Security starts with knowing where information comes from.
Our platform is engineered for enterprises where third-party dependency data is mission-critical. We believe in rigorous technical controls, verifiable evidence provenance, and total transparency about our security maturity.
Our Honest Commitment to Security Verification
We do not claim fabricated badges, premature certifications, or unverified SOC 2 / ISO 27001 logos. AccelFlowSystems is actively aligning its policies, cryptographic implementations, and vendor risk practices with established international security frameworks as part of our formal production roadmap. We welcome enterprise vendor assessments, architecture reviews, and direct technical due diligence from prospective security teams.
Six Security Principles
How we protect customer topology, prevent data leakage, and ensure every dependency graph query is auditable and defensible.
Data Protection
All client data is encrypted in transit using industry-standard TLS 1.3 protocols with forward secrecy, and encrypted at rest utilizing AES-256 bit encryption keys. Cryptographic keys are rotated systematically and managed in dedicated key vaults with strict hardware security perimeter isolation.
Access Control
Principle of least privilege is strictly enforced across every layer. Robust Role-Based Access Control (RBAC), multi-factor authentication (MFA) enforcement, and enterprise SAML 2.0 / OpenID Connect (OIDC) Single Sign-On allow organizations to manage permissions down to individual node and document levels.
Evidence Provenance
No orphaned claims or unverified assumptions. Every data point, risk rating, and dependency link rendered in the platform is cryptographically bound to its verified source document, contractual exhibit, or authoritative telemetry stream, establishing verifiable chain-of-custody for audit defense.
Auditability
Comprehensive immutable activity logging captures all authentication attempts, graph queries, relationship edits, document access events, and export actions. Audit logs can be streamed directly to enterprise SIEM/SOAR platforms for real-time security operations monitoring and retention compliance.
Data Minimization
AccelFlowSystems only requests and processes metadata and textual extracts necessary to reconstruct the dependency graph. We never require access to raw end-customer databases, consumer PII, or internal transaction payloads. Automated tokenization masks sensitive identifiers prior to ingestion.
AI Safety
Client data and proprietary contract documents are never transmitted to public model pools or used to train third-party foundation models. Automated extraction models operate in air-gapped tenant contexts with strict deterministic guardrails, preventing hallucinations and data poisoning.
Designed for multi-tenant isolation with zero cross-tenant contamination.
Graph topologies and documentary stores are segregated at the logical database partition and container runtime levels. Every graph traversal query enforces tenant identity barriers, preventing side-channel exposure across client environments.
- Isolated Memory Footprints: In-memory graph computations execute within isolated process boundaries.
- No Training on Customer Data: Uploaded master agreements and extraction parses are never fed into LLM pre-training weights.
- Continuous Vulnerability Scanning: Static analysis, dependency auditing, and container vulnerability scans execute on every build pipeline.
Responsible Disclosure & Security Inquiries
We welcome collaboration with independent security researchers and enterprise security assessment teams. If you believe you have found a vulnerability or require a formal security questionnaire, please contact our security team.