How Switch Mobility is Building a Connected, Resilient, and Manufacturing-Grade Digital Ecosystem for the Next Era of EV Growth
When EVs Grow Up, Digital Has to Grow Up Too
Electric mobility is no longer living in the comfortable world of pilots those carefully controlled deployments where a few vehicles, a few routes, and a few partners can make almost any system look stable. The market is moving into a more unforgiving phase: manufacturing scale. Thousands of vehicles. Multiple cities. Mixed driving styles. Variable infrastructure. Tight uptime expectations. And customers who don’t buy “innovation” they buy outcomes.
In that reality, software doesn’t win markets on its own. Operational resilience does. The EV maker that can manufacture consistently, service quickly, diagnose remotely, and keep fleets running day after day becomes the one fleets trust with expansion.
At Switch Mobility, that shift is shaping how the company thinks about digital. Not as a shiny product layer, but as something far more foundational: a force multiplier across vehicles, plants, service networks, and customer operations.
In an exclusive conversation, Santosh TG, Chief Digital Officer, explains how Switch is building a common digital backbone that connects engineering, manufacturing, service, and field operations and why the most meaningful “digital metric” isn’t an app download or a dashboard view, but vehicle uptime.
“For a manufacturer, uptime is credibility.”
Santosh TG, Chief Digital Officer, Switch Mobility
The Big Bet: A Single Backbone Across the Vehicle Lifecycle
Ask most leaders about digital transformation and you’ll hear familiar themes: data platforms, dashboards, AI experiments, cloud migration. Santosh’s answer cuts through that noise with a manufacturer’s clarity.
The most consequential digital bet Switch made in the past year, he says, was embedding digital deeply across the vehicle lifecycle not just in one department, but across the enterprise. The objective wasn’t to add more tools; it was to remove the friction that slows decisions and hides problems until they become expensive.
By building a common digital backbone across engineering, manufacturing, service, and operations, Switch reduced the classic enterprise tax: teams operating in parallel systems, resolving mismatched versions of truth, and losing time to cross-functional handoffs.
The result, Santosh notes, is improved decision velocity a deceptively simple phrase that, at scale, becomes a competitive weapon. When an anomaly appears in the field, the difference between “we’ll investigate” and “we already know why” is the difference between a manageable issue and a brand-defining failure.
In other words: a digital backbone isn’t a technology initiative. It’s an execution system.
The Metric That Matters: “Uptime Is Credibility”
If Santosh tracks only one number every single week, it’s vehicle uptime.
That priority says a lot about how Switch frames digital success. Uptime isn’t a vanity metric. It is the composite output of engineering quality, manufacturing consistency, service maturity, and real-time operational intelligence. It’s what customers feel immediately because downtime isn’t an inconvenience in commercial EVs. It’s lost revenue, disrupted routes, strained contracts, and anxious fleet managers. “For a manufacturer,” Santosh says, “uptime is credibility.”
And credibility compounds. As uptime rises, the business benefits cascade: improved fleet utilization, stronger customer trust, better warranty performance, and higher capital efficiency. Even digital maturity shows up here not in the aesthetics of dashboards, but in how effectively an organization prevents failures, resolves incidents, and learns from the field.
Santosh’s framing is telling: “Digital excellence for us is measured not in dashboards, but in disciplined execution.” Uptime is simply the visible outcome of invisible rigor across design, production, service networks, and operations.
The Customer Journey to Fix First: Incident-to-Resolution
If you want to understand commercial EV adoption, don’t look at the sales funnel. Look at the moment something breaks.
When asked which customer journey he’d improve “tomorrow” for fleet operators, Santosh points directly to the incident-to-resolution cycle. Fleet operators judge OEMs less by promises and more by how fast vehicles return to service.
This journey includes everything that happens after a fault appears: detection, diagnosis, parts coordination, technician dispatch, approvals, repair, verification, and the final return to duty. Each minute is expensive. Each delay creates friction between operator expectations and OEM reality.
Santosh’s focus is to compress the time from fault detection to vehicle back in service, using better diagnostics and smoother workflows. The operational payoffs are concrete: reduced downtime, improved first-time fix rates, lower emergency costs, and stronger satisfaction.
In commercial EVs, he underlines, speed of resolution is revenue protection. That’s why digital’s job is not merely to “inform,” but to orchestrate action moving from visibility to closure.
AI Where It Pays Fast: Predictive Maintenance
AI has become an obligatory headline in mobility. But Santosh is blunt about what actually delivered ROI first.
The highest-return AI use case at Switch so far is predictive maintenance “without question.”
Why? Because it flips the service model from reactive to preventive. Fewer breakdowns mean fewer roadside incidents, fewer unplanned service events, and a cleaner warranty curve. It also reduces service complexity and improves customer confidence because operators don’t want to know a failure happened; they want it not to happen at all.
Switch’s approach analyzes real-time vehicle data and detects patterns that historically preceded component issues. When anomalies appear, the system triggers proactive interventions before those issues become breakdowns.
The practical impact shows up in the outcomes Santosh lists: reduced roadside failures, lower warranty claims, improved vehicle availability. Charge optimization, he adds, will matter more over time but predictive maintenance was the fastest route from raw data to operational value.
In other words: AI succeeds when it is tied to field outcomes, not lab demonstrations.
Beyond OTA: The Next Leap Is the Operational Digital Twin
Software-defined vehicles are reshaping the industry, and OTA updates often take center stage. Santosh agrees they’re foundational—because they allow remote fixes, improvements, and performance tuning without physical recalls.
