AI Strategy · Compliance Platform · Talent Transformation For OEMs & Tier Suppliers
AI-Powered · ISO 21434 · AIS-189 · UNECE WP.29 · SDV Compliance

Turn SDV Compliance into Your Competitive Edge

TARA and HARA used to take weeks. UnifyIQ's AI platform cuts that to hours — full ISO 21434 traceability, multi-agent automation, and human-in-loop validation. No shortcuts.

90%
Faster TARA delivery
95%
Vehicles connected by 2030
E2E
Lifecycle coverage
ISO/SAE 21434 UNECE WP.29 R155 AIS-189 ISO 26262 STRIDE / CIA
UnifyIQ — AI-powered security shield protecting a Software-Defined Vehicle inside a digital dome
Built for OEMs Tier 1 Suppliers Tier 2 Suppliers ISO/SAE 21434 Aligned UNECE WP.29 Ready Human-in-Loop Validated
⚡ The Burning Challenge
SDV Compliance is a Race Against Regulatory Time
As vehicles become software platforms, the threat surface explodes — and regulators aren't waiting. Every OEM and Tier supplier is under pressure to deliver watertight TARA and HARA documentation, fast.
Manual TARA takes months
Traditional threat analysis is labor-intensive, debate-prone, and can't keep pace with rapidly evolving SDV architectures and OTA update cycles.
Weeks → Hours
Regulatory deadlines are now
UNECE WP.29 R155 is active in key markets. Type approval and market entry are blocked without demonstrated CSMS compliance — no workarounds. India's AIS-189 is in effect for new type approvals. ARAI and ICAT require TARA traceability evidence in their own submission formats — not the generic R155 template.
WP.29 Active Now
Attack surfaces are exploding
95% of new vehicles connected by 2030. 97% of attacks are remote. Every ECU, OTA path, and V2X interface is a potential entry point.
97% Remote Attacks
Financial and brand risk is severe
Cybersecurity failures mean recalls, legal exposure, and destroyed consumer trust. A single breach costs far more than full CSMS compliance.
$Billions in exposure
Supply chain risk is hidden
Third-party software and hardware introduce vulnerabilities invisible to the OEM. Without systematic TARA across tiers, risk accumulates silently.
Multi-tier blind spots
Scale is impossible manually
Modern SDVs have hundreds of threat scenarios. Only automation can perform the repeated, function-level assessments required — human teams can't scale.
100s of threats/vehicle
The cost of delay is compounding. Every sprint without structured TARA is technical and compliance debt — and once regulators audit, there's no fast-forward button.
See how we solve this →

AI-Powered CSMS for the Software-Defined Vehicle

The only compliance platform purpose-built for Automotive SDV — combining fine-tuned AI agents, pre-built threat libraries, and full lifecycle traceability for TARA and HARA.

90%
Time reduction
E2E
Lifecycle coverage
Zero
False positives — SME validated

E2E TARA in hours, not weeks

AI-augmented threat modelling covers your full component topology — automatically inferring attack vectors and evaluating risk scores with unprecedented depth.

STRIDE / CIA taxonomy built-in

Pre-built threat libraries ensure strict architectural alignment and feature-level ISO/SAE 21434 compliance — no blank-sheet-of-paper problem.

Dynamic risk re-assessment

Post-production TARA updates triggered by OTA releases or new threat intelligence — compliance doesn't stop at launch.

Audit-ready documentation

Total asset-threat-risk-requirement traceability via graph-based engine. Full auditability across security and safety teams.

TARA workflow — automated
1
System Architecture Ingestion
ECUs, IVN topology, interfaces
2
AI Agent Threat Generation
STRIDE-based, multi-agent LLM
3
Risk Scoring & Impact Analysis
CVSS + automotive context
4
SME Validation — Human-in-Loop
Zero false positive policy
5
Audit-Ready TARA Export
ISO 21434 / AIS-189 — section-mapped, ARAI/ICAT-ready
ISO/SAE 21434UNECE WP.29Graph traceability

Hazard Analysis & Risk Assessment

AI-assisted HARA aligned to ISO 26262 — systematically identifying hazardous events, operational scenarios, and safety goals across the full vehicle system.

Unified safety + security view

Cyber-physical risk correlation — HARA and TARA linked in a single platform to surface threats where safety and security intersect (ADAS, LiDAR, sensor fusion).

ASIL allocation automated

Automatic ASIL decomposition and allocation to system elements — reducing manual back-and-forth between safety engineers significantly.

HARA workflow — automated
1
Item Definition & Scope
System boundary, functions
2
Hazardous Event Generation
AI-augmented scenario analysis
3
ASIL Classification
S, E, C parameters — automated
4
Safety Goals & Requirements
Linked to TARA findings
ISO 26262Cyber-physical linksASIL A–D

Continuous threat monitoring

Platform stays active post-production — re-running TARA on OTA update triggers and integrating new CVE and threat intelligence feeds automatically.

Residual risk tracking

Active monitoring of accepted residual risks with escalation triggers — never lose visibility into what's been accepted and why.

End-of-life compliance

Full documentation from concept to decommissioning — as mandated by ISO/SAE 21434. Every risk decision preserved and auditable.

Lifecycle coverage
Concept & Design
Initial TARA + HARA
Development & Integration
Continuous re-assessment
Production & OTA
Live threat intel integration
Decommission
Full audit trail preserved

Fine-tuned automotive LLMs

Purpose-built models trained on automotive threat intelligence — not generic AI repurposed for compliance. Deeper domain understanding, fewer irrelevant outputs.

