Broad global smartphone-first driver-safety and telematics opportunity. Directional.
Investor brief
Build risk is behind us. Capital buys distribution, not R&D survival.
A production-grade, multi-sided platform is already shipped across four surfaces — driver app, fleet console, manager app and the KYD scoring engine. Sakshya is pre-revenue and in pilot, raising a pre-seed round to convert pilot traction into paying contracts and to prove the score predicts claims.
What is built
Shipped, hardened and compliant — not a demo.
The rare pre-Series-A asset is a full, production-grade, multi-sided platform that already exists. That is what removes the ‘can they build and operate it’ question.
And what is not
- Score-to-claims validation: not started. It is the next proof and the first funded milestone.
- iOS: several pieces code-complete but unverified on device. Honest status, cheap to close.
- Live map at 200k+ drivers: engineered and built, not yet deployed at that size. Bottlenecks are known.
- Road Risk Index and road-quality intelligence: designed, no production code.
A team that states what is not proven is a team you can price. We would rather you find this on our website than in diligence.
Production-grade platform — four surfaces live
LiveDriver app, fleet console, manager app, KYD engine and a platform-admin console.
Real-world hardening
LiveOffline resilience, battery and thermal adaptation, mid-trip orientation recovery, per-channel anti-gaming.
Scale engineered in
BuiltLive-map path built for 100k+ drivers per view — built, not yet deployed at that size.
Consent and privacy compliance
LiveDPDP-style export and erasure across 37 tables with a CI gate; per-read access audit logging.
Insurer partner API
BuiltScoped JWT, portfolio distribution and quote-handoff verification already exist.
Market
India-first. Build the safety intelligence layer, then export.
Sakshya is a multimodal AI safety intelligence platform: smartphone, dashcam, GPS and IMU sensing → AI understanding → risk prediction → accident prevention → outcome measurement → model improvement. Insurance is a future monetisation layer, not the lead.
India commercial telematics and fleet safety: $1.97B (2025) → $7.14B (2034), 15.4% CAGR.
IMARC Group, 2025
ARR over 36 months — 150–250k vehicles across 50–100 customers. Bottom-up and directional.
01Live
Commercial fleets
Dashcam and smartphone telematics for trucking, buses and light commercial vehicles. Per-vehicle subscription, live-ops dashboard, driver coaching, incident replay.
02Live
Gig & last-mile
Two- and three-wheeler delivery and ride-hailing drivers — smartphone-first, hardware-free. Highest-risk, highest-turnover, most underserved by incumbents.
03Built
AI safety infrastructure
The multimodal sensing stack and driver-risk scoring engine, priced as a platform SDK or data feed for partners, cities and IoT integrations.
04Future
Insurance / risk API
UBI pricing signals for IRDAI-regulated insurers. A second monetisation layer, activated only once sufficient validation data exists.
Sources: IMARC Group 2025 · Mordor Intelligence · IRDAI UBI framework · IBEF 2025 · MoRTH, Road Accidents in India 2022. Market figures are third-party estimates reproduced for information; SOM is the company’s own bottom-up projection and is not a forecast of results.
Business model
Four revenue lines off one codebase and one dataset.
Several shots on goal, near-zero incremental cost per driver, and a data asset that makes the insurer line more valuable every quarter.
Recurring
Fleet SaaS
Per-driver or per-seat monthly subscription, tiered by live ops, messaging, analytics, compliance and exports, retention and SLA. Expands with fleet headcount — seat and plan gating is already built. Enterprise levers: SSO, MFA, dedicated support.
Highest margin
Insurer / risk API
Per-scored-driver, per-risk-query, or revenue share on UBI policies enabled. The KYD engine is the asset. Partner API, scopes, portfolio distribution and quote-handoff verification already exist. Land with one UBI-curious insurer; expand to reinsurers and broker platforms.
Freemium
Consumer / D2C
Free driver app; premium safety and family plans; partner-insurance referrals. Top of funnel for the data moat — every free driver improves the models.
Later
Data & benchmarking
Anonymised, aggregated, consent-respecting road-risk and road-quality intelligence for insurers, cities and infrastructure bodies. Road Risk Index is designed.
The round
Raising a pre-seed round. Capital buys distribution, not survival.
The product is built, so most of this round goes to go-to-market, score validation and the AI Fleet Manager — not to finding product. Round size, instrument, terms, valuation, pilot names and the financial model are shared with qualified investors under NDA.
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Indicative use of funds
Go-to-market & sales
~35–45%Fleet sales, insurer business development, and the first commercial co-founder hire. Funding growth, not survival.
Data science & score validation
~20–25%Prove the score predicts claims and incidents, plus the first data-science hire. Unlocks the high-margin insurer line.
Engineering
~15–20%iOS parity, OEM background-capture certification, journeys flag-off, MCP server and AI Fleet Manager v1, dashcam OEM integration, live-map scale-out.
