AI Engineering Services — RAG, Agentic Workflows & Private Knowledge Systems
We engineer AI systems that go beyond chatbots. From retrieval-augmented generation over private document sets to autonomous multi-step agents — we build, deploy and maintain production AI infrastructure on AWS.
RAG & Knowledge Systems
Private document RAG: PDFs, manuals and specs turned into searchable AI. Your internal knowledge becomes an assistant that answers with sources.
Multi-source knowledge bases with vector embeddings and hybrid search — semantic + keyword — for accurate retrieval across all your data.
Live case study: TT Assistant — defense tech manuals transformed into an AI support assistant used in production.
Agentic AI & Autonomous Workflows
Multi-step AI agents with tool use built on the MCP protocol — agents that plan, call your systems, and complete tasks end-to-end.
Automated decision-making pipelines that integrate with n8n, AWS Lambda and serverless infrastructure.
AI ops for affiliate and CPA networks — AIAffiliates as live proof: campaign data, reporting and routing handled by agents.
Our Tech Stack
We work with a production-proven AI stack — from model APIs to vector databases and cloud infrastructure.
Built for Production, Not Demos
LLMs: Claude API, OpenAI API, open-source (Llama, Mistral) · Vector DBs: Pinecone, Weaviate, pgvector · Frameworks: LangChain, LlamaIndex, CrewAI · Infra: AWS (Lambda, Bedrock, S3, RDS), n8n · Protocols: MCP (Model Context Protocol) · Frontend: Next.js, Vercel
LLMs & frameworks: Claude API, OpenAI API, open-source models (Llama, Mistral), LangChain, LlamaIndex, CrewAI.
Vector databases: Pinecone, Weaviate, pgvector — embeddings and retrieval tuned to your data.
Infrastructure & protocols: AWS (Lambda, Bedrock, S3, RDS), n8n, MCP (Model Context Protocol), Next.js + Vercel.
Everything is production-grade: monitored, versioned and maintained — CI/CD, observability and cost control included from day one.
Why we?
Upwork Top Rated Plus — Senior AI Engineer positioning, verified track record.
15+ RAG systems delivered — production-grade, not prototypes.
Full-cycle delivery: from discovery to deployment and ongoing support on AWS.
Bilingual team UA/EN — direct communication with engineers, no management layers.
Engineering-first approach: RAG, agentic workflows and data infrastructure that solve real business problems — not demo chatbots.
We emphasize clear communication on project status, deadlines, and costs, fostering long-term relationships based on trust.
