Applied AI Engineering

Vigilant AI Knowledge Engine

An AI knowledge platform for document retrieval, semantic search, structured analysis, and workflow automation.

The Challenge

AI needs context, control, and repeatability.

General-purpose AI systems are powerful, but organizations often need answers grounded in defined knowledge sources rather than relying entirely on a model's internal training. They may also need those results delivered through applications, structured APIs, and repeatable workflows.

The Approach

Treat the model as one component of the system.

Vigilant AI combines AI inference with controlled knowledge retrieval, source validation, APIs, and workflow automation. Instead of relying only on a model's internal knowledge, the platform retrieves current information from defined data sources and produces structured, traceable outputs.

Architecture

How the system works

User / Workflow
       │
       ▼
      n8n
       │
       ▼
    FastAPI
       │
       ▼
Retrieval Engine
    /       \
   ▼         ▼
Ollama     Qdrant
Local AI   Vector DB
              │
              ▼
       Knowledge Sources

Capabilities

From retrieval to automated action

Natural-language document search

Semantic vector retrieval

Multi-source knowledge retrieval

Custom AI inference

Source-backed analysis

Structured response generation

Retrieval validation

REST API integration

Workflow automation

Technology

Engineering stack

PythonFastAPILinuxDockerQdrantOllaman8nREST APIsVector EmbeddingsSemantic Search

Engineering Work

Built as an operating technical environment.

Development includes Linux service deployment, containerized infrastructure, vector database integration, local language and embedding models, Python retrieval services, FastAPI endpoints, multi-collection search, document ingestion, metadata processing, workflow orchestration, and retrieval validation.

Status: Active engineering and technical portfolio project.