But he points to the next stage: operational digital twins.
Not the static replicas some industries talk about but living models that combine a vehicle’s condition with duty cycles, energy usage, environment, and usage behaviors. That is where monitoring becomes foresight.
Operational digital twins, Santosh says, tighten engineering feedback loops, improve service preparedness, and guide product evolution. They enable scenario modeling: predicting component wear, optimizing maintenance schedules, and aligning service protocols with real-world usage.
The long-term value is strategic: field data feeds design, manufacturing adapts to actual performance, and service becomes more precise with time. It’s the promise of a learning system where each deployment improves the next.
Scaling Telematics: Tech Scales Fast, Operations Don’t
When Switch expanded telematics across multi-city deployments, Santosh encountered a common but underappreciated truth: technology scales faster than operations.
Cities differ traffic density, depot discipline, driver behavior, service practices. The same vehicle can perform differently across locations not because the vehicle changed, but because the operational ecosystem did.
The lesson wasn’t about data collection. That part was doable. The true challenge was creating consistent operating standards so insights could be reused across locations rather than staying trapped in local contexts.
Switch responded by building standardized operational playbooks deployed across cities. Without process consistency, Santosh argues, digital insights remain local. With standardization, those insights become enterprise leverage.
It’s a manufacturing mindset applied to operations: the goal isn’t just intelligence it’s repeatability.
UK to India: What Transfers and What Breaks
Switch operates across markets, and that exposes a practical reality: what works beautifully in one region can fail quietly in another.
From the UK market, Santosh says Switch adopted operability-first design: building vehicles with serviceability, diagnostics, and lifecycle cost visibility embedded from day one. That means easier maintenance access, standardized diagnostics, and the ability to service critical components quickly without specialized equipment.
The payoff is clear: lower service time, reduced training needs, and better technician productivity.
But one assumption does not translate neatly to India: uniform infrastructure.
In India, variability is structural power reliability, operating conditions, depot practices, road quality. A digital system optimized for ideal conditions will eventually disappoint.
So Switch designs for resilience: offline modes for connectivity gaps, voltage tolerance for power fluctuations, robust error handling for unexpected conditions. “Designing for variability,” Santosh implies, is as important as designing for performance.
In emerging markets, the best digital systems are not the most elegant. They are the most forgiving.
The Toughest Challenge Isn’t Sensors—It’s Data Quality
Perhaps the most revealing part of Santosh’s perspective is what he calls the hardest challenge in EV digital adoption: data quality.
Not because it’s a tooling problem, but because it reflects how people work.
“You can deploy sensors and platforms quickly,” he notes, “but disciplined data capture, validation, and usage require process change.”
That’s the cultural layer many transformations underestimate. Data quality is governance, workflow discipline, and accountability. It’s an organizational change challenge, not just an IT initiative.
Without governance, analytics becomes noise. With discipline, it becomes advantage.
Switch approached this with data quality checkpoints at every stage: validation rules, mandatory field requirements, audits, and feedback loops that teach teams why accurate data matters. The impact shows up in improved completeness rates, fewer invalid entries, and stronger analytical accuracy.
Digital maturity, in this framing, is a behavioral system as much as it is a technical stack.
Partnerships That Matter: Insight Must Lead to Action
In a crowded EV technology ecosystem, partnerships are easy to announce and hard to operationalize. Santosh draws a bright line between those that help and those that become debt.
The partnerships that changed the game, he says, are the ones that connect insight directly to action analytics embedded into service workflows, engineering loops, and field operations. If insight doesn’t change behavior, it doesn’t create value.
What would he avoid in hindsight? Solutions that scale pilots but not factories or fleets.
Because manufacturing scale is the real stress test. A proof-of-concept can look fantastic with a few vehicles and a controlled environment. But if it cannot handle thousands of vehicles, hundreds of service points, and diverse operating conditions, it becomes technical debt.
Switch’s partner lens is therefore pragmatic: understand manufacturing constraints, service realities, and operational complexity or don’t enter the stack.
The One Widget Every Fleet Operator Needs: A 48-Hour Risk Radar
Finally, Santosh offers a simple vision for the future of fleet operations one that goes beyond today’s dashboards. If he could give fleet operators just one widget, it would be a forward-looking risk indicator: which vehicles are most likely to underperform or fail in the next 48 hours, and what preventive action would avoid it.
This is the shift from visibility to anticipation. Most dashboards tell you what happened, or what is happening. Predictive intelligence tells you what will happen and what to do next.
Done right, this transforms fleet management from reactive firefighting to proactive risk management. The benefits are operational and financial: fewer emergency service calls, smarter technician scheduling, optimized spares inventory, lower downtime costs, and higher utilization.
But Santosh’s framing is important: prediction alone is not enough. The system must also deliver clear action protocols because forecasting without execution is just another chart.
A Manufacturing-Grade View of Digital
Across the conversation, one theme repeats: Switch doesn’t treat digital as decoration. It treats it as industrial infrastructure built for scale, resilience, and repeatability.
In a sector where many conversations still orbit around apps and interfaces, Santosh pulls the spotlight back to fundamentals: uptime, serviceability, operational consistency, and disciplined data. It’s a product-led worldview, where digital earns its place by improving reliability not by generating more screens.
As electric mobility accelerates, the winners will likely be those who understand this simplest of truths: the future isn’t just electric it’s operational.
And in that world, the digital backbone isn’t a feature. It’s the factory floor, the service bay, and the fleet route connected into one learning system that keeps vehicles moving.