Before
- Teams manually extract data from documents, images, and scanned forms — slow and error-prone.
- Legacy OCR/RPA systems break when document formats change or if the layout is non-standard.
- Difficulties in handling handwritten text, nested tables, multi-page contracts, or noisy scans.
- Data sits in silos; no real-time integration into decision systems or business processes
After
- Seamless extraction of data from PDFs, images, handwritten notes, and unstructured text using GenAI and Deep Learning.
- Learns new formats on the fly; no hardcoding needed for every document type.
- Understands context across multiple document types; 90%+ precision.
- Real-time data flow via APIs — enabling faster decision-making and better compliance
Benefits
Reduction in processing time
75%
Accuracy in Data Extraction
95%
Cost savings on operations
60%
about us
Features
Document Insights
- Utilize NLP and computer vision to identify key fields, entities, and layout structures.
- Train models on historical documents for context-aware extraction (e.g., identifying policy numbers, addresses, medical codes).
- Implement feedback loops to improve extraction accuracy over time
Document Insights
- Enable users to ask questions like “Show claims over ₹10L where discharge summary was missing”
- Automatically generate dashboards from extracted document data.
- Visualize extracted insights in real-time, filtered by department, document type, or location
Advanced Document Intelligence
- Summarize long documents (e.g., contracts, KYC reports) into key decision points.
- Automatically classify document types and extract custom fields using prompt-driven models.
- GenAI co-pilot suggests next steps (e.g., “This document lacks PAN validation ”)
Comparison: Traditional RPA vs Mira.ai
Feature
Traditional RPA
Mira.ai
Technology
Rule-based automation, limited to predefined templates.
AI-native, powered by NLP, OCR, ML, and LLMs.
Document Types
Works only on structured or semi-structured documents.
Supports structured, semi-structured, and unstructured (PDFs, images, handwritten, scanned docs).
Scalability
Requires heavy maintenance and scripting for each document type.
Scales effortlessly with continuous learning and auto-adaptation.
Accuracy
~60–70% (breaks with format changes).
90%+ accuracy with real-time self-correction and feedback loop.
Customization
Hardcoded logic; needs developers for every change.
No-code/low-code interface with smart field mapping and auto-training.
Integration
Disconnected from downstream systems.
Seamless integration via APIs into enterprise apps, workflows, and decision engines.
Cognitive Capabilities
None – no understanding of context or intent.
Context-aware extraction, validation, and auto-classification using GenAI.
Time to Deploy
Weeks to months per document type.
Days with pre-trained document models and template-free onboarding.
Maintenance
High – breaks with minor document changes.
Low – self-learning engine adjusts to format shifts over time.
Use Case Coverage
Limited (e.g., invoices, forms only).
Wide (loan apps, contracts, claims, KYC, onboarding, legal docs, etc.).
Ready to Connect? Let’s Talk!
We’re here to listen and excited to explore how we can work together.
