67% of consumers worldwide used a chatbot for customer support in the past year, a report from Invesp in 2023 suggests. Conversational AI and Enhanced Customer Experience have become almost synonymous and complementary to each other. By bringing round-the-clock service, personalized support, and instant resolution to the table, Conversational AI has redefined the consumer industry landscape.

Emergence of Conversational AI

Conversational AI is a sophisticated technology that facilitates human-like interaction through machines. This realm of AI includes but isn’t limited to:

Chatbots
Voice assistants
AI-powered messaging applications

Conversational AI has wide range of applications across consumer industries

Working Mechanism

Relying on Machine Learning, Natural Language Processing (NLP), and complex AI algorithms, these technologies accurately interpret human language, understand the context, and deliver fitting responses.

Conversational AI: A Customer Experience Game-Changer

Impact on Customer Experience

Embedding Conversational AI and Enhanced Customer Experience can lead to a 25% elevation in operational efficiency by 2025 (Gartner). This technological leap allows businesses to cater to the evolving expectations of customers who prefer immediate and personalized service.

Case Study: ICICI Bank’s Leap Towards AI

Taking a step towards AI, ICICI Bank, India, launched a voice-based AI assistant to help customers with banking transactions and services. The AI assistant significantly reduced service delivery time and eased the burden of customer service representatives. It impressively handled over 7.2 million queries in its first year, demonstrating AI’s potential in managing large-scale customer interactions.

Conversational AI: Setting New Standards in Customer Service

Case Study: Myntra’s FashionGPT

Fashion e-commerce giant, Myntra, entered the Conversational AI space with the innovative MyFashionGPT. Designed to answer fashion-related queries, it created a personalized shopping experience for customers.

Case Study: Mantra Lab’s Hitee Chatbot

Tech innovation firm Mantra Labs transformed customer service in the healthcare sector with their Hitee Chatbot. Designed to answer queries related to insurance claims, appointments, and healthcare services, Hitee has significantly improved service delivery time and customer satisfaction. The chatbot helped the company reduce their response time by 60%, highlighting the efficiency that Conversational AI can bring to customer service.

Personalization: The Key to Enhanced Customer Experience

Emphasizing Individuality with AI

Conversational AI is not just about addressing customer queries, it’s about understanding each customer’s unique needs. By using machine learning algorithms and large datasets, AI can tailor responses based on customer’s previous interactions, ensuring a truly personalized experience.

Case Study: Spotify’s AI Recommendation System

Take Spotify for instance. While it’s not a conventional chatbot, it leverages the power of Conversational AI to understand user preferences and recommend music. As a result, it creates a unique, individualized experience for its millions of users.

Conversational AI: Beyond Customer Service

Expansion to Other Sectors

While Conversational AI has largely been utilized in customer service, it’s potential goes beyond. Industries from healthcare to finance are harnessing the power of AI to streamline operations and improve user experience.

Case Study: Ada Health’s AI-Powered Symptom Checker

Ada Health, a global health company, has developed an AI-powered symptom checker that interacts with users to understand their health issues and provide possible diagnoses. It serves as a primary example of how Conversational AI can enhance user experience beyond traditional customer service.

Addressing Challenges and Ethical Considerations

Privacy and Security

As AI becomes more integrated into our lives, concerns around privacy and security grow. Businesses leveraging Conversational AI must ensure robust security measures to protect sensitive customer information.

Building Trust

For AI to be successful, businesses must also build trust with customers. Transparency around data usage can help build this trust and ensure customers feel comfortable interacting with AI.

Investment Trends and Future Potential

Companies across the globe are ramping up their investments in Conversational AI to stay ahead of the curve. Global spending on Conversational AI is projected to reach $5.5 billion by 2024, a staggering growth from $3 billion in 2019 (MarketWatch).

Mantra Labs, a frontrunner in this area, is investing heavily in Conversational AI to develop innovative solutions that enhance customer experiences. Their work is reflective of a larger global trend as more companies recognize the potential of Conversational AI and Enhanced Customer Experience.

Looking ahead, the consumer industry can anticipate a future dominated by more sophisticated AI tools that can understand complex queries, comprehend different languages, and offer even more personalized solutions. Conversational AI is not merely a fleeting trend but a fundamental shift in how businesses connect with their customers. The future of customer experience is here, and it’s automated, instant, and intelligent.

Conclusion

With its potential to deliver personalized, efficient, and round-the-clock customer service, Conversational AI is truly revolutionizing the consumer industry. However, as with any technology, businesses must be aware of and address potential challenges, particularly around privacy and trust. The future of Conversational AI in customer experience is bright, and it’s just the beginning of what’s to come.

