RAG & Knowledge Tools
Source-grounded retrieval systems
Design and build retrieval workflows that turn documents and knowledge bases into usable AI systems with citations, evaluation, and operational checks.
Chunking, embeddings, retrieval, prompt assembly, evaluation
What You Get
Sample Systems
Document search and answer system
Internal knowledge assistant
Embedding and retrieval pipeline
Evaluation harness for answer quality
Timeline
Project-based
From system mapping to deployable software
How It Works
Workflow Map
Short call to understand the process, users, inputs, decisions, bottlenecks, and failure points.
Architecture & Scope
We define the data flow, model role, API boundaries, integrations, evaluation points, deployment path, and project quote.
Build
We implement the backend, workflow logic, AI components, interface, tests, and operational paths.
Deploy & Observe
We measure behavior, review failures, document the system, and improve it against real constraints.
Ready to build the system?
Let's discuss the workflow, constraints, and technical path.