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As of August 18, 2026, Highlight is in transition. Its original individual assistant remains available through a free plan and a $20-per-month Pro plan, while the company says that version is “not where we’re headed” and directs users interested in the new Highlight or Highlight for Teams to a waitlist.
What Medal’s $13 million funding covered
The funding announcement came from Medal, best known for software that records and shares gaming clips. The reported $333 million figure was a post-money valuation; it was not the amount raised. The announcement date was July 11, 2024, and the named investors were:
- Horizons Ventures
- OMERS Ventures
- Peak6
- Arcadia Investments, also referred to as Arcadia Investment Partners
Medal’s announcement and TechCrunch’s coverage presented Highlight as a new product line built around Medal’s experience understanding activity on a computer. The capital was intended to fund the contextual-AI platform, its model integrations and a broader developer ecosystem.
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Medal said MedalTV had more than 1 million daily active users and that its capture technology was used by more than 4 million gamers per month. Those figures were company-provided, not independently audited user metrics. (Medal announcement)
Why a gaming-clipping company moved into desktop AI
Gaming capture is more than saving a video after an event. To identify a useful moment, software must monitor what is happening on screen and in system audio, detect relevant activity and preserve the right segment without requiring a player to edit a long recording manually.
Medal’s strategy was to reuse that context-detection capability for ordinary desktop work. Instead of asking a chatbot to interpret text pasted into a window, Highlight was designed to make the visible desktop itself the starting point. That positioned Medal as a context and routing layer rather than as the maker of one general-purpose language model.
How Highlight was designed to work at launch
Capture and prompt
The launch version was described as a floating desktop interface for Windows and macOS. TechCrunch reported that hovering over a floating button could capture the current screen and provide it as context. Highlight could then suggest prompts or let the user type a question about what was visible.
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Choose an AI service
The user could select an AI model or application. Launch materials named ChatGPT, Anthropic’s Claude and Perplexity, along with other applications. These were launch integrations and choices, not a guarantee that every provider remains supported in the same way in 2026.
Receive an answer or action
The selected context was passed to the chosen model, subject to user permission and that provider’s own processing and retention rules. The result could be an explanation, summary, draft or suggested action. The intended sequence was:
- Open or view the relevant document, webpage, meeting or application.
- Activate Highlight and capture the intended screen context.
- Review a suggested prompt or enter a question.
- Select an available model or assistant.
- Authorize transmission of the context.
- Review the returned answer or action before relying on it.
Information beyond a screenshot
Launch coverage also discussed user-supplied documents, system-audio memory, meeting transcription and identifying action items from online interactions. Broader memory and meeting capabilities were development plans at launch, rather than proof of a fully mature feature set at that time.
Privacy: what was claimed and what users still need to check
Medal said Highlight captured screen content locally, did not store the captured material and would not send anything beyond the user’s screen without permission. Those are company assurances, not an independent security audit. “Continuous capture” also does not mean that all captured content was permanently recorded or uploaded: capture, temporary local processing, user-approved transmission, cloud inference and retention are separate events.
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Users should establish the actual data path for each workflow. Important questions include:
- Does a feature use local processing, cloud transcription or both?
- Are screenshots, audio, transcripts, prompts or outputs retained?
- Which model, transcription or integrated application receives the data?
- Can sensitive windows be excluded, and is there an audit history of transmissions?
- Do workplace or team controls exist for confidential material?
Local capture can reduce exposure of raw screen content, but it does not eliminate risk once a user sends context to an external model. A screen-aware tool may encounter passwords, authentication codes, financial records, medical or legal documents, source code, customer data and confidential calls. Test permissions and exclusions before using it for sensitive work.
Performance and accuracy trade-offs
A context layer can save time when the answer depends on what is already open. Useful examples include explaining an unfamiliar interface, summarizing a visible document, turning an error message into troubleshooting steps, comparing an open spreadsheet with a conversation, or extracting meeting action items.
