- The team spent significant time manually reading, reviewing, and extracting key data points from legal and claims documents.
- High volume and complexity meant errors were common and costly.
- Manual processing created delays in award determination, which directly impacted revenue operations.
- Scaling the process to match business growth was not feasible with the existing approach.
Cynoteck designed an AI-led document processing system that connects directly with the client's existing Salesforce environment.
Custom AI Prompts for Legal Documents: We built four tailored prompts within a Large Language Model (LLM) — each one trained for a specific type of legal document. This means the AI understands the context of what it is reading, not just the words.
Salesforce Integration via Logic Apps: We created an integration layer between Salesforce and OpenAI using Azure Logic Apps. Documents are pulled from Salesforce, processed by the AI, and the extracted data is sent back — all without manual intervention.
Accurate Data Extraction from PDFs: The system reads incoming PDF documents, identifies the required data points for award determination, and extracts them with high accuracy — automatically.
Automated Field Pre-Population: Salesforce records are now pre-filled with extracted data, cutting down manual data entry significantly and keeping the team focused on decisions rather than admin.
Reduced Manual Effort
The team now only reviews flagged exceptions and edits — not every document. Manual review efforts dropped by 80%.
High Accuracy from Day One
The system achieved 96% accuracy within the first month of going live — and maintained an overall error rate of just 0.5%.
Better Use of People
With routine document work automated, the team redirected their time to higher-value tasks that actually need human judgment.
