AI engineering service

RAG and Knowledge Assistant Build

A knowledge assistant over documents, support content, policies, or internal knowledge with grounded answers and useful UI/API access.

2-4 weeksRAG prototype or MVP

Outcome

A working knowledge assistant with content ingestion, retrieval design, answer generation, source-aware responses, a usable API/UI, and documented limitations.

01

Make internal knowledge easier to use

Internal documentation assistant

02

Reduce repeated manual answers

Support knowledge base assistant

03

Ground answers in source material

Sales enablement assistant

04

Create a base for future agent workflows

Policy or process assistant

What you receive

  • Content ingestion flow
  • Retrieval implementation
  • Assistant API
  • Frontend or admin interface
  • Evaluation notes
  • Limitations and improvement plan

Methodology

  • Review content and user question patterns
  • Design ingestion and retrieval approach
  • Build retrieval and answer generation flow
  • Add source/context handling
  • Test against realistic questions
  • Document limitations and next improvements

Scope

Includes one knowledge domain, document/content ingestion, chunking approach, embedding/retrieval setup, answer generation flow, API or simple frontend, source references where possible, and evaluation notes. This is not a guarantee of perfect answers and does not include large-scale enterprise search unless scoped separately.

Details

What to expect from this engagement

What is included?

I build RAG-style assistants that ingest content, retrieve relevant context, and answer with grounded responses. The focus is making internal knowledge usable through an assistant, API, or product interface.

Who is it for?

Teams with documents, support content, policies, or internal knowledge that they want to operationalize.

What do you need to provide?

Requires sample documents/content, expected user questions, access rules, preferred model/provider, and examples of good answers. Does not include cleaning a large unstructured knowledge base or complex permissions unless scoped separately.

Next step

Turn this into scoped AI engineering work.