Show HN: AI Agents for Osint/Sigint (www.makralabs.org)

In a recent announcement, developers unveiled a pioneering approach to AI agents for open-source intelligence (OSINT) and signals intelligence (SIGINT), forecasting a transformative future for web scraping by 2026. Given that 75% of the internet consists of dynamically generated content, challenges have arisen in retrieving data efficiently. The evolution began with retrieval-augmented generation (RAG) in 2024 and progressed through long-context language models (LLMs) that elevated data extraction capabilities. However, persistent issues such as rising costs, hallucinations, and context pollution hindered scalability. The new solution, dubbed 'Makra,' addresses these challenges head-on by utilizing memoization-driven knowledge and data retrieval. This innovative architecture allows for significant cost reductions as web page layouts are stored and reused, leading to more efficient queries. Makra not only minimizes hallucinations—common in LLMs—but also enhances data retrieval precision by focusing on relevant DOM nodes, improving the signal-to-noise ratio. With an in-house read-only browser harness that facilitates easy access to structured data, Makra delivers high-quality results at one-tenth the cost of previous technologies, marking a significant advancement for the AI/ML community in data acquisition efficiency.