Hex vs Holistics
Side-by-side trajectory, velocity, and editorial themes.
Hex bets the product on prompt-as-authoring: data apps are now one sentence away.
Hex is in the most aggressive AI-agent build-out of any analytics tool we track. The last month has stacked: repo connections as agent context, Generative Data Apps, prompt-to-dashboard, context suggestions, user memory, projects-as-context, and a CLI for programmatic context control. Around it, the surface has been extended with Hex-in-Claude, Hex-in-Cursor, a ClickHouse partnership, and Google Sheets export.
Hex is reorganizing itself around an agent that the user steers with prompts and grounds with context. Each release adds either more context channels (repos, projects, semantic models, memory, guides) or more places the agent can act (apps, dashboards, third-party clients). The product surface is being recast: notebooks remain, but the primary entry point is becoming the prompt. Expect Hex to keep stacking context sources and to start moving from authoring assist into autonomous, scheduled, agent-driven workflows.
Next plausible moves: agent-authored scheduled jobs or alerts, deeper integrations with semantic layer tools (dbt-style metric stores) as context sources, and more co-pilot embeddings in third-party editors. A pricing tier tied to agent usage is increasingly hard to delay.
Holistics turns the BI dashboard into a conversational AI surface, on customer-owned models.
Holistics is well into a BI-meets-AI productization phase, layering conversational analytics on top of its existing modeling and dashboard core. Recent releases mix consumer-grade dashboard polish (auto-run filters, K/M/B number formatting, percentile calculations) with deeper AI plumbing: bring-your-own Claude and Gemini keys, per-user AI access controls, and now an Ask AI that asks clarifying questions back. The GitHub App integration also signals enterprise-readiness work alongside the AI push.
The product is being repositioned from a self-service BI tool to an AI-mediated analytics workspace where natural-language exploration is the headline interaction. Crucially, the team is pushing AI as an infrastructure layer customers can own — BYO LLM keys, granular access policies — rather than locking customers into a vendor-managed model. The dashboard improvements look incremental, but read as ground prep for AI agents to consume and manipulate dashboards more reliably.
Expect the next quarter to bring agentic dashboard editing — Ask AI not just answering but proposing dashboards and saving them — plus expanded BYO LLM coverage (likely Azure OpenAI or open-weights via OpenRouter) to widen procurement options for enterprise buyers.
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