Smart Manufacturing Dashboards: A Real-Time Guide for Data-Driven Ops

By : Divyanjali Gupta

Published on Jul 31, 2025

Data Science Manufacturing Analytics Smart Manufacturing

Smart Manufacturing starts with real-time visibility.

Manufacturing companies today generate data by the second through sensors, machines, ERP systems, and MES platforms. But without real-time insights, even the most advanced production lines are essentially flying blind.

Manufacturers are implementing real-time dashboards that serve as control towers for their daily operations, enabling them to shift from reactive to proactive decision-making. These tools are essential to the evolution of Smart Manufacturing, where connected systems, automation, and intelligent analytics come together to drive measurable impact.

Data is available, but what’s missing is timely action.

For many plant leaders and COOs, one challenge persists: operational data is dispersed throughout systems, delayed, or hidden in spreadsheets. And this delay turns into a liability.

Real-time dashboards help uncover critical answers:

What caused downtime during last night’s shift?
Was there a delay in maintenance response?
Did a specific inventory threshold trigger a quality issue?

By converting raw inputs into real-time manufacturing analytics, dashboards make operational intelligence accessible to operators, supervisors, and leadership alike, enabling teams to anticipate problems rather than react to them.

1. Why Static Reports Fall Short

Reports often arrive late—after downtime, delays, or defects have occurred.
Disconnected data across ERP, MES, and sensors limits cross-functional insights.
Static formats lack embedded logic for proactive decision support.

2. What Real-Time Dashboards Enable

Line performance and downtime trends
Track OEE in real time and identify underperforming lines.

Predictive maintenance alerts
Utilize historical and sensor data to identify potential part failures in advance.

Inventory heat maps & reorder thresholds
Anticipate stockouts or overstocks based on dynamic reorder points.

Quality metrics linked to operator actions
Isolate shifts or procedures correlated with spikes in defects or rework.

These insights allow production teams to drive day-to-day operations in line with Smart Manufacturing principles.

3. Dashboards That Drive Action

Role-based dashboards
Dashboards can be configured for machine operators, shift supervisors, and plant managers, each with a tailored view of KPIs.

Embedded alerts and nudges
Real-time prompts, like “Line 4 below efficiency threshold for 15+ minutes,” reduce response times and minimize disruptions.

Cross-functional drill-downs
Teams can identify root causes more quickly because users can move from plant-wide overviews to detailed machine-level data in seconds.

4. What Powers These Dashboards

Data lakehouse integration
Unified access to ERP, MES, IoT sensor, and QA systems—ensuring reliable and timely manufacturing analytics.

ETL pipelines
Real-time data ingestion from high-frequency sources with minimal latency.

Visualization tools
Custom builds using Power BI, or customized solutions designed for frontline usability and operational impact.

Smart Manufacturing in Action: Reducing Market Response Time from 48 Hours to 30 Minutes

Mantra Labs partnered with a North American die-casting manufacturer to unify its operational data into a real-time dashboard. Fragmented data, manual reporting, delayed pricing decisions, and inconsistent data quality hindered operational efficiency and strategic decision-making.

Tech Enablement:

Centralized Data Hub with real-time access to critical business insights.
Automated report generation with data ingestion and processing.
Accurate price modeling with real-time visibility into metal price trends, cost impacts, and customer-specific pricing scenarios.
Proactive market analysis with intuitive Power BI dashboards and reports.

Business Outcomes:

Faster response to machine alerts
Quality incidents traced to specific operator workflows
4X faster access to insights led to improved inventory optimization.

As this case shows, real-time dashboards are not just operational tools—they’re strategic enablers.

(Learn More: Powering the Future of Metal Manufacturing with Data Engineering)

Key Takeaways: Smart Manufacturing Dashboards at a Glance

Aspect	What You Should Know
1. Why Static Reports Fall Short	Delayed insights after issues occur Disconnected systems (ERP, MES, sensors) No real-time alerts or embedded decision logic
2. What Real-Time Dashboards Enable	Track OEE and downtime in real-time Predictive maintenance using sensor data Dynamic inventory heat maps Quality linked to operators
3. Dashboards That Drive Action	Role-based views (operator to CEO) Embedded alerts like “Line 4 down for 15+ mins” Drilldowns from plant-level to machine-level
4. What Powers These Dashboards	Unified Data Lakehouse (ERP + IoT + MES) Real-time ETL pipelines Power BI or custom dashboards built for frontline usability

Conclusion

Smart Manufacturing dashboards aren’t just analytics tools—they’re productivity engines. Dashboards that deliver real-time insight empower frontline teams to make faster, better decisions—whether it’s adjusting production schedules, triggering preventive maintenance, or responding to inventory fluctuations.

Explore how Mantra Labs can help you unlock operations intelligence that’s actually usable.

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