How InsightExtract Solutions Transformed Their Data Processing with llmcontrols.ai

Disclaimer: The following stories are fictitious and generated using AI; they represent potential implementations using LLM Controls, and may include elements under active development or to be jointly developed with customers

The Challenge

Emma, founder of InsightExtract Solutions, managed a team tasked with processing large volumes of unstructured data like invoices, contracts, and customer feedback. Their manual workflows were slow and error-prone, relying heavily on data entry clerks to pick critical details from dense documents.

“We spent more time extracting data than actually analyzing it,” Emma explains. “Key information was hidden deep within unstructured formats, making insights slow to surface and workflows bottlenecked.”

Discovering llmcontrols.ai

Emma’s team discovered llmcontrol.ai as an automated information extraction system while searching for an AI platform that could automate key information extraction with full control and customization. Unlike rigid, rule-based tools, llmcontrol.ai provided a visual workflow builder with AI models that could understand context and structure, adapting to each client’s unique data and business needs.

“What attracted us was the flexibility to define custom extraction rules and the ability to output structured data ready for analytics,” Emma says. “The no-code interface meant we could prototype fast without needing specialized AI engineers.”

Building Their First Data Extraction Workflow

Emma’s team set out to eliminate manual data entry and accelerate document processing. Using llmcontrols.ai’s visual builder, they created their first Document Key Data Extractor, a workflow that automatically extracted essential fields from invoices and contracts.

The Setup:

They connected Document Ingestion component to handle PDFs and scanned files, configured AI Extraction Components to capture key entities like invoice numbers, vendor names, and payment details, and applied Flexible Extraction Rules to adapt to diverse formats. The workflow structures outputs into standardized JSON files compatible with client accounting systems.

After testing for accuracy across document types, InsightExtract expanded into Unstructured Text Insight Mining, using Natural Language Understanding Agents to analyze feedback and social posts for sentiments, key phrases, and trends. To enhance usability, they added Customizable Output Templates with JSON/CSV exports, API Integrations, and Schema Validation for clean, ready-to-analyze data.

The Result:

Processing times dropped from days to hours, while extraction accuracy and scalability improved dramatically. Analysts shifted from manual data handling to generating insights, empowering clients with structured, actionable information. With llmcontrols.ai, InsightExtract turned tedious data entry into a smart, automated pipeline for continuous value delivery.

Scaling Up: Unstructured Text Insight Mining

Buoyed by initial success, InsightExtract expanded to analyzing customer emails, feedback forms, and social media posts:

• Developed natural language understanding agents to identify sentiments, complaints, and feature requests
• Extracted named entities and key phrases to unlock hidden insights from unstructured text
• Customized extraction schemas per client to meet specific reporting and compliance needs

This multi-format extraction hub allowed clients to transform raw text into actionable intelligence.

The Game-Changer: Customizable, Structured Outputs

InsightExtract’s technical lead integrated llmcontrol.ai’s ability to define custom extraction templates and output formats:

• Added JSON and CSV export options tailored to client analytics stacks
• Enabled direct API integrations for seamless data flow into reporting dashboards
• Used schema validation to ensure consistent, high-quality extracted data

This structured approach accelerated client analysis, improved decision-making, and reduced integration friction.

The Impact

Emma’s team shifted from manual data handlers to insight enablers, freeing analysts to focus on higher-value tasks while ensuring data accuracy and speed.

Key benefits included faster document processing cycles, consistent high-quality data outputs, flexible customization per client, and improved scalability to handle diverse data sources.

Building Key Information Extraction Workflows for Every Client

Today, InsightExtract runs numerous custom-built extraction workflows in llmcontrols.ai, each tuned to client-specific data types and reporting needs. Their visual workflows can quickly adapt to new extraction targets and integrate seamlessly with client systems.

Want to build AI-Powered Key Information Extraction Workflows in llmcontrols.ai?

Whether you're struggling to pull critical data from complex documents or unlock insights hidden in unstructured text, we’ll help you design and deploy intelligent workflows that automate extraction and deliver data fit for analysis.

We partner with you to:

• Define custom extraction rules matching your unique data and business needs
• Build scalable workflows to handle diverse document formats and text sources
• Structure outputs for seamless analysis and integration
• Deploy production-ready systems integrated into your operations
• Train your team to evolve and expand AI extraction capabilities independently

Just like InsightExtract Solutions transformed their workflows, we’ll help you unlock faster, smarter, and more reliable information extraction.