Productivity · Head-to-head

tl;dv vs Read AI

tl;dv (freemium, AI Score 7.6/10) vs Read AI (freemium, AI Score 7.6/10). Side-by-side pricing, features, pros and cons, and which to pick.

The verdict

Pick tl;dv if…

→your primary use case is smb and mid-market sales teams running calls across zoom, meet, and teams who want every call in one searchable library and auto-logged to the crm without paying gong-tier prices.
→you need: marketing

Try tl;dv →

Pick Read AI if…

→your primary use case is managers and sales leads at mid-size companies split across zoom, slack and microsoft 365 who need one searchable record of what was said and committed to, plus talk-time and engagement data on their team's calls.

Try Read AI →

Spec	tl;dv	Read AI
Category	Productivity	Productivity
Pricing model	freemium	freemium
Headline pricing	Freemium — free plan available; paid seats start in the ~$20-30/user/mo range. Check website for current pricing	Freemium — free tier with monthly meeting cap; paid tiers start around $15/user/mo on annual billing. Check read.ai/pricing for current rates.
Free tier	Yes — free plan with recording, transcription, AI summaries, and highlights; check the pricing page for current caps, as the free tier has been revised since launch	Yes — free plan covers meeting transcription and AI recaps with a monthly meeting cap, limited history and a reduced integration set. Exact caps change; confirm on read.ai/pricing.
AI Score	7.6/10	7.6/10
Best for	SMB and mid-market sales teams running calls across Zoom, Meet, and Teams who want every call in one searchable library and auto-logged to the CRM without paying Gong-tier prices.	Managers and sales leads at mid-size companies split across Zoom, Slack and Microsoft 365 who need one searchable record of what was said and committed to, plus talk-time and engagement data on their team's calls.
Editor's pick	—	—
Use cases	productivity marketing	productivity
Date added	2026-05-01	2026-05-01

Productivity · freemium

✓Covers Zoom, Google Meet, and Teams in one library — native notetakers only work inside their own platform, so mixed-platform teams get one searchable archive instead of three
✓Automatic Salesforce and HubSpot logging closes the loop that platform-native AI notes leave open
✓Timestamped clip-and-share means you send the 90 seconds that mattered rather than a full recording
✓Transcription across 30+ languages, which matters for distributed teams that multi-language-weak competitors handle poorly
✓Call coaching and playbook scoring at a fraction of what dedicated revenue-intelligence platforms like Gong charge

×The core value has been squeezed hard — Meet, Zoom, and Teams now include AI notetaking for paying seats, so single-platform teams may not need a third-party tool at all
×The free tier is no longer the unconditionally unlimited offer it was at launch; verify current caps before standardizing a team on it
×A bot visibly joining the call is increasingly dated next to local recorders like Granola, and still creates friction with external participants and in consent-sensitive jurisdictions
×Multi-meeting intelligence and coaching — the features that actually justify paying over a native notetaker — are gated to the higher tier

Productivity · freemium

✓Covers meetings, email, chat and calendar in one index rather than transcribing calls in isolation
✓Engagement, sentiment and talk-time analytics that pure note-takers like Fathom and Granola do not offer
✓Works across Zoom, Google Meet and Microsoft Teams, so mixed-vendor teams get one consistent record
✓Per-speaker coaching reports make it genuinely useful for sales and customer-facing managers
✓Real free tier that produces usable recaps before you decide to pay

×Zoom, Teams and Google Meet now include meeting summaries in suites most companies already pay for, which undercuts the core feature
×The cross-app knowledge layer only pays off if most of the team is on it; a single seat in a large org gets a fraction of the value
×Granting access to mail, chat and calendar is a large permission surface that many security teams will question
×Read AI does not disclose which foundation models it runs on, so you cannot reason about quality or data handling from the model vendor

Updated 2026-08-10. Spec data sourced from official product pages and tracked in our public directory at /tools.