How Enterprises Use AI to Solve Complex Data Challenges? | Smart Solutions

  • By : Nadim

🌐Introduction: Why AI for Data Matters

In today’s digital world, data is abundant, but insights are scarce. Enterprises across industries are buried under documents, PDFs, handwritten forms, and voice logs. Traditional systems can’t keep up. That’s where Artificial Intelligence (AI)—especially Large Language Models (LLMs)—come in.

At OnGraph Technologies, we specialize in transforming messy, unstructured data into clean, usable intelligence. We’ve done it for hospitals, venture capital firms, and legal departments—and we can do it for your enterprise, too.

🧠LLMs Alone Aren’t Enough — Orchestrating the Right Model Matters

Unlike most AI providers, we don’t rely on just one LLM. We use a multi-model orchestration system where:

  • Each query is analyzed by our custom-built algorithm.
  • The algorithm then selects the most appropriate LLM based on the task—be it summarization, extraction, classification, or reasoning.
  • Models used include GPT-4, Claude, Mistral, and open-source LLMs fine-tuned for specific domains.

This ensures cost-efficiency, speed, and higher accuracy—every time.

AI Use Cases

🏥 Use Case #1: AI for Hospitals & Healthcare

Hospitals deal with enormous volumes of unstructured data:

  • Scanned forms
  • Doctor notes
  • Lab test results
  • Insurance documents

Our Solution:

  • Extract data from PDFs and handwritten forms using OCR + LLMs.
  • Auto-summarize patient histories and discharge summaries.
  • Natural language search for patient information.
  • AI-led claim verification workflows.

🩺 Outcome: Almost real-time data extraction. A query like this gives real-time data – Female patients in the age-group of 40 to 50 years have diabetes and are taking a “specific medicine”. Earlier, this would have taken days to extract this data

💼 Use Case #2: AI for VC Firms & Investment Analysts

VCs are flooded with:

  • Pitch decks
  • Research reports
  • Interviews
  • Financials

Our Solution:

  • Extract key metrics (e.g., market size, revenue model) from decks and documents.
  • Summarize founder interviews via AI-powered transcription.
  • Generate internal investment memos automatically.
  • Benchmark startups using proprietary AI scoring.

📉 Outcome: The data extraction will take less than 2 hours in a specific format, which used to take more than a week. 

⚖️ Use Case #3: AI for Legal & Compliance Teams

Legal teams navigate:

  • Contract clauses
  • Case files
  • Compliance rules

Our Solution:

  • Parsed contracts for obligations, penalties, and compliance red flags.
  • Summarize legal documents in plain language.
  • Automate clause comparison and risk flagging.

⚖️ Outcome: Legal review time cut by over 50%, enabling faster deal-making.

 

Also read: 10 Ways How AI Will Improve Customer Experience

🧩 Horizontal AI Solutions for Any Industry

Besides building domain-specific AI systems, OnGraph also offers horizontal, reusable AI products that can be applied across industries.

✅ AI-based CRM (Customer Relationship Management)

  • Lead scoring with AI.
  • Smart follow-up generation.
  • Voice and chat summarization.
  • Intelligent pipeline management.

📞 AI Voice Chat Systems

  • 24×7 inbound/outbound AI agents.
  • Multilingual voice understanding.
  • Trained for logistics, real estate, health, and more.

🧠 Built using LLMs, ASR, TTS, and our custom orchestration engine.

💼 Why Leading Enterprises Work With OnGraph

✔️ Multi-LLM Orchestration for Precision

 ✔️ Expert Teams: AI Engineers + Domain Analysts

 ✔️ Affordable Projects

 ✔️ Transparent, Remote-First Engagement

At OnGraph, we build real, production-ready AI solutions that deliver outcomes.

📞 Let’s Turn Your Data Chaos Into Business Clarity

Whether you’re a hospital chain, VC firm, law practice, or growing business, AI can give you a competitive edge.

Let’s explore how AI can work for your enterprise.

👉 Connect with us on WhatsApp

📅 Schedule a free consultation

✅ Ready-to-Use or Built-to-Spec. We’ve Got You Covered.

About the Author

Nadim

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