WHY KAVACH
Why KAVACH Exists.
Automotive cybersecurity engineering has outgrown disconnected spreadsheets and static documents. KAVACH was built to make ISO/SAE 21434 analysis architecture-aware, traceable, reviewable, and practical for real engineering teams.
THE SHIFT
From Document-Driven Analysis to Architecture-Aware Engineering.
Manual / disconnected approach
- ×Architecture context captured separately
- ×Assets and threats manually copied into spreadsheets
- ×Attack paths depend heavily on analyst memory
- ×Traceability is reconstructed later
- ×Evidence quality varies across projects
KAVACH approach
- ✓Analysis starts from the modeled architecture
- ✓Assets, damage scenarios, threats, attack paths, and controls stay connected
- ✓AI assists with coverage and consistency
- ✓Engineers review and approve the outputs
- ✓Evidence is built as the work progresses
CORE DIFFERENTIATORS
What Makes KAVACH Different.
Architecture First
KAVACH reasons from ECUs, interfaces, communication paths, trust boundaries, and vehicle context.
Automotive-specific
KAVACH is designed for automotive cybersecurity, not generic IT threat modelling.
Evidence Connected
Outputs remain linked across the cybersecurity workflow, helping teams review and justify decisions.
Engineer Controlled
AI accelerates analysis, but final engineering judgment stays with the responsible team.
Reviewable by Design
KAVACH outputs are intended to be reviewed, edited, justified, exported, and discussed in engineering reviews — not treated as black-box AI conclusions.
KAVACH is not a black-box AI decision engine. It is a structured workspace for engineers to review, edit, approve, and justify cybersecurity evidence.
BY THE NUMBERS
KAVACH at a glance.
Automotive Threat Scenarios
Reference Document Corpus
ISO/SAE 21434 Work Products generated
Faster TARA cycle (pilot-reported)
FAQ
Common questions about KAVACH.
Score KAVACH against your own architecture.
Sixty minutes, your system, our team in the room. We walk through citation provenance under your evaluation corpus, the deployment options that fit your data-residency clauses, and the integrations your toolchain demands.