I will integrate agentic ai into your workflows

Integrate LLMs into your workflows from simple document search using RAG to connecting to existing tools to automate your existing workflows and improving them where possible.

• Build Agentic Workflows: Construct multi-agent systems, autonomous loops, and tool-calling architectures using frameworks like LangChain, LlamaIndex, or the Model Context Protocol (MCP).
• Advanced Prompt Engineering: Design structured prompts, few-shot templates, and chain-of-thought logic that elicit reliable, deterministic outputs from large language models.
• State & Memory Management: Implement conversational history, short-term session state, and long-term memory retrieval for context-aware applications.
• Advanced Data Ingestion & Chunking: Build robust ETL pipelines to clean, chunk, and structure unstructured documents (PDFs, codebases, databases) for semantic indexing.
• Vector Database Management: Integrate and optimize vector stores (e.g., pgvector, Pinecone, Milvus, Chroma) for low-latency similarity search.
• Hybrid Search & Reranking: Combine semantic (vector) search with keyword (BM25) search, and implement rerankers (e.g., Cohere Rerank) to drastically improve retrieval precision.