Holistics vs Chord
Side-by-side trajectory, velocity, and editorial themes.
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.
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.
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