Perception Stack — Indian Roads

KIRA
SEES
INDIA

Modular perception SDKs trained on Indian road conditions — auto-rickshaws, cattle, unmarked roads, monsoon haze — optimised for edge-class compute. Built in India, for Indian OEMs.

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4+
Sensor Modalities
≤50ms
Edge Latency Target
L2
ADAS Capability
What We Build

Perception Stack.
From Sensor to Signal.

Phase 1 — Now
KIRA VISION
Modular Perception SDKs
Standalone perception modules each trained exclusively on the KIRA Indian road data and deployable as independent software components on edge devices.
Now
Phase 2 — Coming Soon
KIRA BOX
Modular Hardware Stack
Unified hardware and software ECU integration driving custom hardware R&D. Focused on developing, optimizing, and producing the best-in-class processing chips tailored specifically to navigate the unique complexities of Indian road conditions and environments.
Coming Soon
Phase 3 — Coming Soon
KIRA DRIVE
End-to-End Stack
Full autonomous driving stack implementation. A comprehensive, fully integrated end-to-end driving solution built to handle complete autonomous execution seamlessly across diverse scenarios.
Coming Soon
Our Differentiation

Why KIRA Wins
on Indian Roads.

Global perception stacks are trained on European and American road conditions. They fail systematically on India's reality: auto-rickshaws cutting lanes, cattle on highways, unmarked intersections, dust occlusion during peak summer, monsoon haze, and the sheer density of mixed traffic that no global dataset captures.

KIRAAUTONOMY builds perception that is trained, tested, and validated entirely on Indian roads. Our multi-sensor data collection spans diverse conditions — day, night, monsoon, dust, city centre, and open highway — ensuring the models we ship reflect the actual environment they will be deployed in.

We provide modular perception software components that integrate into Indian vehicle platforms — giving OEMs access to production-ready perception capability without building from scratch.

01
India-specific Training Data
Auto-rickshaws, cattle, unmarked roads, dust, monsoon — collected from test vehicles running across diverse Indian conditions. Global SDKs cannot replicate this without years on Indian roads.
02
Modular SDK Licensing
License only lane detection, or only pedestrian detection, or only obstacle avoidance. No forced bundle. Faster adoption, lower entry price, faster integration into OEM pipelines.
03
Edge-Optimised Inference
Every model and inference pipeline is engineered specifically for edge-class compute — the hardware reality of Indian vehicle platforms. Perception accuracy is not sacrificed for deployment constraints.
Company

About
KIRAAUTONOMY.

At KIRAAUTONOMY, we are pioneering the next generation of autonomous perception and decision-making stacks. Born out of a vision to tackle the world's most unstructured and dynamic driving environments, we develop modular, cloud-connected software architectures that bridge the gap between Level 2 advanced driver-assistance systems (ADAS) and Level 3 conditional automation.

We engineer resilient, real-time deep learning pipelines capable of navigating chaos with mathematical precision. By leveraging cutting-edge sensor fusion, edge-to-cloud MLOps, and robust action planning, we empower vehicle manufacturers and fleet operators to deploy safe, reliable, and scalable autonomy today.

From the Founder, CTO & CEO
We founded KIRAAUTONOMY to solve the edge cases that standard vision systems avoid in India. By combining real-time edge intelligence with heavy cloud-scale training pipelines, our team is building an evolutionary software stack that transitions seamlessly from production-ready Level 2 features to robust Level 3 autonomy. We are not just building software; we are building the cognitive foundation for the future of mobility. If you are an OEM or a technology partner looking to accelerate your autonomy roadmap, we invite you to build it with us.
Monish Kiran A
Founder, CTO & CEO — KiraAutonomy Private Limited
People

Meet the
Engineering Team.

Leadership

Monish Kiran A
Monish Kiran A
Founder, CTO & CEO

Leading overall system architecture, strategic vision, and cross-functional technology integration.

Core Engineering

Darshan
Darshan
Founding Engineer — Deep Learning, Planning & HMI

Specializing in neural network architectures, precise localization, and human-machine interface logic.

Varun
Varun
Founding Engineer — Data Architecture & Action Planning

Managing large-scale dataset ingestion, cloud training pipelines, and deterministic behavioral planning algorithms.

Barath
Barath
Founding Engineer — Embedded Systems

Optimizing model deployment, RTOS integration, and low-latency execution on automotive edge-computing hardware.

Mithil
Mithil
Founding Engineer — Robotics Systems

Expert in spatial AI, state estimation, sensor calibration, and localization frameworks.

Technical Interns

Pranav J
Pranav J
Data Engineering Intern
Pranav K
Pranav K
Embedded Engineering Intern
Harjith
Harjith
Robotics Engineering Intern
Sensor Architecture

Multi-modal.
Redundant. Fused.

