Ctxfy is a Context State Engine that compresses LLM conversation history by up to 95%. It strips chit-chat and redundancy, preserving only "Hard State" — decisions, constraints — into a portable State Object and Artifacts - code, schemas, etc. Drop it into any model as a system prompt, inject it into agent loops, or fast-forward it with new diffs and logs. REST API, model-agnostic, zero-retention mode available.see more
Founder
Screenshots
About
Imagine finally conquering the chaos of long, sprawling Large Language Model conversations. We all know the frustration: your AI assistant starts brilliantly, but as the dialogue deepens, performance degrades because the model is drowning in unnecessary preamble, polite acknowledgments, and repeated clarifications. Contextify, or ctxfy.com, is engineered to solve this fundamental scaling problem. It acts as an intelligent memory filter, meticulously analyzing your entire interaction history and distilling it down to only what truly matters: the 'Hard State.' This means stripping away up to 95% of the conversational fluff—the chit-chat and redundancy—leaving behind only the crucial decisions, established constraints, defined parameters, and critical facts that drive the actual work. What you are left with is a compact, highly potent State Object that represents the absolute essence of your session, ready to be redeployed instantly.
This portable State Object is your new superpower for maintaining consistent, high-quality AI interactions across any platform. Instead of feeding gigabytes of old chat back into the prompt window, you simply drop this optimized artifact directly into a new model session as a robust system prompt, instantly bringing the AI up to speed with zero ramp-up time. For developers building complex agentic workflows, Contextify integrates seamlessly. You can inject this distilled state directly into agent loops, ensuring that every subsequent action is grounded in the established context without bogging down processing speed or incurring massive token costs. Furthermore, Contextify supports efficient updates; if your context changes slightly, you don't need to restart from scratch—just feed in the new logs or diffs, and the engine updates the state intelligently, keeping your workflow agile and responsive.
Built with flexibility as a core principle, Contextify offers a clean, accessible REST API, making it model agnostic. Whether you are working with GPT, Claude, Llama, or any other leading LLM, this engine functions as a universal context layer that enhances performance regardless of the underlying technology. For organizations with stringent privacy requirements, the zero retention mode offers complete peace of mind, ensuring that your sensitive conversational context is processed and returned without ever being stored on our servers. Contextify isn't just about saving tokens; it's about unlocking the true potential of LLMs by giving them perfect, efficient memory, allowing you to scale complex projects reliably while keeping your operational costs predictable and your AI interactions sharp from the very first turn.