Unlocking the Future of Field Service Optimization with GenAI-powered Yantr.ai

Introduction
The global field service management (FSM) market was valued at ~$4 billion in 2020 and is projected to reach $24.29 billion by 2030, growing at a CAGR of 19.7% from 2023 to 2030 (Valuates Reports, 2024). FSM primarily concerns the management and optimization of resources employed outside of the company’s properties to perform field service tasks.
In recent years, the number of FSM tools has rapidly increased. Businesses are relying on these tools to reduce expenses, increase productivity, and enhance customer satisfaction. Due to modern technology and the expanding need for field services, more efficient solutions that will save businesses money and effort while providing better customer service are in demand. Generative AI (GenAI) and machine learning (ML) infrastructure are massively transforming the FSM market. As field operations become more complex and customer expectations for faster, more efficient service rise, companies seek creative ways to simplify their operations.
Key Challenges in the Field Service Industry
FSM focuses on the efficient management of resources utilized to complete tasks outside of the company’s premises. Millions of field service technicians are always working on projects. To meet the increasing demand, numerous companies actually hire hundreds of field technicians. However, a few obstacles could prevent organizations from providing effective and fulfilling field services. These may include the following:
- Work Order Management: Inefficient workflow processes resulting in decreased productivity and suboptimal efficiency levels.
- Overhead Cost: Administrative expenses, traveling costs, training, and fixed asset maintenance impacting overall profitability.
- Invoice & Payment Management: Multiple payment cycles may lead to errors and lack of integration.
- Route Planning: Lack of tools to track and monitor live locations.
- Real-Time Communication: Delay in information sharing between field force and back-office.
- Efficiency & Productivity: Lack of data to identify underlying issues, poorly set metrics, and insufficient data support for forecasting.
- Scheduling & Dispatch: Time-consuming manual processes cause scheduling conflicts.
Yantr.ai –Reimagining Field Services for enterprises
Tech Mahindra BPS has developed Yantr.ai, a software as a service (SaaS) + business process as a service (BPaaS) solution. The Yantr.ai platform is powered by AWS services such as Amazon Bedrock, AWS Lambda, and Amazon Simple Storage Service (Amazon S3). This helps optimize field services operations through GenAI-based dynamic decision-making support, deep analytical insights, and future-proof planning. It integrates people, data, and technology to hyperautomate, optimize, and improve field service operations and customer experience.
Yantr.ai delivers intelligent, autonomous execution and end-to-end visibility through people, data, and innovative technology. This lowers operating costs and increases customer satisfaction.
Unlocking the power of Yantr.ai: Key Features and Offerings
The features of Yantr.ai provide businesses with a range of short-, mid-, and long-term advantages, including enhanced customer service, faster response times, and resource and time savings. To address market gaps and differentiate itself from other FSM providers, Yantr.ai provides a variety of features:
- End-to-End Visibility (Control Tower): Provides a centralized view of operations for seamless monitoring and proactive issue resolution across the supply chain.
- Strategic and Operational Planning: Enables data-driven decision-making to optimize resources and align operations with business objectives for long-term success.
- On-the-Day Risk Management (Jeopardy Planning): Monitors real-time risks and proactively manages disruptions to ensure operational continuity and service level adherence.
- Supply Optimization (Long Term, Short Term, Mid Term): Optimizes inventory and supply chain strategies across varying time horizons to minimize costs and enhance service efficiency.
- Scenario Modeling (Extreme Event Management): Simulates extreme scenarios to prepare and mitigate the impact of unexpected events, ensuring robust operational resilience.
- Route Optimization: Streamlines route planning to minimize travel time and fuel costs while maximizing service efficiency and technician productivity.
- ADAM (GenAI Assistant): Leverages GenAI to provide technicians with real-time assistance, knowledge retrieval, and decision support in the field.
Yantr.ai Architecture
Yantr.ai runs on an event-driven, serverless architecture to enable developers to run code without provisioning or managing servers. The GenAI services are offered through Amazon Bedrock, which offers a choice of high-performing foundation models (FMs) through a single API, along with a broad set of functions for security, privacy, and responsible AI. Other components of Yantr.ai architecture include:
- User Interaction via React Frontend: Field technicians use a react-based frontend to input queries, which are processed by the backend for actionable responses. The front end runs on Amazon Elastic Kubernetes Service (Amazon EKS).
- ADAM Backend: ADAM is a field technician assist module that leverages AWS GenAI services to provide field technicians with real-time, contextual support. This significantly enhances their productivity and efficiency by offering technical information on equipment and guiding them through procedural steps.
- Amazon Bedrock Agents: Bedrock agents orchestrate the foundation model, knowledge base, AWS Lambda functions, and user queries, managing API calls and data flow.
- Action Group Execution: Bedrock Agents use action groups to fetch necessary data via APIs, ensuring the correct information is retrieved based on the technician’s query.
- Foundation Models: Amazon Bedrock provides foundation models accessed by agents for embeddings and response generation.
- Data Ingestion and Object Storage: Using an automated data ingestion pipeline managed by Apache Airflow DAGs, with AWS services handling data processing transformation and secure storage in S3 buckets.
- Embedded Storage: Documents are converted into embeddings via foundation models and stored in a knowledge base for quick retrieval.
- AWS Lambda Functions: These functions handle user requests by coordinating data retrieval and response structuring through Amazon Bedrock Agents.
- Best Practices: AWS Identity and Access Management (IAM) controls access to services and resources with minimum access. All data is encrypted at rest and in transit.
Customer Benefits
Tech Mahindra’s Yantr.ai has transformed field services for its customers across domains and geographical locations by improving customer experience, optimizing the total field spent, and delivering operational efficiency. Yantr.ai helps streamline operations by reducing wasteful practices and allowing administrative staff to concentrate on more strategic tasks. This optimization boosts revenue, controls expenses, and leverages the full potential of the evolving work environment.
The following benefits have been realized by existing Yantr.ai customers:
- Tech Efficiency: Achieved a ~7% increase in internal technician productivity and a 15% improvement in experience
- SLA Enhancement: Improved SLA by ~ 4% – 7%
- NPS Boost: Improved NPS by ~ 5-7%
- Production Boost: Improved efficiency of the workflow control center by approximately 15%
- Brand Elevation: Improved brand perception and strategic positioning
Success Stories: Yantr.ai in Action
Dispatching technicians and allocating resources proved to be problematic for a telecommunications and media giant and one of Tech Mahindra’s prominent customers. There was a lot of downtime and disgruntled customers due to the inefficiency of traditional methods. By implementing Yantr.ai, customers were able to maximize technician routes, anticipate equipment failures, and significantly reduce total downtime and other benefits like:
- 25% improvement in efficiencies of the field back-office team
- 10% improvement in technicians' productivity
- 5% improvement in NPS
This real-world use case demonstrates that Yantr.ai can transform field service operations and improve customer satisfaction and operational efficiency.
Summary
By utilizing GenAI to enhance operations and increase productivity, Yantr.ai is revolutionizing the FSM sector. Tech Mahindra’s collaboration with AWS enables them to leverage the latest AWS GenAI and cloud services, providing their customers with secure and scalable solutions.
Yantr.ai can transform your field service operations, resulting in higher customer satisfaction, decreased downtime, and increased efficiency. Experience firsthand the revolutionary power of GenAI in FSM by visiting Yantr.ai and connecting with the Tech Mahindra team.
Tech Mahindra – AWS Partner Spotlight
Tech Mahindra is an AWS Premier Tier Services Partner and MSP that specializes in digital transformation, consulting, and business re-engineering solutions.

