▶ LIVE● Safety Engine: ACTIVE · All Rules Loaded● 1,247 Vehicles Connected● DTC P0D17 · Active Alert · VIN IN-BLR-2847● Data Trust: 92.4% Confidence● API Gateway: p99 14ms · 99.97% Uptime● OTA Queue: 3 Staged · Awaiting Approval● Critical Fault · VIN IN-PUN-0392 · Motor Phase Imbalance● ISO 26262 V&V Gates: All Passed● AUTOSAR DEM: 2 Events Active● Predictive Alert: Battery SOH <85% · 11 vehicles · Action in 7 days▶ LIVE● Safety Engine: ACTIVE · All Rules Loaded● 1,247 Vehicles Connected● DTC P0D17 · Active Alert · VIN IN-BLR-2847● Data Trust: 92.4% Confidence● API Gateway: p99 14ms · 99.97% Uptime● OTA Queue: 3 Staged · Awaiting Approval● Critical Fault · VIN IN-PUN-0392 · Motor Phase Imbalance● ISO 26262 V&V Gates: All Passed● AUTOSAR DEM: 2 Events Active● Predictive Alert: Battery SOH <85% · 11 vehicles · Action in 7 days
📋
EV-SIP V2 — Executive Pitch Summary
This platform is an ISO 26262-compliant AI Advisory System — not a replacement for human judgment. Every AI recommendation is gated by a deterministic Safety Validation Engine, confidence-scored, risk-classified, and requires qualified technician sign-off before any repair action. Designed for Bosch SVP / OEM leadership review.
LIVE SYSTEM · PRODUCTION READY
EV Service Intelligence Platform
A domain-trained AI system purpose-built for EV diagnostics, predictive maintenance, and real-time service engineering — compliant with ISO 26262, AUTOSAR, and ISO/SAE 21434.
70%
FASTER DIAGNOSIS
40%
LESS DOWNTIME
~200ms
EDGE INFERENCE
ISO 26262 Advisory ASIL-B/QM
AUTOSAR CP/AP
ISO/SAE 21434
UDS ISO 14229
MQTT / OBD-II
LIVE TELEMETRY
Real-Time Vehicle Data Intelligence
Continuous telemetry ingestion via CAN bus, OBD-II, and BMS sensors. Anomaly detection runs at edge with cloud-sync every 500ms.
Data Confidence
92.4%
Sensors Active
14 / 16
Anomalies Detected
2
Missing Frames
0.3%
Validation Status
TRUSTED
DATA TRUST & VALIDATION MODULE · ISO 26262 §7.4.3
BATTERY VOLTAGE · PACK LEVEL
72.4V
↑ +0.2V from baseline
SOC (State of Charge)
84%
Cell Min / Max
3.62V / 3.68V
Cell Delta
0.06V NORMAL
Pack Temp
38°C
BMS Status
NOMINAL
MOTOR / INVERTER
3,480RPM
⚡ 1.82 kW output
Phase Current
24.1 A
Inverter Temp
54°C
Efficiency
91.4%
SYSTEM HEALTH
Throttle
42%
Speed
38 km/h
DTC Codes
2 Active
RUL Estimate
6,240 km
AI DIAGNOSTIC ENGINE · V2
Advisory AI + Safety Validation Architecture
Domain-trained LLM provides repair recommendations, not decisions. Every AI output passes through a deterministic Safety Validation Engine before reaching technician — compliant with ISO 26262 human-in-the-loop requirements.
Namaste 🙏 I'm your EV Service Intelligence assistant — advisory mode only. I'm reading live vehicle telemetry (VIN: IN-BLR-2847). Active DTC: P0D17 · Battery temp: 38°C. Ask me about any fault, or use the quick prompts below.
AI recommendations depend on data quality and must be validated by a certified technician before any repair action is taken.
Diagnostic Workflow
Animated step-through of AI diagnostic pipeline
📡
Telemetry Ingestion
CAN Bus · BMS · OBD-II → Edge Processor
IDLE
🔍
UDS Fault Extraction
DTC P0D17, P0A93 · Freeze Frame Data
IDLE
📚
RAG Knowledge Retrieval
OEM Manual §4.3.2 · 847 similar cases matched
IDLE
🧠
LLM Root Cause Analysis
Domain-LLM inference · ASIL-B validated output
IDLE
🔧
Repair Protocol Generation
Step-by-step · Safety checks · Parts list
IDLE
✅
Verification & Sign-off
ISO 26262 compliance stamp · Technician approval
IDLE
🛡️
Safety Validation Engine · ISO 26262 §6
Rule-based deterministic gate — overrides unsafe AI outputs
Technician authorization required before any repair action. AI provides recommendation only — final decision rests with qualified technician.
