Stop feeding raw scraped data to your LLMs (You're burning API credits)
Hey Hackers,
I’ve been building real-time data pipelines and custom web scrapers for over 3 years now, and if there’s one major mistake I see founders making right now, it’s this: Throwing raw, unfiltered HTML dumps or messy data straight into an LLM context window.
Doing this does two things:
It triggers heavy hallucinations because of the data noise.
It burns massive amounts of tokens, driving your OpenAI/Anthropic bills through the roof.
Lately, I’ve been focusing heavily on Data Density and Real-Time Signal Filtering for high-intent B2B Lead Generation. Instead of traditional batch scraping (which just extracts thousands of dead, messy contacts), I build custom parsers that clean and enrich data at the scraping layer itself before it ever hits an AI pipeline.
The result? A recent test showed a 40% improvement in token efficiency and zero hallucinations because the input data was strictly high-density.
I’m looking to connect with founders who are currently scaling their outbound sales or building data-dependent AI agents.
If you are struggling with messy data dumps, high API costs, or need hyper-targeted B2B leads that actually convert, let’s swap notes! Drop a comment below or feel free to DM me. Happy to look at your current setup and share some insights.
Totally agree. Clean context beats more context. We’ve seen the same with AI memory - high-quality, structured context not only cuts token usage but also gives LLMs much more reliable outputs. Garbage in, expensive garbage out. 🙂
This is incredible, also similar reasons I decided to launch my application.
That’s fantastic to hear! It sounds like we’re on a similar path. Launching an application comes with its own set of unique challenges, especially when it comes to infrastructure and data handling.
I’d love to hear more about what you're building. Are you also focusing on AI-driven automation, or is your application targeting a different niche? It’s always great to connect with fellow builders who are tackling these same hurdles.
Hello
Yes, my application is targeting automation, but it's also a high density AI Web OS featuring a 6-model Consensus check, Parasitic UI Engine, a secured Codex Vault with Workspaces and different filtering modes. Full browser, community network- (e.g. personalized profile setup, DM's, live chat, live video chat, WebRTC meetings, forums, group chats), and so many other design, research, and fun interactive features. The main purpose is to save people time and money from having to move from one application to another and paying multiple subscriptions when you should be able to do it all in one place for less. It's still fresh, working on some improvements, but its live and I'm very open to feedback. My updates I've been working on will be released today if you want to check it out - zelvaron . io