Multi-agent reasoning framework

Specialised agents for threat generation, risk scoring, requirement mapping, and validation — working in parallel for speed without sacrificing precision.

Human-in-the-loop by design

AI generates; domain experts validate. Every TARA output is reviewed by automotive cybersecurity SMEs before it enters compliance documentation.

Graph-based knowledge engine

Assets, threats, risks, and requirements linked in a knowledge graph — enabling cross-reference, gap detection, and full traceability that spreadsheets cannot provide.

AI architecture layers
AI
Fine-tuned Automotive LLMs
Domain-specific threat models
Multi-Agent Orchestration
Parallel specialised reasoning
Knowledge Graph Engine
Asset-threat-risk-requirement links
SME Validation Layer
Human-in-loop — zero false positive
Multi-agent LLMFine-tuned modelsKnowledge graph

Three Ways We Accelerate Your SDV Journey

From compliance automation to strategic roadmaps to workforce transformation — UnifyIQ operates at the intersection of AI, cybersecurity, and automotive expertise.

01
★ Compliance Platform

HATARA — AI-Powered Compliance

ISO 21434 · TARA · HARA · Full Lifecycle

Our platform automates TARA and HARA delivery — combining fine-tuned AI agents with human expert validation to turn weeks of manual work into hours of audit-ready output.

ISO/SAE 21434UNECE WP.29STRIDEOEMs & Tier 1/2
Explore the platform →
02
AI Consulting

AI Catalyst — Strategic Roadmaps

UnifyIQ AI Catalyst · OEMs · Tier 1 & 2

We craft execution-ready AI roadmaps that balance strategic ambition with tactical delivery — grounded in deep automotive domain expertise. From where to start, to how to scale.

Roadmap designUse-case prioritisationAI governanceROI framing
Talk to our consultants →
03
Talent Transformation

AI Upskilling — Every Level

CxO · Mid-management · Embedded · AI for All

Tailored AI learning journeys for automotive organisations — from C-suite AI literacy to hands-on embedded engineering. We build the internal muscle for continuous AI adoption.

CxO leadershipBusiness teamsEmbedded engineersAI fundamentals
Explore programmes →

A Rare Intersection of Four Deep Domains

Our unique expertise intersection
Artificial Intelligence
Fine-tuned models · Multi-agent systems · LLM engineering
Cybersecurity
TARA · CSMS · Threat intelligence · STRIDE
Automotive / SDV
OEM & Tier expertise · ECU · IVN · ADAS · V2X
Data & Engineering
Knowledge graphs · Pipeline architecture · Analytics
Combined, these domains create capabilities no single-domain vendor can match

Purpose-built, not repurposed

HATARA is not a generic compliance tool with an AI add-on. It was designed ground-up for automotive threat analysis — with models trained on automotive threat intelligence.

Speed without sacrificing rigour

Our AI-first approach delivers 90% time reduction — but human SME validation ensures every output meets the accuracy bar that ISO 21434 and WP.29 audits demand.

From compliance hurdle to growth engine

We help clients move beyond treating compliance as a cost — building it as a competitive differentiator that accelerates market entry and builds stakeholder trust.

End-to-end across the OEM ecosystem

We work across OEMs and Tier 1/2 suppliers — delivering consistent compliance frameworks across the full supply chain, not just at one tier.

Strategic + tactical, simultaneously

Our AI Catalyst consulting gives you the roadmap. Our platform gives you the execution. Our talent programmes give you the internal capability. No gaps.

ISO/SAE 21434 alignedEvery output maps to standard
Rapid time-to-valueFirst TARA session in days
Automotive SMEsHuman validation built in
OEM + Tier 1/2 readyScales across supply chain

Insights for Automotive AI Leaders

Practical intelligence on SDV compliance, AI strategy, and cybersecurity engineering — from our team of domain experts.

View all insights →
Key Questions — SDV Compliance & AI AEO optimised
What is TARA and why is it mandatory for automotive OEMs? +
TARA — Threat Analysis and Risk Assessment — is a structured methodology required by ISO/SAE 21434 for identifying and evaluating cybersecurity threats in vehicle systems. It is mandatory for type approval under UNECE WP.29 R155, which is active in the EU, Japan, South Korea, and other major markets. Without a documented TARA process, vehicles cannot achieve regulatory approval for market entry.
How does AI automation improve TARA delivery without compromising compliance accuracy? +
AI-powered TARA uses fine-tuned language models to generate threat scenarios across system architectures — covering attack vectors a human team might miss. The key to compliance accuracy is human-in-the-loop validation: every AI-generated scenario is reviewed by automotive cybersecurity SMEs before it enters documentation. This combination delivers 90% faster delivery without sacrificing the rigour that auditors and regulators require.
What is the difference between TARA and HARA in automotive safety? +
TARA (Threat Analysis and Risk Assessment) addresses cybersecurity threats under ISO/SAE 21434. HARA (Hazard Analysis and Risk Assessment) addresses functional safety hazards under ISO 26262. In Software-Defined Vehicles, these disciplines must be integrated — cyber attacks can directly cause safety hazards, such as adversarial manipulation of ADAS sensor data leading to loss of vehicle control.
What does a CSMS need to include for WP.29 compliance? +
A CSMS for WP.29 R155 compliance must cover: cybersecurity policies and processes, risk management across the vehicle lifecycle, TARA documentation, supply chain security controls, incident response procedures, and evidence of continuous monitoring post-production. Type authorities assess CSMS evidence during the approval process before issuing a Certificate of Compliance. In India, ARAI and ICAT serve as type approval authorities under AIS-189.
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