OTA + SDV INTEGRATION
OTA FIX AVAILABLE
BMS Firmware v2.4.1 — Patch for NTC calibration drift. Resolves DTC P0D17 without hardware replacement in 60% of similar cases.
OTA STAGING PIPELINE
Patch Size
1.2 MB
Sign Method
HSM · ECDSA-256
Rollback Support
Yes
Digital Twin Test
Passed (sim run)
TECHNICIAN ACTION LOG
— Awaiting technician action —
FLEET INTELLIGENCE
Enterprise Fleet Analytics Dashboard
1,247
VEHICLES CONNECTED
38
ACTIVE ALERTS
12
CRITICAL FAULTS
94.2%
FLEET UPTIME
FLEET HEALTH DISTRIBUTION · REAL-TIME
BATTERY DEGRADATION ANALYTICS · FLEET AVERAGE SOH
PREDICTED FAILURES (7 DAY)
23
⚠ 6 critical within 48h
Battery Cell Degradation
11
Motor Bearing Wear
7
Charger Port Fault
5
MAINTENANCE SCHEDULE AI
AI has recommended 18 service appointments for this week, pending fleet manager approval to optimize workshop capacity utilization.
Workshop Capacity
73%
Parts Pre-ordered
34 SKUs
Avg Repair Time
2.1 hrs
COST OPTIMIZATION
₹4.2L
↓ Saved this month vs reactive maintenance
Warranty Claim Reduction
-34%
Roadside Assist Calls
-58%
Avg Diag Time
8 min
SYSTEM ARCHITECTURE
Production-Grade Full-Stack Design
Layered architecture from vehicle edge to cloud inference — compliant with AUTOSAR modular ECU integration and ISO/SAE 21434 cybersecurity requirements.
Standards
ISO 26262 Advisory ASIL-B/QM
AUTOSAR CP/AP
ISO/SAE 21434
UDS ISO 14229
MISRA C:2012
Edge Layer
BMS ECU
Motor Controller
CAN Bus Sniffer
OBD-II Gateway
Edge AI Processor
Telemetry Logger
Comm Layer
MQTT v5 (TLS 1.3)
WebSocket Streaming
REST API (HTTPS)
4G/5G Telematics
mTLS Auth
Cloud Platform
API Gateway
Microservices (K8s)
Data Lake (Parquet)
Stream Processor (Flink)
TimeSeries DB (InfluxDB)
Fault Index (ElasticSearch)
AI Layer
Domain LLM (7B params)
RAG Pipeline (FAISS)
Anomaly Detector (LSTM)
RUL Predictor (XGBoost)
NLP Multilingual
Digital Twin Sync
Safety Gate
Safety Validation Engine
Rule-Based Override (ISO 26262)
Confidence Scorer
HARA Traceability Log
Human-in-the-Loop Gate
Data Trust Validator
Application
Technician Mobile App
OEM Dashboard
Fleet Manager Portal
OEM API Integration
Dealer Management Sync
ISO 26262 · Functional Safety
AI outputs carry QM/ASIL-B advisory classification. Safety-critical paths are dual-validated by deterministic rule engine. Full HARA documentation maintained per V-model lifecycle phases.
ASIL Target
QM / ASIL-B (advisory system, not actuation)
V&V Method
Shadow mode + staged rollout with ASIL gate
HARA
Hazard analysis documented per §7.4 — 14 hazardous events catalogued
Traceability
Every AI recommendation links to DTC + OEM manual reference + confidence score
Lifecycle
Full ISO 26262 V-model: Concept → Design → Integration → V&V → Release
AUTOSAR Architecture
ECU modules follow AUTOSAR Classic Platform layering. Diagnostic stack implements DiagnosticMonitor SWC with DEM/FIM integration. AP AUTOSAR for compute-intensive edge inference tasks.
Platform
AUTOSAR Classic (CP) for BMS/VCU ECUs; AP for edge AI processor
SWC
DiagnosticMonitor, DEM (Diagnostic Event Manager), FIM (Function Inhibition Manager)
Integration
EV-SIP packaged as AUTOSAR SWC — drop-in for OEM BSW stacks
Comms
AUTOSAR COM / PduR for inter-ECU messaging
OTA
UCM (Update and Config Management) module for software updates
ISO/SAE 21434 · Cybersecurity
Threat Analysis & Risk Assessment (TARA) performed for all attack surfaces. mTLS mutual authentication on all vehicle-to-cloud channels. HSM for key storage at ECU level.
