Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(21)

Clean Tech(9)

Customer Journey(17)

Design(45)

Solar Industry(8)

User Experience(68)

Edtech(10)

Events(34)

HR Tech(3)

Interviews(10)

Life@mantra(11)

Logistics(6)

Manufacturing(3)

Strategy(18)

Testing(9)

Android(48)

Backend(32)

Dev Ops(11)

Enterprise Solution(33)

Technology Modernization(9)

Frontend(29)

iOS(43)

Javascript(15)

AI in Insurance(38)

Insurtech(66)

Product Innovation(59)

Solutions(22)

E-health(12)

HealthTech(24)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(153)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(8)

Computer Vision(8)

Data Science(23)

FinTech(51)

Banking(7)

Intelligent Automation(27)

Machine Learning(48)

Natural Language Processing(14)

expand Menu Filters

AI’s Insatiable Appetite: Powering Innovation Sustainably

AI dazzles us with its feats, from chatbots understanding our queries to language models spinning creative tales. But have you pondered the colossal energy needed to fuel these technological marvels?

Research from the University of Massachusetts Amherst reveals that training a single behemoth like GPT-3, a titan among language models, emits carbon equivalent to 300,000 cars’ lifetime emissions. That’s akin to a medium-sized European town’s carbon output! And brace yourself: emissions from natural language processing doubled yearly till 2020, now rivaling the aviation industry’s impact. It’s as if countless planes continuously encircle the globe.

AI: Here to Stay, but at What Expense?

Yet, pulling the plug on AI isn’t an option. It’s entrenched in our lives, propelling innovation across sectors from healthcare to finance. The challenge? Balancing its ubiquity with sustainability.

The scale of energy consumption in the AI sector is staggering. According to a recent report by the International Energy Agency (IEA), global electricity consumption by AI data centers alone is projected to surpass 1,000 terawatt-hours annually by 2025, equivalent to the current electricity consumption of Japan and Germany combined. Such figures underscore the urgent need to address the environmental implications of AI’s rapid expansion.

AI: Here to Stay, but at What Expense? Indeed, the environmental cost is profound, necessitating concerted efforts from all stakeholders to reconcile AI’s benefits with its energy footprint.

Solutions for a Greener AI

Efforts span both hardware and software realms. Firms invest in energy-efficient hardware, like specialized chips and accelerators, and refine algorithms through compression and pruning, yielding environmental gains and cost savings.

Then there are the colossal data centers housing AI infrastructure. Leading cloud providers are pivoting to renewable energy sources and pioneering cooling systems, even exploring underwater data centers for natural cooling.

The Energy Consequences of AI:

  • AI’s adoption demands extensive energy, notably during training.
  • Balancing AI’s reach with energy efficiency is critical.
  • AI’s energy consumption contributes to environmental harm.
  • Urgent measures are needed to curb AI’s energy footprint.
  • Collaborative efforts are vital to mitigate AI’s energy-related impacts.
Technology

Policy and Partnerships: Leading the Charge

Governments worldwide are stepping into the fray, recognizing the urgent need for sustainable AI practices. Through a combination of regulations, incentives, and collaborative initiatives, policymakers are shaping a landscape where environmental consciousness is ingrained in technological innovation.

From establishing carbon emission targets specific to the AI sector to offering tax credits for companies adopting renewable energy solutions, governmental interventions are driving significant shifts towards sustainability. Additionally, partnerships between the public and private sectors are fostering innovative approaches to address the energy consumption dilemma without stifling technological advancement.

Urging Responsibility in AI Development: Setting the Standard

The responsibility falls not just on policymakers but also on AI developers and researchers to embed energy efficiency into the very fabric of AI design and implementation. By prioritizing sustainability metrics alongside performance benchmarks, the industry can pave the way for a greener future.

This involves not only optimizing algorithms and hardware but also cultivating a culture of environmental consciousness within AI development communities. Through knowledge-sharing, best practices, and collaborative research efforts, developers can collectively contribute to mitigating the environmental impact of AI technologies while maximizing their benefits.

Global Cloud Computing Emissions
(Source: Climatiq)

A Tale of Sustainable Success

Mantra Labs, in partnership with Viteos, developed advanced machine learning algorithms to optimize brokerage selection for specific trades and expedite insights from historical profit and loss (P&L) data. Our AI-enabled solution utilizes regression, outlier detection, and feature selection models to analyze historical transactions, trades, and financial data. It empowers Viteos’ users to efficiently identify the lowest-commission broker for their trades while ensuring rapid and accurate data insights. Our approach offers flexibility across diverse datasets and optimizes memory utilization, enhancing scalability and efficiency. To read the case study, click here.

Shaping an Energy-Efficient AI Future

AI’s future is luminous, but it must be energy-efficient. With collaborative efforts spanning tech firms, developers, policymakers, and users, we can safeguard the planet while advancing technological frontiers.