01
RGB
Stereo and monocular cameras for colour, texture, lane marking, sign reading, and fine-grained object classification. Front-windshield mounted. Primary daytime modality.
02
Thermal
Passive infrared for pedestrian and animal detection at night and in low-visibility conditions — monsoon, dust haze, fog — where RGB degrades below reliable thresholds.
03
LiDAR
Dense 3D pointcloud for precise depth, object geometry, and occupancy grids — enabling spatial reasoning, accurate object sizing, and ground-truth data for model training and validation.
04
Radar
Three front-bumper radar units for all-weather velocity estimation and long-range detection — rain, dust, direct sunlight — providing reliable object presence when all other sensors degrade.
India Advantage

The Road
Conditions No One
Else Has Solved.

Auto-rickshaws & Mixed Traffic
3-wheelers, cycles, cattle, and pedestrians sharing unmarked lanes simultaneously. No global training set captures the density and unpredictability of Indian urban intersections.
Unmarked Roads & Intersections
Absence of lane markings, missing signage, and informal road logic that GPS maps do not reflect. Perception must reason from visual context alone — not map data.
Monsoon & Dust Occlusion
Monsoon haze, peak-summer dust clouds, and waterlogged roads dramatically degrade RGB sensors. Thermal and radar layers trained on Indian seasonal conditions provide cross-modal redundancy.
Night Without Lane Markings
Rural highway driving at night with no reflective markers, no streetlights, and oncoming high-beam traffic. Thermal becomes the primary detection layer — not a supplement.
Livestock on Roads
Cattle, dogs, and other animals as active road participants — not rare edge cases but everyday occurrences on Indian highways and rural roads. A detection class global models systematically underfit.
Potholes & Road Surface
Road surface quality as a perception input — pothole detection, subsidence, and surface hazard mapping from front and bonnet-mounted cameras, relevant for both safety and comfort features.
Data Engine

The Pipeline Behind
the Perception Stack.

01
Collection
Curated data collection across Indian road conditions — highways, urban centres, and high-density traffic scenarios representing the full diversity of Indian driving.
02
Annotation
In-house annotation engine and pipeline — built entirely by KIRAAUTONOMY. India-specific object classes, QA layers, and active learning for edge cases.
03
Training
SOTA architecture fine-tuned on Indian data. Domain adaptation. Multi-task learning. Quantization-aware training for edge.
04
Benchmark
Head-to-head comparison vs. global baselines on India-specific scenarios. Precision and recall per object class published.
05
SDK Delivery
Modular SDK packaged for target edge SoC. OEM integration support. 30-day evaluation trial available.
Live Product

Pipeline & Hardware — In Action

Real inference output and physical sensor infrastructure — not a concept deck. Our models run on collected Indian road data; our test bench validates multi-modal perception before OEM deployment.

Model Inference Pipeline

Live perception inference on KIRA VISION — detection, tracking, and edge deployment validated on Indian road scenarios.

Sensor & Hardware Test Bench
KIRAAUTONOMY multi-sensor hardware test bench with LiDAR, cameras, and edge compute

Physical robotics setup — multi-sensor suite and edge compute platform used for data collection, calibration, and on-vehicle validation.

Who We Serve

Perception for
Indian OEMs.

We work with Indian vehicle manufacturers and platform builders — two-wheelers, three-wheelers, commercial vehicles, and passenger cars — who need production-ready perception capability without the cost and timeline of building it in-house.

Electric Vehicle OEMs
EV manufacturers racing to differentiate on safety and intelligence — who need perception capability delivered fast, without building an in-house ML team from scratch.
Commercial Vehicle Makers
Truck, bus, and 3-wheeler manufacturers where fleet operators and logistics companies are demanding demonstrable safety features as a condition of procurement.
Passenger Car OEMs
Indian passenger car manufacturers seeking perception modules that are validated on Indian road conditions — not adapted from global platforms that were never trained here.
Get in Touch

Contact Us.

Partnership inquiries, pilot programs, investor relations, or benchmark data requests.

Response within 48 hours — from an engineer, not a sales team.

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Join KIRAAUTONOMY

Build With Us.

We are looking for people who have shipped real perception, robotics, embedded systems, or data infrastructure. Tell us what you've built.

Upload Resume — PDF or DOC

Every submission is read by a technical founder.

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Office
23, Rathinam Nagar, Cheran Maa Nagar Extn
Kalapatti, Coimbatore — 641 048
Tamil Nadu, India
Contact
+91 99421 47571
monish@kira-autonomy.com
LinkedIn · @kiraautonomy
What We Build
Perception stack technologies for autonomous driving in India — modular SDKs trained on Indian road conditions, optimised for edge-class compute.