Jinba
Product & Competitive Intelligence
Lets enterprises build secure AI workflows through chat interfaces in regulated industries.
Company Overview
Builds a secure, AI-powered enterprise workflow automation platform that lets users create, deploy, and manage complex workflows through natural language chat interfaces, visual editors, and API/MCP deployment, targeting Fortune 500 clients in regulated industries.
Competitive Advantage & Moat
Product Roadmap & Public Announcements
Jinba has publicly launched Jinba Flow (chat-to-flow workflow builder) and Jinba App (execution environment for business users), with 100+ pre-built connectors, SOC II compliance, on-prem/private cloud hosting, SSO, RBAC, audit logging, and MCP server deployment. Pricing tiers from Free through Enterprise with dedicated engineer support. Expanding into Tokyo for APAC sales and engineering.
Signals & Private Analysis
Job postings for "Forward Deployed Engineers" in SF and Tokyo signal active enterprise onboarding with Palantir-style land-and-expand motion. Hiring for "Founding Design Engineer" with canvas editor expertise suggests major visual workflow builder overhaul. Provider-agnostic LLM architecture (OpenAI, Anthropic, Azure AI, private models) positions them to upsell model hosting. Tokyo expansion hints at early traction with Japanese financial institutions and manufacturers.
Product Roadmap Priorities
Natural language chat interface that converts plain English descriptions into production-ready, enterprise-grade automation workflows with integrated connectors and compliance controls.
You describe what you want automated in plain English, and the AI builds the entire workflow for you — like telling a really smart intern exactly what to do and having it done instantly.
It's like having a universal TV remote that you program by just saying "record all my shows on Tuesday" instead of reading a 50-page manual.
RAG-powered compliance layer that automatically validates AI-generated workflows against enterprise security policies, regulatory requirements, and data governance rules before deployment.
Before any AI-built workflow goes live, a compliance AI double-checks it against your company's security rules — like a spell-checker, but for regulatory violations.
It's like having a building inspector review your renovation plans before you knock down any walls — except this inspector reads every regulation ever written in milliseconds.
Publishes approved workflows as Model Context Protocol (MCP) servers, enabling AI agents and LLMs across the enterprise to discover, invoke, and chain workflows as contextual tools — creating a self-service automation mesh.
Your approved workflows become tools that any AI assistant in the company can automatically find and use — like giving every department access to the same well-organized toolbox.
It's like turning every recipe your company has ever perfected into a menu item that any chef in any kitchen can order and serve — without having to learn how to cook it themselves.
Company Overview
Key Team Members
- Shoya Matsumori, Founder & CEO
Founder Force Multiplier
Jinba's separation of "build" (Jinba Flow) and "run" (Jinba App) environments creates an enterprise governance layer that competitors like Zapier and Make lack, letting compliance teams approve workflows before business users execute them via chat. Combined with provider-agnostic LLM hosting, on-prem deployment, and MCP server publishing, they offer a uniquely secure AI automation stack for regulated industries.
Funding History
- 2025 | Shoya Matsumori founds Carnot Inc (Jinba).
- 2026 | Accepted into Y Combinator Winter 2026 batch.
- 2026 | Launches Jinba Flow and Jinba App with 100+ connectors.
- 2026 | Expands hiring to Tokyo for APAC go-to-market.
Competitors
- No-Code/Low-Code Automation: Zapier, Make (Integromat), n8n, Tray.io.
- Enterprise Workflow: ServiceNow, Microsoft Power Automate, UiPath.
- AI-Native Workflow: Relevance AI, Respell, Lindy.ai, Cassidy.
- Chat-Based Automation: Moveworks, Aisera (IT-focused conversational AI).