By embracing energy-smart practices and renewable energy, we can unlock AI’s potential while minimizing ecological fallout. The moment for action is now, and each stakeholder plays a pivotal role in crafting a sustainable AI tomorrow.

Cancel

Knowledge thats worth delivered in your inbox

Sales Applications Are Disrupting More Than Just Sales

Sales success today isn’t about luck or lofty goals—it’s about having the right tools in your team’s hands, wherever they go. Following our earlier in-depth exploration of sales technology, we will now examine how cutting-edge sales apps are becoming the backbone of modern industries, transforming complex workflows into seamless, growth-driving machines.

From retail to healthcare, logistics to real estate, businesses are deploying sales applications to enhance operational transparency, cut redundant tasks, and build intelligent sales ecosystems. These tools are not only digitizing workflows—they’re driving growth, improving engagement, and redefining how field teams operate.

Lead Ecosystems: Unified visibility across channels

One app. Five workflows. Zero friction.

A leading insurance brand relaunched their app—a sleek, powerful sales companion that’s turning everyday agents into top performers.

No more paperwork. More time to sell.

Here’s what changed:

  • Every visit is tagged, tracked, and followed through. Renewals? Never missed. Leads? Fully visible.
  • Attendance and reimbursements went on autopilot. No more manual logs. No more chasing approvals.
  • New business and renewals are tracked in real time, with accurate forecasting that sales leaders can finally trust.
  • Dashboards are clean, configurable, and useful—insights that move the business, not just report on it.
  • Seamless Integrations. API connectivity with Darwin Box, IMD Master Data, and SSO authentication for a unified experience.

The result? A field team that moves faster, sells better, and works smarter.

Retail: Taking Orders from the Frontline—Smartly

Field sales agents in retail, especially FMCG, used to rely on gut instinct. Now, with intelligent sales applications:

  • AI recommends what to upsell or cross-sell based on previous order patterns
  • Real-time stock availability and credit status are visible in the app
  • Geo-fencing ensures optimized route planning
  • Built-in payment collection modules streamline transaction closure

Healthcare: Structuring Sales with Compliance and Precision

Healthcare leaders don’t need more reports—they need better visibility from the field.  Whether it’s engaging hospital networks, onboarding clinics, or enabling diagnostics at the last mile, everything needs precision, compliance, and clarity. 

Mantra Labs helped a leading healthcare enterprise design a sales app that integrates knowledge, compliance, performance, and recognition, turning frontline agents into informed, aligned, and empowered brand advocates. 

Here’s what it delivers:

  • Role-based onboarding that keeps every level of the field force aligned and accountable
  • Escalation mechanisms are built into the system, driving transparency across commissions and performance reviews
  • A centralized Knowledge Hub featuring healthcare news, service updates, and training modules to keep reps well-informed
  • Recognition modules that celebrate milestones, boost morale, and reinforce a culture of excellence

Now, the field agents aren’t just connected—they’re aligned, upskilled, and accountable.

Real Estate: From Cold Calls to Smart Conversions

For real estate agents, timing and personalization are everything. Sales applications are evolving to include:

  • Virtual site tour integration for remote buyers
  • Mortgage and EMI calculators to increase buyer confidence
  • WhatsApp-based lead capture and nurture sequences
  • CRM integration for inventory updates and automatic scheduling

Logistics: From Chaos to Control in Field Coordination

Field agents in logistics are switching from clipboards to real-time command centers on mobile. Modern sales applications offer:

  • Live delivery status and route deviation alerts
  • Automated dispute reporting and issue resolution tracking
  • Fleet coordination through integrated GPS modules
  • Customer feedback capture and SLA dashboards

What’s new & what’s next in Sales Applications?

Here’s what’s pushing the next wave of innovation:

  • Voice-to-Text Logging: Agents dictate notes while on the move.
  • AI-Powered Nudges: Apps that suggest next-best actions based on behavior.
  • Omnichannel Communication: In-app chat, WhatsApp, email—unified.
  • Role-Based Dashboards: Different data views for admins, managers, and field reps.

What does this mean for Business Leaders?

Sales Applications are not just tactical tools. They’re platforms for transformation. With the right design, integrations, and analytics, they:

  • Replace guesswork with intelligence
  • Reduce the cost of delay and manual labor
  • Improve agent accountability and transparency
  • Speed up decision-making across hierarchies

The future of field sales lies in intuitive, AI-driven applications that adapt to every industry’s nuances. At Mantra Labs, we work closely with enterprises to custom-build sales applications that align with business objectives and ground-level realities.

Conclusion: 

If your agents still rely on Excel trackers and daily call reports, it’s time to reimagine your sales operations. Let us help you bring your field operations into the future—with tools that are fast, field-tested, and built for scale.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot