AI Foundation

CodeBaby’s avatars utilize more than artificial intelligence, we use emotional intelligence, making it easier and more effective to serve your customers. At CodeBaby, we have a mission to create a tool that gives people access to complex, life-improving technologies while making them feel heard and understood. To do this we have layered emotional intelligence and artificial intelligence to make an accessible technology. Most of us are already pretty familiar with what a chatbot can offer to our online customers. How are avatars an improvement over the typical chatbot experience? Well, chatbots that are driven by Natural Language Processing (NLP) are already much more capable than traditional chatbots, and our avatars build on that existing advantage. By providing an audio option for communication, avatars broaden who can use a chat experience. Characters increase engagement over traditional chatbots or IVRs and lead to better understanding and retention of information.

Antares is a family of open-weight security small language models purpose-built to localize known vulnerabilities inside large codebases. Antares-350M and Antares-1B are compact enough to run locally or on premises, helping teams keep proprietary source code inside their environment while reducing inference cost and runtime. Starting from a vulnerability description, advisory, or CWE category, the model follows an iterative investigation process similar to a human analyst, it searches for relevant code patterns, reads candidate files, incorporates new evidence, changes direction when a path is unproductive, and narrows the search to the files most likely to contain the weakness. Antares returns a ranked list of potentially vulnerable source files together with the terminal exploration trace that produced the result, making findings easier to review and prioritize.