Chord
Chord rebuilds Copilot from the ground up, betting its CDP on conversational AI.
A side-by-side editorial comparison of Count and Deepnote — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | Count | Deepnote |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 6.3 | 6.3 |
| Sparks · 30d | 1 | 1 |
| Top themes | agentic-analytics, mcp, public-api, warehouse-connectors | data notebooks, agentic ai, mcp, reproducibility |
| Last editorial update | 17d ago | 21h ago |
| Website | Visit → | — |
Count is turning its BI canvas into a governed, agent-operated analytics platform.
Count is a data-canvas analytics tool reorganizing itself around an AI agent. In two months it shipped a full public REST API and hosted MCP server (governed agent access via OAuth and service accounts), a major agent upgrade that lets the agent read and edit the entire canvas and answer from Slack, and the ability to plug external MCP servers (Linear, HubSpot, Stripe, Slack, Drive) into the agent. Around the agent it keeps broadening warehouse support—ClickHouse, Snowflake semantic models, OSI—alongside chart and UX polish.
Deepnote reshapes the data notebook into agent-operable infrastructure.
Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.
Count is a data-canvas analytics tool reorganizing itself around an AI agent. In two months it shipped a full public REST API and hosted MCP server (governed agent access via OAuth and service accounts), a major agent upgrade that lets the agent read and edit the entire canvas and answer from Slack, and the ability to plug external MCP servers (Linear, HubSpot, Stripe, Slack, Drive) into the agent. Around the agent it keeps broadening warehouse support—ClickHouse, Snowflake semantic models, OSI—alongside chart and UX polish.
Count is building toward analytics where agents are first-class operators: a governed API/MCP layer for access, an agent that drives the canvas end to end, external tool reach via MCP, and connection-level context so guidance is captured once and inherited. Governance—permissions, scopes, service accounts—is the enabling layer that makes agent access acceptable in real data stacks rather than a bolt-on.
Expect more connection- and warehouse-level context controls, a widening catalog of supported external MCP integrations, and deeper Slack-native agent workflows.
Deepnote, a collaborative data-science notebook, is steadily making itself agent-native: MCP tools now let AI agents create and wire integrations end-to-end, and OpenAI's Codex connects natively to a Deepnote workspace's notebooks, schedules, and data. Underneath, it keeps shipping solid workflow features — run snapshots, Git and GitLab sync, Polars, PDF export.
Two tracks are converging: reproducibility and engineering rigor (immutable run snapshots, Git sync, notebook interoperability) and agent-operability (MCP tools, Codex context). Deepnote is positioning the workspace as the trusted context layer that AI agents act through, not just a place humans write notebooks.
Expect more MCP tooling that lets agents operate Deepnote projects autonomously, plus deeper native hooks for external coding agents — the workspace-as-agent-context bet will likely expand beyond Codex.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Count or Deepnote.
Chord rebuilds Copilot from the ground up, betting its CDP on conversational AI.
MotherDuck climbs from serverless DuckDB warehouse to an agent-operable data platform
Superset's Helm chart ships steadily, but these tags track packaging, not the BI app
Apify retools Actors for the agentic web — agent payments and login-gated MCP access.
Usermaven consolidates a sprawling analytics suite into one AI-assisted hub.
Appfigures turns its estimate engine into market-ranking and competitor-intel products.
See all Count alternatives → · See all Deepnote alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — mcp — within Analytics. Count and Deepnote are shipping at a similar cadence (velocity 6.3 vs 6.3, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Count and Deepnote are shipping at a similar cadence (velocity 6.3 vs 6.3, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top Count alternatives in Analytics are ranked by recent ship velocity. Browse the "Count alternatives" section above for the current picks, or visit /alternatives/count for the full list with editorial commentary on each.
Top Deepnote alternatives in Analytics are ranked by recent ship velocity. Browse the "Deepnote alternatives" section above for the current picks, or visit /alternatives/deepnote for the full list with editorial commentary on each.