Tana vs voxai

Tana and voxai are both meeting assistants tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Tana

The core workflow is: join a call, talk through the work, and let configured agents handle the artifacts. The vendor describes this as 'botless' — participants do not see a recording bot in the call, which removes the social friction that kills adoption on tools like Fireflies or Otter. Agents are configured by describing the workflow in plain language; Tana builds the skills from that description. Integrations cover GitHub, Jira, Linear, Slack, HubSpot, and Google Calendar, with Google Workspace and Microsoft 365 listed as coming. The compounding-knowledge claim — that every meeting feeds a shared context graph so agents never start blank — is the architectural bet that separates Tana from transcript-only tools, and also the one that requires organizational discipline to validate.

voxai

VoxAI runs entirely on macOS, records locally, and splits your mic from system audio on calls so speaker labels come from channel identity rather than voice-guessing. It connects to Claude, Cursor, or any MCP-compatible client via a single copied prompt — no extension installs, no Python environment, no API-key configuration step. The AI reads the growing transcript in a side panel and can surface risks, questions, or draft action items mid-conversation. The wall appears at ten sessions: after the trial, new recordings cap at ten minutes until you unlock the paid tier. Teams who run long client calls or multi-hour workshops hit that ceiling fast.

Attribute	Tana	voxai
Pricing	Paid	Paid
Price	$20/mo	$19.99 one-time or $19.90 direct
Free trial	30 days	No
Open source	No	Yes
Has API	No	No
Self-hosted option	No	Yes
Platforms	—	macOS (Apple Silicon, 14+)
Pros	Botless call presence — agents operate inside the meeting without a visible recording bot joining the call — so participants do not self-censor and adoption friction drops compared to tools that announce themselves to every attendee. Plain-language agent configuration, so an operations lead can describe a workflow in prose and get a working agent without writing code or hiring someone who can. Bidirectional integrations with Jira, Linear, GitHub, Slack, and HubSpot, which means issues and tasks land in the tracker where engineers actually work rather than sitting in a meeting notes doc nobody revisits. Compounding knowledge graph across meetings, so agents preparing for next week's all-hands pull last week's committed decisions rather than asking someone to re-summarize what was covered. LLM-agnostic architecture, so switching inference providers when cost or capability shifts does not require rebuilding the agent configuration.	Live transcript streaming to your AI client during the conversation, so advice on a negotiation risk or a contract clause arrives while you can still act on it — not in the debrief. Channel-based speaker identification on calls (mic vs. system audio), which means labels are accurate even when voices are similar, so you avoid the manual cleanup that ruins a transcript's usefulness. Fully local recording and transcription with cloud explicitly opt-in, so sensitive client conversations, legal interviews, or internal strategy calls never leave the machine by default. One-time purchase with no account required, so there is no subscription to manage and no credential to rotate when someone leaves the team. MCP connection via a single copied prompt — no extension, no environment setup — which means an AI client like Claude or Cursor is live in under two minutes, and the setup does not break on macOS updates.
Cons	Google Workspace and Microsoft 365 integrations are not available; the vendor lists both as coming with an ETA of Q3 2026. Teams whose calendar, docs, and email live in either ecosystem hit a hard wall on the integrations that would make artifact routing automatic — they bridge the gap manually or wait. Agent quality is a direct function of workflow description quality. Teams that invest time in configuring skills precisely get specific, routable outputs; teams that do not get a well-organized transcript at best. There is no default agent behavior sophisticated enough to substitute for deliberate setup, which means the first two weeks look more expensive than a transcript-only tool. The knowledge graph compounds only if meetings happen consistently inside the platform. A team that routes some standups through Tana and others through a separate recorder ends up with a fragmented context store — agents surface incomplete histories and the compounding-intelligence premise breaks down. Teams that hit this fragmentation typically either mandate full migration or abandon the graph-based features and use Tana as a transcript tool, at which point the cost-to-value comparison against simpler alternatives shifts unfavorably.	The trial caps at ten sessions before new recordings are limited to ten minutes — teams running long client calls, extended interviews, or multi-hour workshops will hit the ten-minute ceiling before they can fully evaluate whether the tool fits their workload, which pushes the purchase decision earlier than the trial design implies. macOS 14 and Apple Silicon are required with no Windows or Linux support described anywhere in the vendor materials — cross-platform teams cannot standardize on this tool, and members on non-Apple hardware must use a different transcription workflow entirely, which usually means the team abandons VoxAI for a browser-based alternative like Otter or Fireflies that runs on any OS. There is no API exposed and the tool is not agentic — it streams context to your AI but does not act on it autonomously. Teams who want the AI to automatically file action items, send follow-up emails, or update a CRM from the transcript must build that layer themselves in their AI client, which means the automation work lands outside VoxAI.

Bottom line

Voxai is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Tana and voxai?

Tana is Paid, while voxai is Paid and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Tana better than voxai?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.

Tana vs voxai: which should I pick?

Pick Tana if its pricing model, openness, or platform fit matches your constraints; pick voxai otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.