Beyond the Hype: Why Mira is the Backbone of AI Success

AI assistants like Microsoft CoPilot and ChatGPT are rapidly gaining capability. They can generate text, answer questions, and analyze documents at a level that would have been unthinkable just a few years ago. But in complex business environments, there is one crucial difference: the journey from raw, unstructured data to usable, reliable insights is much longer than simply “asking AI a question.” That’s exactly where Mira’s strength lies.

Mira is not a generic AI chatbot, but a specialized Intelligent Document Processing (IDP) platform that lays the foundation on which tools like CoPilot and ChatGPT truly become valuable.

1. Modular Approach – Enhance Only Where Needed

Where CoPilot and ChatGPT often work as an all-in-one environment, Mira seamlessly fits into your existing processes. You don’t replace entire systems—you strengthen only the weakest links.

• Activate only the modules you need (e.g., digital mailroom automation, HR data migration, handwriting recognition).
• Work directly within your existing infrastructure without workflow overhauls.

Result: minimal disruption, maximum impact.

2. Advanced Preprocessing for Unmatched Accuracy

Generative AIs rely on the input they receive—and that’s often where things go wrong. Poorly scanned documents, incomplete metadata, or inconsistent formats lead to misinterpretations.

Before AI even comes into play, Mira takes care of:

• Cleaning and structuring raw data.
• Correcting OCR errors and optimizing image quality.

Result: higher precision in extraction and analysis than with an AI tool alone.

3. Context Handling – Not “Better Search” but Better Prepared Data

Copilot, ChatGPT, and Mira all use the same search building blocks: vector search (to understand meaning) and keyword search (for exact matches). The difference isn’t in the search technology itself — it’s in how and where they apply it.

• Copilot works mainly inside the Microsoft 365 environment (Teams, SharePoint, Outlook, Office…). It uses generative AI to help you write, summarise, and analyse the content you already have there.
• ChatGPT can handle any content you feed it, and can perform similar tasks — often with more flexibility — but it doesn’t automatically connect to your organisation’s protected data unless you set that up.
• Mira can use the same AI models (OpenAI or others, in the cloud or fully on-premise) but is built to pull from many different sources — including legacy systems, scanned PDFs, images, and handwritten documents — and to clean, enrich, and structure that data before search or AI even touch it.

The key difference: all three can “find” information, but Mira makes sure the information is clean, complete, policy-compliant, and ready for action — so the results are more reliable for automation, workflows, and decision-making.

4. NLP-Driven Workflow Automation – No Coding Required

CoPilot can offer suggestions, but it doesn’t build full data-processing workflows for you. Mira does:

• Describe your process in plain language.
• Mira automatically links extraction, validation, and migration steps together.
• Ready for execution without developer involvement.

Result: immediate automation of complex document flows, without technical barriers.

5. Flexible Deployment – Cloud or On-Premise

Where many AI assistants are cloud-first, Mira offers a choice:

• Cloud for scalability and speed.
• On-premise for maximum control and compliance in sectors like government, finance, and healthcare.

Result: your data stays exactly where you want it—critical for sensitive or regulated information.

Conclusion

CoPilot and ChatGPT are powerful generalists. Mira is the specialized backbone that ensures these AIs work with clean, structured, and contextually rich data. Rather than competing, Mira makes generative AI more relevant, reliable, and valuable in your business processes.

Whether it’s HR records, medical files, legal contracts, or logistics documents—Mira lays the foundation for AI success: from archive to insight, without searching.