Compliance, security & certifications
~5–10%DPDP-aligned data-protection audits, insurer and enterprise procurement certifications, one external penetration test.
Operations, support & G&A
~10%Customer success for fleets, runway buffer, cloud and tooling.
Milestones this funds
- Three to five paying fleets on a committed run-rate.
- Five to ten thousand active scored drivers.
- iOS parity and the OEM background-capture matrix closed.
- MCP server live and AI Fleet Manager v1 shipped.
- One insurer validation proof of concept started, with a co-signed study design.
Roadmap
Three horizons. Honest tags, always.
Capital funds the near-term milestones that convert pilots to contracts and unlock the insurer revenue line. We never upgrade a maturity tag without checking the system behind it.
Near term — what the next cheque funds
~6–12 months
Insurer-grade score validation (Phase 3)
Not startedCorrelate the score against real claims and incidents using Tier 3 data — smartphone, dashcam and GPS tag. The single proof that converts pilots to contracts. Needs partner data and the fidelity layers.
iOS parity
In progressSeveral pieces code-complete but unverified on device, because there is no Mac in the build chain today. Honest status, and cheap to close.
Background-capture certification across OEMs
In progressThe capture spine is built; what remains is systematic on-road certification on the handset makers that kill background services. A device-time problem, not a code problem.
Server-side automatic SMS and richer SOS delivery
PlannedToday’s SMS is sent from the device, deliberately, for carrier reliability and zero platform-policy risk.
Turn on journeys / chaptering
BuiltLong commercial drives stitched into one journey of chapters. A flag-off, and a funded milestone.
Mid term
~12–24 months
Road Risk Index (RRI)
DesignedThe trip stream as a geospatial risk map. An external heavy-stack approach was evaluated and rejected in favour of the existing pipeline.
Road-quality / pothole intelligence
DesignedIMU-derived road-condition mapping — a second data product for insurers, cities and infrastructure bodies.
Live-map deployment at 200k+ drivers
BuiltEngineered, not yet deployed at that size. Bottlenecks are known; deployment is a funded milestone, not a redesign.
AI assistant / service layer
DesignedIn-app driver assistant, plus insurer-partner and legal-information service threads.
Long term
~24+ months
Multi-geography expansion
PlannedSame software, no hardware supply chain. Target emerging markets with smartphone-first, two-wheeler-dominant driver bases.
Data & benchmarking products
PlannedAnonymised, consent-respecting road-risk intelligence for insurers, cities and infrastructure bodies.
Embedded-insurance partnerships
PlannedThe Sakshya score embedded at the point of quote, with revenue share on policies enabled.
The thesis
Six reasons — build, moat, money, scale, tailwind, trust.
01
Build risk retired, distribution risk ahead
A rare pre-Series-A asset: a full, production-grade, multi-sided platform already shipped across four surfaces. Capital compounds into growth rather than into finding product.
02
A compounding data moat keyed to the UIN
Every trip makes the risk signal more valuable and harder to replicate, keyed to a portable driver identity that follows the driver across fleets and insurers. Latecomers start cold.
03
Multiple monetisation paths
Fleet SaaS, insurer API, direct-to-consumer, and later data — off one codebase and one dataset. Several shots on goal.
04
Hardware-free means capital-efficient scale
No per-vehicle bill of materials, no install logistics, software gross margins and fast geographic export. It serves two-wheelers, which hardware telematics cannot.
05
Regulatory tailwinds, not friction
UBI liberalisation, road-safety mandates and consent law all push in the same direction. Sakshya is already consent-native rather than retrofitted.
06
Execution proof — and honesty about what is not proven
The team ships safely to production and states plainly what is not yet proven: score-to-claims, iOS, and 200k deployment. That combination de-risks the ‘can they build and operate’ question.
The team
Two founders who built and shipped the entire platform.
A small, capital-efficient team at AIABS Research and Services Pvt Ltd, where Sakshya is the first product. The driver app, fleet console, manager app, platform-admin console and the KYD engine were built end to end by the founders.
HT
Harsh Tiwari
Chief Executive Officer & Chief AI EngineerOver a decade across BFSI and insurance, with deep work in software engineering, applied AI and enterprise architecture — focused on AI-driven claims analytics and risk management. Architect and principal engineer of the Sakshya platform.
LinkedIn
MS
Manish Kumar Singh
Chief Financial Officer & Co-founderEleven years in corporate finance and strategic management — financial planning, regulatory compliance, budgeting and capital allocation for growth-stage technology companies.
LinkedInDiligence questions welcome — including the uncomfortable ones.
Pilot names, counts, the financial model and round terms sit in the data room under NDA. The methodology, the abstention rules and the code’s compliance gates we are happy to walk through in detail.
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