RP AIA · an area of the work

Text AI

Text intelligence — any document, any format, Indian languages.

BUILDING
Text lives everywhere a machine still can't read it — inside images, in handwriting, across Indian languages and mixed scripts. Generic OCR stops at characters and breaks on Indian documents. Text AI turns any document — any language, any format — into structured, attributed, machine-usable meaning.
Text AI is the text-perception layer. Any document — PDF, image, handwriting — is detected, its text extracted, classified into domains, and attributed to a writer. It reads across Indian languages, turning raw documents into structured facts.
Manual data entry runs at 18–40% error. Text-AI-class extraction cuts a document from about 20 minutes to under 2, drops errors by 80–90%, and reads across Indian languages — turning typing into reading.
faster per document
20 min → <2 min
0%
fewer errors
up to 99% accuracy
0
Indian languages
Eighth Schedule
18–0%
manual entry error
Docsumo 2025
Manual entry 3 docs/hr
Text AI extraction 30 docs/hr
Dimension⊘ Manual entry✒ With Text AIGain
Time / documentcapture speed ~20 min <2 min ~10×
Error ratefidelity 18–40% ~1% 80–90% fewer
Cost, year 1operating cost baseline −60–80% major
Σ Coveragelanguages English-centric OCR Indian languages India-first

Market baselines for document automation, validated 2026-06-10; Text AI targets these as its India-first extraction layer.

Sources: Docsumo — IDP statistics 2025Mindee — IDP explained

🌱 Seed
Extract text from documents and images — OCR.
← shaped by the gap that off-the-shelf OCR fails on Indian scripts and real-world formats.
🛤 Path
Built the L1 perception module — detect → extract → classify → attribute, across PDF, image and handwriting.
← shaped by the stack principle — text perception is the foundation layer everything sits on.
🔀 Pivot
From OCR to language intelligence — not just the characters, but the language understood.
← shaped by the Computer Vision ↔ Text AI boundary — Computer Vision reads the text inside pixels, then hands the words to Text AI.
💎 Crystal
Text AI = the text (L1) layer of Voice AI, with India-first domain schemas.
← shaped by bottom-up architecture — Phase-1 facts are prerequisite inputs to Phase-3 intelligence.
⭐ Principle
Any document, any Indian language, any format → detected, extracted, classified, attributed, in real time.
← shaped by industry-agnostic document intelligence built for India first.
  • Extraction pipeline: format + language detection + OCR
  • Text classifier across 6 domains
  • Writer identification (LBP + SVM, closed-set)
  • Indian languages via Unicode matching + OCR
  • Conversational intake agent (Stage 0)
  • OCR optimization for local image processing
  • Authorship + authenticity layer
  • Cross-document entity linking
  • Feed structured facts into higher intelligence
★ the moonshot

Text understood to its deeper meaning — authorship, intent, authenticity — atop rock-solid multilingual extraction.

Imagine this working on your everyday tasks. The deepest how reveals itself when we build it together.

Build with me → See how it all fits — RARE
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