Vikasit AI

company

AI & ML interests

Core Focus Areas Open-source LLM development (efficient, deployable, and scalable) Fine-tuning small & mid-sized models (0.5B → 13B) for real-world use CPU-first AI (GGUF, quantization, edge deployment) Autonomous AI agents for business workflows (lead gen, SEO, automation) Specializations Programmatic SEO using AI (mass-scale content + Q&A generation) Multi-agent systems (Claude-style / tool-using agents) Self-hosted AI infrastructure (privacy-first alternatives to SaaS AI) RAG pipelines for knowledge-based products Tech Stack Interests Transformers, LoRA, QLoRA GGUF / llama.cpp ecosystem LangChain, LlamaIndex, custom agent frameworks Vector databases (FAISS, Chroma, Weaviate) Applied Use Cases AI for lead generation & outbound automation AI writers for blogs, tutorials, and documentation at scale Developer tooling & copilots AI-powered SaaS products for SMEs Exploration Areas Rebranding & productizing open models (e.g., Qwen-based ecosystems) Synthetic dataset generation at scale AI + SEO synergy (next-gen content engines) Ultra-low-cost inference systems