The same design creates failure modes:
- The assistant may capture a partial document, the wrong browser tab or an outdated screen state.
- Charts, images and transient notifications can be interpreted incorrectly.
- Frequent capture may affect CPU, GPU, memory, battery life, game frame rates or video-call performance.
- Answers can be wrong even when the captured context is accurate.
- A floating control can add distraction or conflict with accessibility workflows.
No performance benchmarks establish negligible system impact. Keyboard-only activation, screen-reader behavior, multi-monitor handling, protected content and exact operating-system requirements were not established by the cited launch materials.
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Medal’s larger platform ambition
Medal did not describe Highlight merely as a wrapper around a chatbot. It proposed open APIs, third-party assistants, an app-store-style ecosystem and developer grants of up to $30,000. Founder and company materials compared the intended extension model with Raycast, but the analogy has limits: Raycast is primarily a launcher and extension platform, while Highlight’s proposed differentiator was contextual capture and model routing across Windows and Mac.
The plan was also model-agnostic. Users could switch among providers rather than committing to one vendor. That creates flexibility, but integrations can break when APIs change, providers have different privacy policies and credit-based pricing can obscure the cost of a typical task. The sources establish the proposed ecosystem and grants, not that a large developer marketplace ultimately materialized.
How Highlight compares with alternatives
| Need | Potential fit | How it differs from Highlight’s original pitch |
|---|---|---|
| Screen-aware and meeting-context assistance | Highlight AI | Combines desktop capture, context injection, model routing and assistant actions. |
| Standalone general AI | ChatGPT, Claude, Perplexity | Better suited to mature chatbot, writing, document or web-research workflows without a separate desktop capture layer. |
| Keyboard-driven desktop productivity | Raycast or Alfred | More deterministic launch, search and automation tools; less focused on interpreting whatever is visible. |
| Meeting notes and audio | Granola or Krisp | More specialized for meeting notes, transcription or audio quality than arbitrary desktop context. |
| Personal memory and meeting context | Limitless | Relevant to memory-oriented use cases; recording, consent and retention policies require separate review. |
Operating-system assistants from Microsoft, Apple and Google are strategic competitors because they control desktop permissions and default assistant surfaces. They are not necessarily feature-for-feature substitutes: Highlight’s original proposition was a vendor-neutral context layer that could work across applications and models.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Current availability and pricing in 2026
The official Highlight pricing page, viewed August 18, 2026, gives the clearest current status:
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| Plan | Published details | Best interpreted as |
|---|---|---|
| Free | $0 per month; unlimited chats with automatically selected base models, local audio transcription, daily briefs and summaries, and integrations. | An entry tier for trying the individual assistant. |
| Pro | $20 per month; 2,000 credits monthly, premium and flagship models, screen-context and meeting action items, real-time cloud transcription, enhanced notes and bring-your-own API keys. | A paid tier for heavier model and context use. The page does not say how many typical tasks 2,000 credits cover. |
| Teams | Custom credits, marked “coming soon,” with a waitlist. | An announced direction rather than generally available team pricing. |
The page says the original “Highlight for Individuals” remains available but is “not where we’re headed.” It directs people interested in the “new Highlight” or Highlight for Teams to a waitlist. That language matters: the 2024 Medal launch description should not be treated as a complete description of the current product, and launch-era free access is no longer the only pricing story.
What the funding bet means
Medal’s round was a bet that context capture could become an interface layer for AI. If the product works, users can ask for help without repeatedly copying text, switching applications or deciding which model should handle each task. The business challenge is harder: the company must earn trust around sensitive data, control model and transcription costs, maintain integrations, avoid performance problems and persuade users to adopt a separate layer while operating-system vendors build similar capabilities into Windows and macOS.
For a buyer, the practical question is not simply whether Highlight can answer questions. It is whether its context workflow saves enough time to justify the privacy review, cloud dependencies, credit system and possible overlap with tools already included in a chatbot or operating system.
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