AI-Integrated Automation Services

Problem

Customers needed accurate data extraction from unstructured documents without fragile LLM pipelines or runaway costs.

Solution / Approach

Built a structured extraction pipeline using schema validation, deterministic post-processing, and fallback logic. Experimented with self-hosted Ollama to balance privacy, latency, and cost.

Architecture

• Extraction services with per-schema validation rules.
• Deterministic post-processing and error handling.
• Observability and cost tracking to keep runs predictable.

Key Features

• PDF/text to JSON structured extraction.
• Validation pipelines with retries and deterministic fallbacks.
• Cost/latency monitoring dashboards.

What I Learned

Reliable AI automation depends on deterministic steps around the model, not just prompt quality.