{"id":9560,"date":"2026-06-24T15:13:57","date_gmt":"2026-06-24T10:13:57","guid":{"rendered":"https:\/\/paknews.centers.pk\/ais-streaming-stack-engagement-agents\/"},"modified":"2026-06-24T15:13:57","modified_gmt":"2026-06-24T10:13:57","slug":"ais-streaming-stack-engagement-agents","status":"publish","type":"post","link":"https:\/\/paknews.centers.pk\/ur\/ais-streaming-stack-engagement-agents\/","title":{"rendered":"AI’s Streaming Stack: Engagement Agents"},"content":{"rendered":"


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The three companies covered in this issue\u2019s column are all involved in bringing more monetization or engagement to today\u2019s streaming content. The key differentiator is using AI to delve deep into content meaning and adjacent data to create new opportunities for content formats that previously did not exist.<\/span><\/p>\n

While we sometimes cover tools that are suitable for smaller publishers, these AI tools<\/a> require a certain scale of content to \u2026 well, work at scale. Two of these companies have been around for 10-plus years. The other one is much newer but already has an impressive connection with a media company.<\/span><\/p>\n

Moments Lab<\/strong><\/h2>\n

Moments Lab<\/span><\/a>\u00a0is helping media and entertainment IP owners create\u00a0<\/span>new revenue streams from their existing IP by identifying content within assets in their video libraries that can be repurposed to attract new audiences. The company describes this new product category as an \u201cAI MAM<\/a>.\u201d<\/span><\/p>\n

One customer it\u2019s working with is Banijay Entertainment<\/a> to help the Paris-based producer and distributor find micro stories within existing content. Banijay could use Moments Lab\u2019s Discovery Agent<\/a> to search for the \u201ctop 10 best fish dishes ever from <\/span>Master\u00adChef Australia<\/span><\/em>, for instance,\u201d says Moments Lab co-founder and CEO Phil Petitpont<\/a>. \u201cOur agent has a capacity to find all these fish dishes, take the top 10, and then publish them on social media to generate new audience streams.\u201d<\/span><\/p>\n

\"Using
Using Moments Lab\u2019s\u00a0AI chatbot-based Discovery Agent for natural language content library queries\u00a0(Source: Moments Lab)<\/span><\/span><\/em><\/p>\n

Petitpont goes on to explain how this capability increases profitability or reduces costs for publishers like Banijay: \u201cMost of the time, what our customers see is this capacity to really scale the revenue line of the business.\u201d Banijay has told Moments Lab that repurposing a 1- or 2-minute video currently costs roughly $1,000. With help from Moments Lab, that cost drops to under $100.<\/span><\/p>\n

\u201cIt\u2019s a totally new way to generate a revenue stream that is very different from just reselling the rights of Season 10 of <\/span>MasterChef<\/span><\/em>,\u201d Petitpont explains. \u201cIt\u2019s like creating a new narrative angle that will then generate a new audience on social media.\u201d This short-form content is served on YouTube, Meta, Instagram, or TikTok.<\/span><\/p>\n

Petitpont says there are three revenue streams: mid-roll and post-roll ads, sponsorships, and directly inserting ads into the video. \u201cLots of marketing teams are using this tool not only to generate revenue streams, but also to promote their shows,\u201d he notes.<\/span><\/p>\n

Like most companies, Moments Lab picks and chooses models to deliver a multimodal solution. \u201cWe are using 20 different models,\u201d Petitpont says. \u201cIf I\u2019m searching for some moments about fish dishes, I can find not only all of the 2- and 3-minute sequences about each fish dish, but also a very specific step of cooking or putting it in the fridge or the oven.\u201d These moments are identified in time-based metadata. Users can manually create clips with their clipping tool or use automated clip generation. The metadata breaks out frame-by-frame shot descriptions, complete with a full description of the visual details. Moments Lab also creates content sequences and summaries that can be used by an editor in their outside editing tool.<\/span><\/p>\n

\u201cWe separate the production flow into two steps,\u201d Petitpont explains. \u201cThe first is what we call the \u2018upstream\u2019 step: the original show, the 22-minute episode, the 30-minute newscast, the 52-minute episode, whatever. The second part is what we call \u2018downstream,\u2019 which is everything related to monetizing the show, whether it\u2019s publishing the show, receiving the rights, or repurposing the show.\u201d<\/span><\/p>\n

While Moments Lab works with news, episod\u00adic, and reality content, Petitpont believes that\u00a0<\/span>reality content is especially ripe for splicing and dicing. \u201cOne of the things we observe that\u00a0<\/span>is very interesting for TV reality shows like <\/span>Big Brother<\/span><\/em>,\u201d he says, is that publishers \u201cwant to start the downstream workflow during the show. Many things are happening at the same time. But as a director, you choose one thing at a time; you can\u2019t cover two stories during the show. On social media, you don\u2019t have this issue because you can choose to cover different parallel stories. You don\u2019t have this issue of producing a linear show.\u201d<\/span><\/p>\n

The company\u2019s product demo showed an easy-to-understand interface, featuring an AI agent customers can talk to. It also works by API. In one sample clip generated by AI in the demo I saw, there was administrative metadata such as title, content type, program category, season, episode, EPG summary, social media descriptions, chapter markers, and hashtags.<\/span><\/p>\n

\"Moments
Moments Lab-generated administrative metadata (Source: Moments Lab)<\/em><\/p>\n

\u201cWe are storing three kinds of meta\u00addata: visual elements, tran\u00adscription, and summarization,\u201d Petitpont says. He told me that customers can extract this metadata for other uses as well. \u201cOne important thing we\u2019ve worked on is to avoid any vendor lock-in on the metadata. When a customer is indexing content with us into our platform, this metadata is globally available. You don\u2019t need to pay to access the metadata to use it in other systems.\u201d<\/span><\/p>\n

Moments Lab stores the following metadata types:<\/span><\/p>\n