Power BI migration path
Holistics is a BI platform built around analytics-as-code, where models and dashboards are defined in its AMQL language and version-controlled in Git. Recent releases push on three fronts at once: competitive migration (a one-command Power BI importer), AI-native authoring (Claude Code setup skills and a conversational Ask AI), and steady breadth work like an Oracle connector and org-level GitHub App auth. The throughline is making the code-first workflow easier to adopt and operate.
The direction is to lower the switching cost from incumbent BI tools while betting that analytics teams will work through agents and code rather than point-and-click. Migration tooling and agentic setup skills both target the same friction: getting a team productive in Holistics fast. Parallel embed and dashboard-runtime polish (auto-run, KPI styling) point to a continued focus on the embedded-analytics use case.
Expect the migration story to extend to other incumbents and the agentic-development skills to deepen, given the back-to-back Power BI importer and Claude Code setup releases. Embedded-analytics controls look set to keep maturing.
Hex is remaking its notebook into an agent that both uses and plugs into MCP
Hex is converting its analytics notebook into an AI agent platform. It now runs as an MCP client, is invocable from Codex, and ships generative data apps built from prompts, while keeping its model roster current with Kimi K2.7 and Fable 5 and giving admins default-model and branding controls. Integration and governance work — a Figma connector, AWS IAM-role support, signed embedding — rounds out the core.
The arc points at Hex as connective agent infrastructure: consuming external context and tools via MCP, distributing itself into other agent surfaces like Codex, and letting analysts assemble apps and dashboards from prompts. Expect the agent, rather than the notebook grid, to become the primary interface, with model choice and governance layered on top.
Likely next steps deepen the agent's tool-use over MCP connections and push generative apps further toward production embedding and governance controls.
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