Sacra estimates that Loom hit $50M annual recurring revenue (ARR) in October 2023.

Loom serves over 25 million registered users globally, with an estimated 200,000–350,000 paying business customers. In 2024 alone, users recorded roughly 88 million videos, indicating that Loom is not a novelty tool but a habitual communication layer embedded into daily workflows.

Average revenue per customer sits around $300 annually, reflecting Loom’s freemium, bottom-up adoption model. This ARPA has been diluted somewhat post-acquisition as Atlassian increasingly bundles Loom with Jira and Confluence, but that tradeoff expands Loom’s surface area dramatically. Rather than optimizing for standalone monetization, Loom is being repositioned as a value amplifier across Atlassian’s 300,000+ customer base.

Atlassian acquired Loom for approximately $975 million in October 2023, representing an exit multiple of roughly 19x ARR at the time. The deal closed in November 2023 and was structured as a mix of cash and equity awards.

Prior to the acquisition, Loom raised about $203 million in venture funding. The largest round was a $130 million Series C in May 2021 led by Andreessen Horowitz, which valued the company at $1.53 billion during the peak of the SaaS valuation cycle.

Earlier rounds were backed by Sequoia Capital, Kleiner Perkins, General Catalyst, ICONIQ Growth, and Coatue Management. From a venture perspective, Loom exited below its last private valuation, but the outcome still reflects a strong strategic acquisition rather than a distressed sale.

Loom is an asynchronous video messaging platform built around one core insight: explanations scale better as links than as meetings. Users record their screen, camera, or both using a browser extension, desktop app, or mobile app, and Loom uploads the video in real time so a shareable link is instantly available when recording ends.

Recipients can watch directly in the browser without downloads, react with emojis, leave timestamped comments, or reply with threaded videos. This makes Loom videos collaborative objects rather than static files.

The product has expanded well beyond simple recording. Loom’s AI features automatically generate titles, summaries, chapters, transcripts, and action items. Users can convert a video into a Confluence page, Jira ticket, or step-by-step guide with a single click, turning spoken context into structured work output.

Recent improvements include filler-word removal, silence trimming, and automatic video enhancement, reducing the friction of publishing without requiring traditional editing skills. A rebuilt cloud editor enables near-instant trimming and stitching, eliminating long re-encoding delays.

Native integrations with Jira and Confluence allow users to record directly inside issues or pages, while embeds across Slack, Gmail, Notion, GitHub, and other tools make Loom links portable across the modern work stack.

Loom’s core users span product teams documenting decisions and bugs, engineers reproducing issues, sales teams sending personalized demos, and support teams building tutorial libraries. Across all of these, Loom’s value lies in turning explanation into durable, reusable artifacts.

Loom operates on a freemium SaaS model. Core recording and sharing features are available for free, while advanced functionality is gated behind paid Starter, Business, and Enterprise tiers.

Historically, Loom monetized through standalone subscriptions driven by team-level adoption. Post-acquisition, the model is shifting toward bundling within Atlassian’s Teamwork Collection alongside Jira, Confluence, and Rovo.

This shift lowers Loom’s customer acquisition costs dramatically while increasing its strategic importance. Loom becomes less a product customers buy and more a capability they inherit as part of Atlassian’s platform.

Revenue expansion occurs through seat growth inside organizations, upgrades to higher tiers for admin and security features, and deeper usage that increases reliance on Loom-generated artifacts. Video storage, processing, and AI inference drive costs, but Atlassian’s infrastructure scale supports healthy gross margins for a video-heavy product.

The long-term monetization lever is workflow dependency. As teams build processes and institutional knowledge around Loom videos and summaries, switching costs rise even if Loom is not priced as a standalone line item.

Loom competes across three overlapping layers of the modern work stack: async communication primitives, video-enabled collaboration platforms, and AI-driven knowledge capture systems. What makes Loom unusual is that it does not try to win on raw video quality or live communication, but rather on how effectively video turns into shared work output.

As video recording itself commoditizes, Loom’s competitive position increasingly hinges on workflow depth, distribution leverage via Atlassian, and ownership of post-video artifacts (summaries, tasks, documentation).

At the most basic layer, Loom competes with tools that let users send short-form async video updates instead of text.

Slack Clips is the most direct threat here. It offers native, unlimited short video and audio messages embedded directly in Slack channels—zero setup, zero additional cost, and perfect contextual placement. For daily standups, quick clarifications, or team updates, Slack Clips is “good enough,” and its advantage is structural: it lives where conversations already happen.

Similarly, Zoom Clips leverages Zoom’s massive installed base and video infrastructure to offer async recording with light editing. Zoom’s positioning is less about replacing Loom outright and more about preventing Zoom customers from needing a separate async video tool.

