# Noodle4

> Noodle4 is content intelligence as infrastructure. Monitor, listen, review, and audit video, image, and text at a cost that scales.

Legacy tools miss the data, and general-purpose models only summarise the obvious. Noodle4 is the utility for monitoring creator content, listening to comment intent, reviewing assets against briefs, and auditing brand health.

## Start here

- [Home](https://noodle4.com/): Content intelligence as infrastructure.
- [Products](https://noodle4.com/products): Monitoring, listening, review, reporting, MCP, API, and Slack.
- [Solutions](https://noodle4.com/solutions): How brands, agencies, PR, and product teams use Noodle4.
- [Examples](https://noodle4.com/examples): Intelligence produced by Noodle4 pipelines.
- [Pricing](https://noodle4.com/pricing): Usage-based plans from £99. Pay for usage, not seats.
- [noodle4 Labs](https://noodle4.com/blog): Latest research and industry news on content analysis and intelligence — and how we apply it to video, comments, and briefs.
- [Contact sales](https://noodle4.com/contact-sales): Pilots, questions, and enterprise packages.
- [Full catalog for agents](https://noodle4.com/llms-full.txt)

## Products

- [Influencer monitoring](https://noodle4.com/products/influencer-monitoring): Track creator content and performance in real time.
- [Brand monitoring](https://noodle4.com/products/brand-monitoring): Watch brand mentions, SKUs, and share of voice.
- [Social listening](https://noodle4.com/products/social-listening): Surface intent, sentiment, and the signals others miss.
- [Influencer screening](https://noodle4.com/products/influencer-screening): Screen creators before you brief or onboard them.
- [Content review](https://noodle4.com/products/content-review): Audit compliance and creator content at scale.
- [Content reporting](https://noodle4.com/products/content-reporting): Turn reviews into reports stakeholders can act on.
- [MCP](https://noodle4.com/products/mcp): Connect Noodle4 to agents and tools via MCP.
- [API](https://noodle4.com/products/api): Run monitors, reviews, and search from your stack.
- [Slack](https://noodle4.com/products/slack): Route briefs, reviews, and alerts into Slack.

## Solutions

- [Brands](https://noodle4.com/solutions/brands): Monitor category, creators, and brand health in one place.
- [Agencies](https://noodle4.com/solutions/agencies): Run reviews, monitors, and reporting across client programmes.
- [PR](https://noodle4.com/solutions/pr): Catch mentions, creators, and coverage as it lands.
- [Product and R&D](https://noodle4.com/solutions/product-and-rd): See how products, SKUs, and claims show up in culture.

## noodle4 Labs

- [How to check every creator video against your brief, without watching them all.](https://noodle4.com/blog/how-to-check-every-creator-video): Reviewing a sample tells you how the average video did, not about the one that went wrong. Here is how to turn your brief into something every video can be checked against.
- [Why untagged creator posts are your biggest blind spot](https://noodle4.com/blog/why-untagged-creator-posts-are-your-biggest-blind-spot): Stories, reposts and unpaid mentions never hit the tracking link. Here is how to find the posts your brief never saw.
- [Weekly creator reports without the spreadsheet](https://noodle4.com/blog/weekly-creator-reports-without-the-spreadsheet): A weekly report should show which requirements failed, on which videos, with the moment attached — not another tab of statuses.
- [Reading the comments: questions, complaints and buying signals](https://noodle4.com/blog/reading-the-comments-questions-complaints-and-buying-signals): Comments tell you what the video did not. Sort them into questions, complaints and buying signals before you call a campaign a success.
- [Why ASR hears “Road” when the video says Rhode](https://noodle4.com/blog/why-asr-hears-road-when-the-video-says-rhode): Social listening is noisy on video because most tools match brands on ASR transcripts. General speech models are not trained on beauty names, so Rhode becomes Road and silent pack-shots vanish.
- [Why we abandoned OpenAI for comment analysis](https://noodle4.com/blog/why-we-abandoned-openai-for-comment-analysis): Most social listening tools do not read every comment. Frontier LLMs are too expensive at thread scale, so they sample. The allergic reactions and product hacks live in the outliers that sampling throws away.
- [Why a Sephora haul comment is not sentiment for your brand](https://noodle4.com/blog/why-sephora-haul-comments-are-not-brand-sentiment): In a five-brand haul, “this made me look splotchy” is not negative for every product on screen. Isolated comment scoring cannot tell which SKU the viewer meant.
- [Why frame-by-frame video analysis cannot scale](https://noodle4.com/blog/why-frame-by-frame-video-analysis-cannot-scale): Sending one frame per second to a frontier vision model is roughly $200 a month per heavy user. Most of those frames cannot answer the question you are asking, so the cost is unscalable as a product.
- [Why we stopped asking open questions of video models](https://noodle4.com/blog/why-open-vqa-hallucinates-on-video): Open, single-shot VQA changes its answer every time you ask. Without a fixed schema the model narrates, invents products, and cannot be rolled up. A harness that demands mechanical evidence is what made outputs stable.
- [Why video summaries bury the 10 percent that matters](https://noodle4.com/blog/why-video-summaries-bury-the-insight): Typical video summaries are 80–90 percent filler. If you search those summaries, the model is reading noise and forgetting the hook, friction, SKU, and claim that actually change a brief.
- [Logo detection is not SKU-level compliance](https://noodle4.com/blog/logo-detection-is-not-sku-level-compliance): Logo detection is not enough for influencer compliance. Multi-SKU brands need to know which product was used, and whether a competitor appeared in frame — including in silent video.
- [Why a 15 million view video can have 1 percent purchase intent](https://noodle4.com/blog/why-high-reach-videos-have-low-purchase-intent): High reach is not high conversion. A morning routine with 15 million views can carry about 1 percent purchase intent, while a 10k-view wear-test sits near 35 percent. Rank on hook × comment intent, not likes.

## Optional

- [Privacy](https://noodle4.com/privacy): How organisation and content data is handled.
- [Terms](https://noodle4.com/terms): Terms for using Noodle4.
- [Sign up](https://noodle4.com/signup): Create a workspace.