Snapshot 222742

Document
Security page
URL
https://ninchi.ai/en/security
Fetched
HTTP status
200
Content type
text/html; charset=utf-8
Fetch mode
static
Size
83914 bytes
SHA-256 (raw)
658137059dad0f450f413515d19facf574bf36d9026232a55f96ecfbf4d61377
SHA-256 (normalized text)
45f5939c19cbed977d0561dd860387dd78f1bae358f5a535398b991bdc83f7c4

Normalized text

Scripts and page chrome removed; this is what change detection compares.

Legal
Data Handling & Security
Last Updated: August 2026
Core Philosophy
Insight-Aware, Not Data-Retentive: We prioritize extracting human understanding and organizational knowledge over the long-term retention of your raw information.
Transient Processing: We interact with your data only when necessary to perform analysis. Repository context is processed transiently; manually submitted challenge text may be retained with the challenge record.
Definitions
Source Identifiers
The repositories and development tools that you explicitly connect to Ninchi. LMS and document-workspace integrations are not currently available.
Source Data
Repository context that Ninchi analyzes, plus supported plain-text or code excerpts that an authorized user manually submits. Native PDF, DOCX, LMS, and cloud-document ingestion are not currently available.
Derived Information
Proprietary analytics (e.g., Ninchi Scores, knowledge maps) created by our engine that do not contain raw Source Data.
How Ninchi Works
Trigger: A supported repository change occurs, or an authorized user manually submits a supported text or code excerpt.
Analysis: The system securely accesses the relevant Source Data subset to generate context-aware questions or evaluations.
Response: The assigned user provides an answer.
Evaluation: Ninchi evaluates the response against the current context.
Retention: Repository context is processed transiently. Manually submitted challenge text may be retained with the challenge record.
What We Do NOT Store
Full connected repository contentsRaw file versions or historical repository snapshotsPII beyond necessary account identifiers
What We DO Store
Manually submitted challenge textQuestions & responsesEvaluation scores & qualitative feedbackMetadata (content type, complexity, difficulty)Proprietary analytics (Ninchi Score, knowledge maps)
Security & Compliance
SOC 2 Type 1: Ninchi has completed a SOC 2 Type 1 attestation. Our compliance posture is continuously monitored with Vanta and Drata, and audit logs and compliance metadata are reviewed to verify our internal controls. A SOC 2 Type 2 observation period is underway; we do not claim Type 2 attestation until that engagement completes.
Prospective enterprise customers may request access to the SOC 2 Type 1 report via our Trust Center (access is gated and reviewed). For help, email support@ninchi.ai or book a call. The report is managed in Vanta and is not published as a public download.
Infrastructure
Encryption in transit (TLS) and at rest (AES-256)
Secure cloud infrastructure (AWS) with strict access controls
Private networking for backend services
Secure secret management and least-privilege service accounts
Enterprise Deployment: Dedicated deployment options, including dedicated VPCs and isolated tenant environments, can be arranged under an Enterprise agreement to satisfy strict data residency and egress requirements.
AI & Model Usage
Zero-Training Pledge: We do not train external AI models (including foundational or third-party models) on any customer Source Data.
Data Siloing: Your data is never shared across organizations. Analysis is strictly focused on patterns and understanding within your specific environment, not on proprietary logic transfer.
Proprietary Analytics
Ninchi Score: A transparent, difficulty-weighted record of demonstrated understanding. It is Derived Information — a summary of verified interactions with your organization's work, not a measure of anyone's ability or intelligence, and not a copy of your raw input.
Knowledge Maps: Visual representations of organizational understanding. These are generated from aggregated metadata and contain no raw Source Data.
Designed for Trust
Our architecture is built on a "minimal retention" model. By focusing on verified human understanding rather than raw data storage, we ensure that your intellectual property remains under your control while providing the actionable insights needed to scale your organization.
Contact / Support
For security inquiries, contact us at privacy@ninchi.ai.
Data Handling & Security · Ninchi