These tools aim to collapse async video into existing communication surfaces, betting that convenience beats specialization for most teams.

Loom’s defense is that it treats video as a first-class, durable artifact, not an ephemeral message. A Loom video is designed to live beyond the moment: linkable, commentable, searchable, and increasingly convertible into structured work objects.

The second competitive layer is large collaboration suites embedding recording as a defensive feature.

Microsoft combines screen recording, transcription, and AI summarization across Teams, Stream, Clipchamp, and Copilot. Google Workspace auto-saves Meet recordings to Drive with AI-generated captions and summaries. In both cases, recording is “free,” tightly integrated, and bundled with enterprise contracts.

These platforms are not trying to be Loom, they are trying to eliminate the category by making standalone async video feel unnecessary. For IT buyers, the pitch is compelling: fewer vendors, fewer contracts, fewer data governance headaches.

This is where Loom’s Atlassian ownership becomes decisive. Atlassian does not compete on email, chat, or meetings. It competes on work tracking, documentation, and execution. Loom’s job inside Atlassian is not to replace Teams or Meet, but to ensure that when work is explained visually, it flows directly into Jira issues, Confluence pages, and Rovo-powered knowledge graphs.

In other words, Microsoft and Google treat video as a communication endpoint. Atlassian (via Loom) treats it as input material.

A third category includes tools optimized for specific professional use cases rather than general collaboration.

Vidyard dominates sales video, where the goal is personalization at scale, analytics on viewer behavior, and tight CRM integration. Its competitive advantage is pipeline attribution, not async teamwork.

Descript and similar AI editing tools compete on production quality and creative control. They win when users want to author content, not explain work quickly.

These tools coexist with Loom rather than fully displacing it. Loom’s sweet spot is low-friction explanation (status updates, walkthroughs, bug reports, internal demos) not polished marketing assets.

Looking forward, AI-generated video platforms like Synthesia and Runway represent a longer-term, structural risk. If teams can generate high-quality explainer videos without recording themselves, Loom’s capture-first model could be bypassed for training, onboarding, and presentations.

However, these tools currently solve a different problem: broadcasting information, not collaborating around work. Loom’s moat here is context, in that its videos are anchored to live projects, tickets, and documents, not standalone scripts.

Loom’s initial market of async video messaging is relatively limited. Its real upside lies in expanding what video represents inside organizations, from communication to knowledge capture and AI-readable context.

Every Loom recording produces transcripts, summaries, chapters, and action items. When these outputs live in Confluence and are indexed by Rovo, video becomes part of an organization’s searchable knowledge base.

This expands Loom into the knowledge management market, estimated at over $25 billion globally. Instead of documentation written after the fact, teams capture knowledge as they explain work, with AI structuring the output automatically.

Over time, Loom’s value compounds as video libraries grow and are repeatedly queried, reused, and referenced across projects.

The acquisition of Rewatch extends Loom into the meeting productivity space, bringing live meetings alongside async video.

The value proposition is not recording meetings but closing the loop. AI-generated notes, decisions, and action items flow directly into Jira and Confluence, turning meetings into structured work inputs rather than dead-end recordings.

This positions Loom against tools like Otter, Fireflies, and Fathom, but with a deeper integration into execution systems rather than note-taking alone.

As Loom inherits Atlassian’s enterprise infrastructure, it becomes viable in regulated industries such as healthcare, financial services, and the public sector.

Features like data retention policies, audit logs, and compliance controls unlock markets that historically avoided async video. In these environments, Loom functions as a governed communication layer rather than a lightweight productivity tool.

Long term, Loom videos become high-signal training data for organizational AI agents. Explained decisions, narrated workflows, and recorded edge cases give systems like Rovo a richer understanding of how work actually happens.

In this future, Loom is not just a video tool. It becomes the human-to-AI translation layer inside the enterprise.

Bundling commoditization: As major platforms like Microsoft, Google, and Slack embed basic screen recording capabilities for free, Loom's core value proposition risks becoming commoditized. While Loom offers superior AI features and editing capabilities, many teams may find platform-native tools sufficient for basic async communication needs.

Integration dependency: Loom's growth strategy relies heavily on Atlassian's customer base and platform integration, creating concentration risk around a single distribution channel. If Atlassian's growth slows or competitive dynamics shift, Loom's expansion could be constrained by factors outside its direct control.

AI displacement: Emerging generative AI video tools like Synthesia could eventually replace human-recorded videos with synthetic alternatives for training, presentations, and other structured content. If AI-generated videos become indistinguishable from recorded content, Loom's capture-focused model could face obsolescence in key use cases.