TARA
23 threat scenarios identified; 8 rated HIGH — all mitigated
Key Mgmt
HSM-backed ECDSA-256 keys; air-gapped PKI for OTA signing
Network
mTLS v1.3 + zero-trust microsegmentation between services
ECU Sec
Secure boot, code signing verification before firmware execution
Audit
Continuous TARA review cycle; IDS at ECU and API gateway layers
UDS ISO 14229 · Diagnostics
Full UDS service implementation: ReadDTCInformation (0x19), ECUReset (0x11), SecurityAccess (0x27). DTC freeze frame data cross-referenced with AI knowledge base for root cause correlation.
Qualified technician reviews advisory + safety-verified output. Approves or requests further diagnosis. Logged with timestamp.
🔧
STEP 06
Repair Executed
Step-by-step repair protocol displayed. Parts pre-ordered via DMS integration. OTA patch staged if applicable.
✅
STEP 07
Sign-off & Trace
Repair recorded in EV-SIP audit trail. ISO 26262 traceability link generated. Fleet dashboard updated instantly.
VEHICLE-IN TO DIAGNOSIS
8 min
vs 45 min traditional
AI CONFIDENCE (AVG)
87.4%
across 50M+ case corpus
SAFETY GATE OVERRIDES
1.2%
AI outputs blocked by safety rules
FIRST-TIME FIX RATE
91%
vs 68% without EV-SIP
CORE CAPABILITIES
Full EV Service OS — Not Just a Chatbot
🧠
Domain-Trained Diagnostic LLM
7B-parameter model fine-tuned on 50M+ EV repair cases, OEM service manuals, and UDS fault logs. Understands cell chemistry, motor physics, and BMS behavior — not generic language.
RAG · FAISS
Fine-tuned
Hindi/Tamil/English
🔮
Predictive Maintenance Engine
LSTM anomaly detection + XGBoost RUL predictor. Identifies degradation patterns 2–3 weeks before failure. Battery SOH forecasting with 95.4% accuracy validated across 12 OEM models.
LSTM
RUL Estimation
SOH Analytics
📡
Live Telemetry Ingestion
Sub-second data pipeline from CAN Bus, OBD-II, BMS, and IMU sensors. Stream processing via Apache Flink with real-time anomaly flagging at the edge before cloud upload.
CAN / OBD-II
Edge AI
500ms sync
🗣️
Voice + Multilingual Interface
Technician UI supports Hindi, Tamil, Telugu, Marathi, and English voice queries. Adaptive UI simplifies for L1 technicians, exposes full data for senior engineers. India-first design philosophy.
Voice NLP
8 Languages
Skill-Adaptive
🔒
Cybersecurity-First Design
ISO/SAE 21434 TARA-compliant architecture. End-to-end mTLS, HSM key storage, zero-trust network model. OTA update signing with hardware attestation. Intrusion detection at ECU and API layers.
ISO/SAE 21434
mTLS
HSM
🔁
Digital Twin Integration
Optional bidirectional Digital Twin sync enables what-if simulations before physical repair. OEM partners can run virtual validation of software updates before OTA deployment.
Digital Twin
OTA Staging
Simulation
BUSINESS MODEL
SaaS Pricing for Every Scale
WORKSHOP
Starter
₹4,999
/ month · per workshop
Up to 100 vehicles/month
AI Diagnostic Assistant
UDS DTC Reader + Decoder
OEM Manual Access
Hindi + English UI
Email support
FLEET OPERATOR
Professional
₹299
/ vehicle / month
Unlimited workshops
Predictive Maintenance Engine
Fleet Analytics Dashboard
RUL & SOH Forecasting
All 8 language UIs
API access (5000 calls/day)
Dedicated CSM
OEM INTEGRATION
Enterprise
Custom
per OEM agreement
White-label platform
Custom LLM fine-tuning
Digital Twin integration
On-prem / hybrid deploy
AUTOSAR SWC packaging
ISO 26262 audit support
24×7 SLA
API MARKETPLACE
Developer
₹0.08
/ diagnostic API call
REST + WebSocket API
AI Inference endpoint
RAG knowledge API
Telemetry ingest API
Volume discounts
Sandbox environment
ROI IMPACT
Quantified Business Value
30–70%
Reduction in diagnostic time per vehicle through AI-guided fault resolution
20–40%
Reduction in unplanned downtime through predictive maintenance alerts
3.2×
Workshop throughput improvement with AI-assisted technician workflows
MARKET POSITIONING
Why EV-SIP Wins
Capability
Bosch EV-SIP
Generic AI Chatbots
Legacy Diagnostics
OEM Proprietary Tools
Domain-Trained LLM
✓ Fine-tuned on EV data
✗ Generic knowledge
✗ Rule-based only
△ Proprietary, closed
Real-Time Telemetry
✓ Live vehicle integration
✗ Static input only
△ OBD-II limited
✓ OEM-only access
Predictive Maintenance
✓ LSTM + XGBoost ML
✗ Not available
✗ Reactive only
△ Limited models
ISO 26262 Compliance
✓ ISO 26262 Compliant (ASIL-B/QM Advisory)
✗ No safety framework
△ ASIL-B at best
✓ Model-specific
India Multilingual
✓ 8 Indian languages
△ English-first
✗ English only
✗ Limited
Multi-OEM Support
✓ All OEMs
✗ No integration
△ Tool-specific
✗ Single OEM
Digital Twin
✓ Bidirectional sync
✗
✗
△ Select OEMs
BENCHMARK ANALYSIS
EV-SIP vs Traditional Diagnostic Tools
Head-to-head capability comparison against industry incumbents — measured across real service center deployments in Pune and Bangalore pilots.
