Cognica Blog

Modern search systems struggle to combine lexical matching with semantic understanding. We explore how we built a probabilistic ranking framework in Cognica Database that transforms BM25 scores into calibrated probabilities, enabling principled fusion of text and vector search results.

The essential infrastructure that makes Copy-and-Patch JIT development and debugging practical. We explore the multi-architecture disassembler for validation and software CPU emulator for cross-platform testing and debugging.

How Cognica Database Engine breaks the JIT compilation latency barrier. We explore Copy-and-Patch JIT compilation, a technique that achieves 2-10x speedup over interpretation while keeping compilation time under one millisecond per kilobyte of bytecode.

We discuss why NOT operations are difficult in vector search.

We propose a new approach to LLM usage by momentarily reconstructing the context.

We know that terms like big data, data lakes, and web-scale are fancy and attractive, but those are only everyday issues for very few of us. Most companies will never deal with the petabytes scale of the data. Let's be practical and stay on the ground. Most companies just need a simple but powerful database system to solve real problems. We are here to build a product for most companies, not just for unicorns. Our mission is to solve the common problems often associated with existing database systems and simplify software development by keeping your software stacks as simple as possible.