Chord vs Hex
Side-by-side trajectory, velocity, and editorial themes.
Chord is rebuilding Copilot on Anthropic models, Enriched Context, and a breaking SQL infra change.
Chord is a CDP that has spent the last quarter rebuilding its Copilot AI from the inside. The reasoning layer switched to Anthropic models, the context capture got expanded as Enriched Context, and the SQL generation pipeline took a breaking infrastructure change. Around that, the regular CDP work — Iterable data modeling, searchable tables, Activations sync redesign — continues at a steady release cadence.
Copilot is becoming the product. Each release this year has tied AI further into the CDP's core data plane — modeling, querying, activations — rather than treating it as a sidebar. Live documentation grounding and feedback memory in the latest release signal a push to keep Copilot accurate as the schema evolves underneath it.
Expect a deeper agentic move where Copilot proposes activations or builds segments end-to-end. The Iterable-style data modeling work hints at where AI assistance lands next.
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.
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