Amsterdam · Working with clients worldwide
AI agents and RAG development
Help your team find answers in business documents and act on them. FlowboticsAI builds AI agents and retrieval augmented generation (RAG) systems around your data, permissions and existing tools.
Discuss your projectWhen a RAG system is useful
Your team may spend too long finding an answer across PDFs, internal documents or support material. A RAG application retrieves relevant passages before generating an answer, so the user can inspect the supporting sources. An AI agent can also call approved tools to investigate a transaction or complete a defined workflow.
Start with your documents and real questions
The first paid milestone can test a representative set of documents against questions your users actually ask. We agree what a useful answer looks like, which sources each user may access and when the system should say it lacks enough evidence. That gives you a basis for deciding whether to expand the build.
Choose the stack around the requirements
Implementation can use OpenAI and pgvector, a Python or FastAPI application, or Amazon Bedrock. The choice depends on your existing infrastructure, access controls, document formats and operating costs. Retrieval, source display and tool permissions need testing alongside the language model. RAG can improve grounding, but it does not make every generated answer correct.
Relevant work
For Emagination Cloud, the team built a Bedrock operations agent that queries Parquet data through Athena and investigates failures using S3 debug logs. The client owned the frontend and production deployment. Separate portfolio work includes a FastAPI document Q&A application with visible sources and a healthcare RAG proof of concept using synthetic data. These demonstrations are labelled separately from paid client delivery.
Explore the Google Drive document Q&A demonstration, including the source-quotation and new-document examples.
What we scope together
A project can cover document ingestion, retrieval, answer generation, source links and connections to business tools. Before implementation, we agree the evaluation questions, access rules, refresh process and handover responsibilities. Existing systems can start with a retrieval-quality diagnostic rather than a complete rebuild.
Do I need to move to AWS?
No. The service covers non-AWS stacks as well as Amazon Bedrock. We choose the approach after reviewing your data, systems and delivery requirements.
Discuss a first milestone
Work directly with Rajiv Unnikrishnan, founder of FlowboticsAI in Amsterdam. Start with a 30-minute discovery call to discuss the work and scope a paid next step.