Capability
Bosch EV-SIP V2
Traditional Scan Tools
Manual + Printed Manual
Generic OBD App
AI-Guided Diagnostics
✓ Domain LLM + RAG
✗ Rule lookup only
✗ Manual search
✗ DTC code only
Predictive Maintenance
✓ LSTM + XGBoost RUL
✗ Reactive only
✗ Not available
✗ Not available
Real-Time Telemetry
✓ CAN + BMS + OBD live
△ OBD snapshot only
✗
△ OBD only
Safety Validation Engine
✓ ISO 26262 rule gate
✗
✗
✗
Human-in-the-Loop (HITL)
✓ Mandatory approval flow
△ Technician decides
✓ Human decides
✗
Multilingual (Indian Languages)
✓ 8 languages incl. Hindi
✗ English only
✗
✗
OTA Patch Recommendation
✓ Signed HSM + Digital Twin test
✗
✗
✗
Data Confidence Scoring
✓ Real-time sensor validation
✗
✗
✗
Average Diagnosis Time
~8 minutes
~35–45 min
~60–90 min
~15–20 min (DTC only)
First-Time Fix Rate
91%
~72%
~60%
~55%
BUSINESS IMPACT
Quantified ROI Per Vehicle & Fleet
Financial impact based on pilot data from 3 Indian fleet operators (Pune, Bangalore, Chennai) across Q3–Q4 2024.
💰 ROI Per Vehicle (Annual)
Diagnostic Labor Saved
₹8,400
Unplanned Downtime Avoided
₹12,200
Warranty Claim Reduction
₹5,600
Parts Waste Reduction
₹3,100
TOTAL PER VEHICLE
₹29,300
🏭 Workshop Efficiency Gains
Avg Diagnosis Time
−82%
Vehicles/Technician/Day
+3.2×
Repeat Repairs
−38%
Technician Upskill Time
−65%
Service Booking SLA
+94% on-time
📈 Fleet Operator KPIs
Fleet Uptime
+6.4 pp
Roadside Assistance Calls
−58%
Battery Replacement Early ID
+3 wk lead
Total Maintenance Cost
−31%
NPS (Fleet Manager)
74 → 91
ENGINEERING HONESTY
Real-World Constraints & Mitigations
📊 Data Dependency Challenge
LLM accuracy is dependent on high-quality telemetry and repair data. Cold-start problem for new OEM models with limited fault history. Mitigation: Federated learning across fleet + synthetic data augmentation using validated simulations.
🔌 Legacy System Integration
Older workshops use proprietary DMS software without modern APIs. ECUs from pre-2018 vehicles lack standardized CAN protocols. Mitigation: Universal OBD-II gateway hardware + adapter library for 40+ DMS platforms.
⚠️ Safety Validation Requirements
Every AI model update must undergo full ISO 26262 V-model validation before deployment to safety-critical diagnostic paths. Mitigation: Shadow mode deployment, staged rollout with human-in-the-loop gates, formal verification for rule engine components.
🔐 Cybersecurity Risks
Vehicle-to-cloud channels are high-value attack surfaces. OTA exploit risks if signing infrastructure is compromised. Mitigation: Hardware Security Modules at ECU and server, code signing with air-gapped PKI, continuous TARA review per ISO/SAE 21434 update cycles.
AI GATEWAY ARCHITECTURE
How AI Inference Flows Safely to the Technician
Every diagnostic request passes through a secure, logged, cost-controlled AI Gateway before reaching the LLM. Output is safety-gated before display. No AI response reaches a technician without passing the deterministic validation layer.