Cinnamon AI: IDP Software Vendor
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Tokyo-based AI company offering Flax Scanner AI-OCR platform and specialized business AI agents for financial appraisal and knowledge management.
Overview
Founded in 2012 in Tokyo, Cinnamon AI has evolved from document processing into a two-product IDP stack: Flax Scanner HUB handles ingestion and extraction across unstructured forms; Super RAG handles downstream retrieval and analysis of the resulting content. Together they position the company as a full-stack IDP vendor rather than a point-solution OCR or RAG provider. The company serves over 50 enterprise customers - including Toyota, Sumitomo Pharma, Fujitsu, and Daikin - across four continents with approximately 119 employees. After raising $39M in Series C funding in April 2020 ($52.9M total), the company has expanded well beyond its original OCR roots.
In early 2026, CEO Miki Hirano articulated a strategic shift toward "process redesign" - emphasizing where AI should be applied rather than what it can do - and toward specialized business agents with limited, well-defined objectives. Hirano's appointments to Japan's Growth Strategy Council (November 2025), AI and Semiconductor Working Group (December 2025), and Drug Discovery Working Group (December 2025) embed the company within national AI policy development.
By February 2026, that strategy was visible in go-to-market moves: Super RAG expanded from an unspecified tier structure to three pricing tiers, adding a starter plan that opens the product to smaller buyers beyond the enterprise accounts it originally targeted. A new version of Flax Scanner HUB was also released, though no version string or benchmarks are publicly available. Trade-show density - AI Expo Osaka in January, Life-Work Balance EXPO Tokyo in February, Japan DX Week Nagoya in late February - signals a deliberate regional coverage push within Japan rather than international expansion in this period. At Osaka, the company actively recruited system integrators and BPO companies as reseller partners, suggesting an indirect channel is being built alongside direct enterprise sales.
All product claims in this period are vendor-stated. No third-party analyst coverage, independent benchmarks, or external pricing confirmation are available.
How Cinnamon AI Processes Documents
Cinnamon AI's document processing architecture separates ingestion from retrieval across two products.
Flax Scanner HUB handles the extraction layer using a three-engine architecture - coordinate-defined, feature-learning, and generative AI extraction - selecting the optimal method per document type. This distinguishes it from conventional coordinate-only OCR systems. The feature-learning engine requires no template creation, operating coordinate-free across industry documents, technical drawings, and photographic images. Processing speed is approximately 3 seconds per document. A no-code semi-automatic learning function allows teams to improve extraction without developer involvement.
Measured accuracy on financial documents: 92.99% character accuracy and 86.17% item-specific accuracy across 27 invoice items. On trade documents: 91% accuracy across 54 Commercial Invoice items, with automatic extraction of 50 Bill of Lading items.
Super RAG handles the downstream layer - retrieval and analysis of content already extracted or held in unstructured formats. The system is self-improving: it learns from queries against technical documentation, financial statements, internal regulations, and tacit-knowledge workflows. Cinnamon AI positions it against the 80% of enterprise data held in unstructured formats. As of February 2026, Super RAG is available across three pricing tiers including a new starter plan; no pricing figures are disclosed.
Financial Appraisal AI Agents sit above both layers, automating first and second appraisal processes in financial services with human oversight reserved for complex later-stage evaluations. These agents represent the company's clearest move into vertical-specific automation beyond document extraction.
Use Cases
Financial Services
Financial institutions deploy Cinnamon AI's Financial Appraisal AI Agents for automated first and second appraisal processes, with human oversight reserved for complex later-stage evaluations. Finance teams also use Flax Scanner HUB for invoice processing, achieving 92.99% character accuracy and 86.17% item-specific accuracy across 27 invoice items without template configuration.
Logistics and Trade
Logistics departments process shipping documents with 91% accuracy across 54 Commercial Invoice items and automatic extraction of 50 Bill of Lading items - both without coordinate-based templates.
Engineering and Knowledge Management
Engineering teams implement Super RAG against technical documentation repositories. The system learns from query patterns over time, improving retrieval accuracy on incident prediction workflows, equipment manuals, and tacit-knowledge capture. This use case extends Cinnamon AI's footprint from document extraction into ongoing knowledge management.
Pharmaceutical and Life Sciences
CEO Hirano's appointment to Japan's Drug Discovery Working Group (December 2025) signals emerging engagement with pharmaceutical document workflows, though no product deployments in this vertical are publicly documented as of February 2026.
Technical Specifications
| Feature | Specification |
|---|---|
| Core Products | Flax Scanner HUB, Super RAG, Financial Appraisal AI Agents |
| Extraction Engines | Coordinate-defined, feature-learning, generative AI (auto-selected per document type) |
| Template Requirements | None (coordinate-free extraction) |
| Processing Speed | ~3 seconds per document |
| Invoice Accuracy | 92.99% character, 86.17% item-specific (27 items) |
| Trade Document Accuracy | 91% (Commercial Invoice, 54 items); 50 Bill of Lading items auto-extracted |
| Super RAG Pricing Tiers | Three tiers including starter plan (figures not disclosed) |
| Deployment Options | Multi-tenant SaaS, single tenant, on-premise, private cloud |
| Integration | API support |
| Learning Function | No-code semi-automatic learning (Flax Scanner HUB); self-improving retrieval (Super RAG) |
| Third-Party Benchmarks | None publicly available as of February 2026 |
Resources
- Website
- Flax Scanner Product Page
- Flax Scanner HUB Platform
- Super RAG Platform
- AI Trends 2026 Analysis
- News Feed
- AI Expo Osaka 2026 Exhibit
- Pitch Video 1
- Pitch Video 2
For context on the OCR and RAG capabilities underlying these products, see OCR Technology and Agentic Document Processing. For Japanese-market alternatives with comparable OCR depth, see Cogent Labs.
Company Information
Headquarters: Tokyo, Japan (offices in US, Vietnam, Taiwan)
Founded: 2012
Founders: Miku Hirano (CEO), Hajime Hotta, Hiroaki Kitano, Mori Aki, Yoshiaki Ieda
Employees: ~119 (across 4 continents)
Funding: $39M Series C (April 2020), $52.9M total raised
CEO Hirano holds advisory positions on Japan's Growth Strategy Council and two working groups (AI and Semiconductors; Drug Discovery) as of late 2025 - appointments that give the company visibility into national AI procurement and regulatory direction.