Lumina AI Inc.
Lumina AI Inc. builds Chunkr, document-ingestion and document-intelligence infrastructure that turns complex PDFs, office files, spreadsheets and images into high-quality, machine-readable data for RAG/LLM applications. Its goal is to give developers granular control over speed, quality and features without having to build document parsing in-house.
At a Glance
- AI and developer teams
- Financial services
- Legal and compliance
- Healthcare
- +5 more
AI Tools by Lumina AI Inc.
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Chunkr
Document Parsing API for RAG
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Latest News
Chunkr is joining Extend; hosted Chunkr API shutdown scheduled for November 15, 2026, with migration documentation
Introduced chunkr-layout-1, a production-ready document layout-analysis model
Introduced chunkr-parse-1 and chunkr-parse-1-thinking document-native VLMs
Released a guide and implementation pattern for granular PDF citations and in-answer images in RAG
Products & Services
Fully managed document parsing and extraction API using proprietary in-house models for production workloads; supports PDFs, presentations, Word documents, images and spreadsheets.
AGPL-3.0, self-hostable document-intelligence service for layout analysis, OCR, bounding boxes, semantic chunking and LLM/RAG-ready output; distributed through GitHub, Docker Compose and Helm.
Converts documents into structured HTML/Markdown and LLM-ready chunks with layout-aware segments, OCR, bounding boxes and metadata.
Fills custom JSON schemas from documents and returns structured values with segment/word/spreadsheet-range citations and confidence metrics.
Market Position
Chunkr positions itself against general document-AI and OCR platforms such as AWS Textract, Azure Document Intelligence, Gemini and open-source parsing stacks. Its differentiation is segment-level configurability, precise citations/bounding boxes, structured HTML/Markdown, custom schema extraction, self-hosting and proprietary in-house models for the cloud product; the company also reports that structured HTML outperformed direct image-based Vision RAG in its benchmark.
Leadership
Founders
Mehul Chadda
Co-founder and CEO; background in metrology and a BSc in materials engineering, with previous experience at CAMECA.
Ishaan Kapoor
Co-founder; previously worked at Lumina and Affinity Consulting Group LLC and focuses on document/vision data infrastructure.
Akhilesh Sharma
Co-founder and CTO; software/AI engineer who previously served as CTO of Lumina and worked on the Chunkr Rust infrastructure.
Executive Team
Mehul Chadda
Co-founder & CEO
Background in metrology and materials engineering; works on improving vision capabilities in models.
Ishaan Kapoor
Co-founder
Co-founder focused on document and vision-data infrastructure; previously worked at Lumina and Affinity Consulting Group LLC.
Board of Directors
Founding Story
The founders were initially building Lumina, an AI search engine for scientific literature, and needed an ingestion pipeline capable of processing about 600 million pages. Existing document-processing products lacked the performance, observability and features they needed, so they built parsing in-house; after spending substantial effort on foundational problems, they pivoted to productize that underlying document-ingestion challenge as Chunkr.
Business Model
Revenue Model
Usage-based credits for the hosted Parse and Extract APIs, sold through monthly subscription plans with overage charges; enterprise customers can buy custom solutions and on-premise deployments.
Pricing Tiers
25,000 included credits; $0.015 per overage credit; 99.9% SLA uptime.
75,000 included credits; $0.01 per overage credit; 99.99% SLA uptime.
250,000 included credits; $0.008 per overage credit; 99.99% SLA uptime.
Custom solutions, pricing and terms.
Target Markets
- AI and developer teams
- Financial services
- Legal and compliance
- Healthcare
- Government
- Education and research
- RAG and document-question-answering systems
- AI agents that reason over contracts, reports, spreadsheets and research papers
- Finance: invoices, bank statements and SEC filings
- Legal: contracts, evidence and regulatory compliance
- Supply chain: bills of lading, packing slips and purchase orders
- Healthcare and medical-record processing