The Rise of CaaS: Context-as-a-Service for Agentic AI — Omer Primor, Bright Data
Just past 15,000 queries, renting context stopped being the cheaper option. Omer Primor gets that number from a small experiment he is careful to call a test rather than a benchmark: enrich one company across 25 fields, run it 100 times against this event's sponsors, and compare AI search products, context as a service vendors, and a scraper pipeline built in roughly a day. Pricing a week of setup at $5,000, the build it yourself path crossed over a little above 15,000 entities, and he expects the real crossover sits lower than most teams assume.The argument underneath is about frequency rather than volume. Web data decays fast, with social content stale inside a day and news, finance, and retail largely irrelevant after 30 days, so context is never a snapshot you take once. Every repeated query costs what the first one did, even when nothing has changed and the answer comes back identical. What he sees teams do about that is quietly cut scope: check a company weekly instead of daily, take 10 results instead of all of them, skip the question entirely. Owning the pipeline inverts the shape, paying upfront so that retrieval afterwards is effectively free. One result surprised him. The dedicated context vendors scored lower on coverage than general search, because they can only answer from what they already hold, and a question outside that set has no answer at any price.
Speaker info:
- https://www.linkedin.com/in/omer-primor/
Timestamps:
0:00 - Web scale, and the web as context rather than data
2:43 - Data decay, and why context is not a snapshot
3:37 - Search fragments, from Google to the AI search companies
5:42 - What search cannot answer about change over time
6:32 - Context as a service, and the vertical search shape
10:01 - The test: 25 fields, 100 companies
11:04 - Coverage, and why the context vendors placed lower
12:32 - Cost, and frequency as the real killer
15:22 - Cutting corners, renting versus owning
15:59 - Building it yourself in a day
18:34 - The tipping point just above 15,000 queries
21:31 - Owned context compounds, rented context decays Receive SMS online on sms24.me
TubeReader video aggregator is a website that collects and organizes online videos from the YouTube source. Video aggregation is done for different purposes, and TubeReader take different approaches to achieve their purpose.
Our try to collect videos of high quality or interest for visitors to view; the collection may be made by editors or may be based on community votes.
Another method is to base the collection on those videos most viewed, either at the aggregator site or at various popular video hosting sites.
TubeReader site exists to allow users to collect their own sets of videos, for personal use as well as for browsing and viewing by others; TubeReader can develop online communities around video sharing.
Our site allow users to create a personalized video playlist, for personal use as well as for browsing and viewing by others.
@YouTubeReaderBot allows you to subscribe to Youtube channels.
By using @YouTubeReaderBot Bot you agree with YouTube Terms of Service.
Use the @YouTubeReaderBot telegram bot to be the first to be notified when new videos are released on your favorite channels.
Look for new videos or channels and share them with your friends.
You can start using our bot from this video, subscribe now to The Rise of CaaS: Context-as-a-Service for Agentic AI — Omer Primor, Bright Data
What is YouTube?
YouTube is a free video sharing website that makes it easy to watch online videos. You can even create and upload your own videos to share with others. Originally created in 2005, YouTube is now one of the most popular sites on the Web, with visitors watching around 6 billion hours of video every month.
