FULL PITCH DECK
INVESTOR + STRATEGIC VERSION
Addressing the ADAS calibration and validation gap with real-time drift detection, automated compliance validation, and fleet intelligence across OEM, aftermarket, and insurance channels.
The Critical Problem
Multi-billion dollar systemic failure in ADAS calibration and validation.
Sensor Misalignment Crisis
Minor collisions, windshield replacements, and routine service introduce sub-degree camera pitch/yaw errors that degrade safety features.
- 0.5 deg camera pitch error -> 15-20% AEB range reduction
- Cross-sensor fusion failures increase false negatives
- Lane departure and ACC reliability degrade
Calibration Compliance Gap
Industry findings indicate over 80% of vehicles needing post-repair ADAS calibration leave without proper validation.
- No real-time drift detection in most shops
- No automated compliance logging
- Claims lack sensor-health evidence trails
Cascading Economic Impact
OEM lines lose calibration throughput while fleets absorb downtime, compliance exposure, and insurance severity increases.
- OEM EOL calibration: 30-60 min / vehicle
- OEM labor impact: $40-80 / vehicle
- Fleet downtime: $200-500 / day
- Claim severity increase: 8-15%
NADIR Solution Architecture
Real-time drift detection, automated validation, and continuous sensor health monitoring.
Hardware Layer
- Camera: Sony STARVIS / OnSemi, >=120 dB HDR
- IMU: Bosch BMI270, 16-bit, +/-2000 deg/s, +/-16g
- Connectivity: GMSL2, CAN FD/FlexRay, Automotive Ethernet, LTE-M/5G OTA
- Environmental: +/-0.5 C temp, IP67 sealing
Compute Platform
- NVIDIA Orin (254 TOPS), Snapdragon Ride, TI TDA4VM
- Linux 5.15+ PREEMPT_RT / QNX 7.1 option
- AUTOSAR Adaptive and secure boot (TPM 2.0)
- Performance: <10-15ms latency, 30-60 FPS
Software Stack
- ROS2, C++17/20, CUDA 12.x, TensorRT 8.x
- OpenCV 4.8+, Eigen 3.4+, GTSAM 4.2+, Ceres 2.1+
- Inference target: <5ms
- Pipeline latency target: <15ms end-to-end
Core Algorithms
- SE(3) drift estimation with sliding-window BA
- Precision: +/-0.05 deg angular, +/-2 mm translation
- Fusion: camera-radar-IMU with EKF/UKF
- Validation: Mahalanobis + chi-square testing, 99.7% confidence
Market Data and Analytics
Comprehensive market sizing, growth assumptions, and segment distribution.
TAM: ADAS hardware market (2024)
SAM: calibration services (2033)
SAM: calibration tools (2035)
SOM: target addressable by Y5
Growth Trajectory
- Calibration services CAGR: 12.8%
- Calibration tools CAGR: 13.1%
- CaaS CAGR: 3.4%
Customer Segment Distribution
- Collision repair: 42% ($3.5B)
- OEM production: 25% ($2.1B)
- Fleet management: 21% ($1.8B)
- Insurance/warranty: 12% ($1.0B)
Adoption Forecast (2025-2030)
- Progressive fleet deployments
- Aftermarket install acceleration
- OEM integration curve ramps by Y3-Y5
Platform Capabilities and Positioning
NADIR as the only platform combining real-time drift detection, validation, and fleet intelligence.
Competitive Gaps
- Tier-1 suppliers: static factory calibration only
- OEM tech groups: proprietary and siloed efforts
- ADAS software leaders: perception-first, no calibration ops layer
- Fleet telematics: no sensor-level ADAS diagnostics
- Repair tech: manual workflows, limited validation
NADIR Unique Value Proposition
- Continuous SE(3) monitoring versus one-time checks
- Cross-OEM AUTOSAR-compatible platform
- Vertical chain coverage: factory -> aftermarket -> fleet -> insurance
- Automated compliance validation and audit trails
Business Model and Unit Economics
Multi-revenue hardware + SaaS + data model with strong gross margin profile.
OEM Hardware + License
Per-vehicle hardware module + software license. Target 5-10% OEM penetration by Y5.
Gross margin: 40-50%
Aftermarket Retrofit
Retrofit kit, install, and first-year subscription for collision and glass channels.
Gross margin: 55-65%
Fleet SaaS
Per-vehicle cloud platform and APIs for compliance, alerts, and benchmarking.
Gross margin: 80-85%
Data Licensing / Insurance API
Anonymized sensor health feeds for UBI, claims severity, and fraud analytics.
