This startup leverages its proprietary Digital Twin technology to provide real-time and predictive insights for the mobility industry.
The mobility ecosystem is facing several challenges because of skyrocketing fuel prices, rising labour costs for both skilled and unskilled labour, as well as a labour shortage. As regulations tighten and competition heats up, the entire system is getting increasingly complex. With these elements piling up on several fronts, fleet operators must have cost control metrics aided by the right technology to boost their bottom line, while also optimising operations.
There are various solutions in the market that have attempted to meet these pressing needs of fleet managers, but none of them has been comprehensive enough to deliver the necessary insights. The fundamental concerns that must be addressed are the health of the asset and its operator.
This is where Intangles steps in, a company that leverages its proprietary Digital Twin technology to provide predictive insights in real-time for the mobility industry. The solution entails the use of proprietary ML algorithms to generate predictive insights on component failure, precise statistics on vehicle performance (fuel consumption, distance, run hours), driving behaviour and automated reports by leveraging geospatial intelligence.
As of today, the Intangles platform monitors 40K+ assets across 10 countries, while on-boarding approximately 500 fleet operators per month and wrangling a staggering two billion sensory data points on a daily basis.
The Tech Panda spoke to Anup Patil, the CEO of Intangles, about what they do and how they got there.
We provide comprehensive predictive insights that enable an operator to receive alerts well before a failure occurs, along with an appropriate set of diagnostic instructions
“We provide comprehensive predictive insights that enable an operator to receive alerts well before a failure occurs, along with an appropriate set of diagnostic instructions. Such precise diagnostic instructions, combined with predictive alerts, are altering the entire ecosystem where responsibility for a vehicle’s health becomes a collective endeavour rather than a blame game. This is the issue that Intangles is attempting to solve,” he says.
“We also recognise that the present set of analytics tools is inadequate and lacks the ability to resolve these issues. This is why we have taken a whole new approach by creating digital twins of every component of a vehicle, including the engine, battery, intercooler, turbocharger, and air and fuel intake system. We analyse these virtual twins from numerous angles, making peer-to-peer comparisons and providing the appropriate set of recommendations based on the analysis,” he adds.
What They Do
The Intangles system uses proprietary hardware that can communicate with the latest vehicle diagnostic ports.
“This technology can collect data from a wide range of commercial vehicle platforms and powertrain technologies. The captured data is sent to the cloud through a cellular network and is consumed by a fully specialised server backbone,” explains Patil.
The data is then fed to various ML algorithms, which mimic the behaviour of various systems and components, such as the engine’s cooling system and the fuel tank. Using geospatial knowledge, the algorithms generate predictive insights on component failure, detailed statistics on vehicle performance (fuel consumption, distance, run hours), driving behaviour, and automated reporting.
Inspiration & Origin
The Intangles team’s passion for data sciences and automobile technologies led them to the exploration of On-Board Diagnostics data on passenger vehicles.
“It was fairly discernible that there was limited scope for predictive health diagnostics on passenger vehicles for good/routine upkeep of personally owned and operated vehicles. This led us to analyse data streams on commercial vehicles including trucks and buses, which opened doors to a vast arena of opportunities,” Patil recalls.
It was fairly discernible that there was limited scope for predictive health diagnostics on passenger vehicles for good/routine upkeep of personally owned and operated vehicles. This led us to analyse data streams on commercial vehicles including trucks and buses, which opened doors to a vast arena of opportunities
“With a clear use case in sight, we developed our hardware interface capable of collecting data from CV (Commercial Vehicle) platforms across OEMs, fuel injection and emissions technologies,” he adds.
This was augmented with a state-of-the-art edge-to-cloud communication backbone and a suite of proprietary algorithms targeted toward predictive health alerts, driver behaviour profiling, fuel pilferage and geo-spatial intelligence.
The Intangles USP
Intangles’ main point of differentiation is the extraction of easily observable, actionable insights from complicated telemetry data streams, intending to meet the KPIs of the average fleet manager.
“This envelopes highly accurate performance information (fuel consumption, distance, run hours), highly precise predictive alerts for failure, diagnostic alerts with detailed metadata (causes, repair solutions), and detailed reports on schedules and pilferages,” explains Patil.
With visibility on the route and application-specific performance aggregates, they can better plan their operations with a focus on improved profits
Their solutions can predict key engine faults, leading to less downtime and cheaper maintenance expenses.
“With visibility on the route and application-specific performance aggregates, they can better plan their operations with a focus on improved profits. Fuel pilferage notifications issued by our platform facilitate an immediate decrease in trip costs and automated reports on fleet performance reduce the need for human intervention,” he adds.
Intangles is constantly generating around 20,000 predictive alerts per month, which has enabled as much as a 75% reduction in breakdown events. Patil further informs that it has tracked over 200,000 litres of fuel pilferage through its devices equipped in Indian fleets.
The company has also recorded a 20-30% improvement in driver behaviour through its monitoring of 20+ driver behaviour exceptions. In addition, it has brought about a 10-30% increase in asset availability owing to a reduction in vehicle breakdowns. It has also helped reduce vehicle maintenance costs by 5-10%.
When it comes to EVs in the commercial vehicle market, we aim to be the face of telematics in India, from last-mile delivery to long-haul
“In the Indian market, we have gained traction from every level of the industry, be it small or medium scaled businesses to large OEMs. The rapid adoption and acknowledgement of our solutions by our large customer base, speaks for itself,” he says.
In the 11 countries where it’s currently functioning, Intangles has already onboarded 7 OEMs. Furthermore, it already has over 8,000 fleet operators on the platform.
“As of today, the Intangles platform monitors 60K+ assets across 11 countries, while on-boarding approximately 500 fleet operators per month and wrangling a staggering three billion sensory data points on a daily basis. With some of the biggest brands in mobility already signed up as customers, we expect 5x growth in FY’23,” he predicts with pride.
While Intangles is cementing its position in the Indian mobility ecosystem, the prospect of new opportunities in North America, Europe, Australia, and APAC is highly promising, says Patil.
“Our remarkable development and expansion story exemplifies the game-changing potential of Predictive Analytics enabled by Digital Twin technology. We will continue our efforts to redefine performance benchmarks in mobility and transportation in FY’23.
Digital Twin is a system which creates a virtual replica of a real-world asset and is capable of simulation, reasoning and machine learning.
“When it comes to EVs in the commercial vehicle market, we aim to be the face of telematics in India, from last-mile delivery to long-haul. In terms of technology, we intend to cement our position as forerunners in harnessing Digital Twin technology to serve use cases such as motor health and battery health.
The company is also strengthening its position in the medium to heavy commercial vehicle category with IC engines and expanding its analytics package to include vehicle health monitoring, driver ranking, and fleet operations automation.