Gross margin: 90-95%
Unit Economics (Fleet)
- CAC: $480
- ARPV: $220
- Gross margin: 82%
- Customer lifetime: 8 years
- LTV:CAC target: 3.0:1 by Y2-Y3
5-Year Revenue (Conservative)
- Y1 2025: $0.8M
- Y2 2026: $4.2M
- Y3 2027: $18.5M
- Y4 2028: $52.3M
- Y5 2029: $124.7M
Scale Progression (Account-Level)
- Y1: $1.0k
- Y2: $2.8k
- Y3: $9.6k
- Y4: $28.0k
- Y5: $66.0k
Go-to-Market Strategy
Phased market entry: Fleet -> Aftermarket -> OEM.
Target 50-500 vehicle fleets (Amazon, UPS, FedEx, rideshare partners). Value: $200-500 per vehicle/year savings, compliance automation, liability reduction. Success target: 10K vehicles, 3-5 anchors, <6 month payback.
Partnerships with MSO chains, dealer service, and windshield channels. Model: $199-349 retrofit + $6-10/mo per bay. Success target: 500+ shops, 80%+ compliance (from <20%).
Tier-1 partnerships (Bosch, Continental, Aptiv). Value: $40-80 labor savings and +8-12 vehicles/day throughput per line. Success target: 1-2 OEM programs, 200K+ vehicles/year, $45-75 ASP.
Founding Team
Deep technical capability in autonomous systems, CV, embedded software, and automotive architecture.
Dhruv Hegde - Co-Founder & CEO
University of Michigan - Computer Science & Mathematics. Focus on computer vision, camera calibration, and low-level sensor programming for automotive systems.
Srivatsan Balaji - Co-Founder & CTO
University of Michigan - Computer Engineering. Focus on embedded systems, real-time optimization, and sensor fusion architecture.
Hiring Priorities (12 Months)
- Founding perception engineer
- Full-stack founding engineer (React/TypeScript/API)
- Embedded and optimization talent
Operating Focus
- Production-grade validation tooling
- Fleet and channel integrations
- OEM readiness and safety-cert pathway
Current Traction and Milestones
Started in Q1 2026. MVP completed with pilot, fundraising, and hardware tracks in motion.
Validated on KITTI and nuScenes. Achieved +/-0.05 deg and +/-2 mm simulation results.
Alpha stack: NVIDIA Orin + Sony STARVIS + Bosch IMU targeted for completion in Q4 2026.
LOI target with regional delivery fleet (250 vehicles), 6-month pilot. Savings validation target: $400/vehicle/year.
Team expansion (4-6 engineers), beta run (500 units), 3-5 pilots.
10-15 shop deployments. Compliance improvement goal: <20% -> 85%+.
Seed target: $8-15M after traction. Tier-1 roadmap discussions with Bosch/Continental.
Pre-Seed Funding Round
Funding options and operating plan reflected from current deck materials.
Raise Range
Indicative target at $4M-6M pre-money valuation (~5-10% dilution range).
Scale Objective
Broader pre-seed objective in roadmap mode to support larger pilot and hiring cadence.
18-Month Milestones
- M1-6: hiring + beta production + first pilot (500 vehicles)
- M7-12: 3-5 pilots, 3K vehicles, 15 shops, $500K-1M ARR validation
- M13-18: seed prep ($8-15M), ISO pathway, $2-3M ARR target
Team expansion
Hardware and manufacturing
Pilot deployments
Infrastructure and operations
Risk Factors and Mitigation
Transparent risk model with specific mitigation tracks.
OEM Sales Cycle Length
Risk: 18-36 month procurement cycle delays revenue.
- Prioritize fleet + aftermarket for near-term ARR
- Use Tier-1 channels over direct-only OEM selling
- Diversify revenue mix in parallel
Tier-1/OEM Competition
Risk: incumbent in-house drift solutions.
- Aggressive IP posture and early mover execution
- Cross-OEM neutral platform positioning
- Defensible aftermarket channel strength
ISO 26262 Certification Complexity
Risk: ASIL-D path can require 12-18 months and $1M-2M.
- Phase 1 with fleet/aftermarket on ASIL-B profile
- Parallel certification consultants (TUV SUD, SGS)
- Budget seed allocation for certification track
Customer Acquisition Economics
Risk: early LTV:CAC below 3:1 target.
- Pilot case studies reduce CAC over time
- Channel partnerships increase distribution efficiency
- Insurance co-marketing incentives for fleets
Let's Build the Future of ADAS Safety
Seeking strategic partners, investors, and early customers.
Contact
dhruv@nadir.ai
srivatsan@nadir.ai
NADIR Technologies Inc.
San Francisco, CA
Founded 2025