Praveen is a seasoned Product/Practice Leader at Yantr.ai, Tech Mahindra, with extensive experience in creating and implementing AI-powered solutions. He specializes in developing strategies that enhance operational efficiencies, particularly in the field service domain. His expertise lies in bridging the gap between technology and business needs to deliver scalable and impactful products.

As a Product/Practice Leader at Yantr.ai, Tech Mahindra, Abhinav has been instrumental in leveraging AI and automation technologies to transform FSM. He focuses on crafting user-centric solutions that streamline workflows and improve productivity. With a keen eye for innovation, Abhinav drives projects that deliver measurable outcomes for clients.

Gaurav, a Technical Lead at Yantr.ai, Tech Mahindra, has a strong background in designing and implementing robust AI and machine learning frameworks. He is dedicated to building high-performing technical architectures that address real-world challenges in field service optimization. His hands-on approach ensures reliable and efficient solution delivery.

Mohammad is an Associate Vice President in the AWS Business Unit at Tech Mahindra. He brings a wealth of expertise in cloud computing, specializing in integrating AWS services with AI-driven solutions. His focus is on delivering tailored, scalable platforms that help organizations achieve operational excellence and digital transformation.

Nirmal is a Senior Solutions Architect at AWS with deep experience designing innovative and scalable cloud-based solutions. His expertise lies in leveraging the full potential of AWS services to address complex customer needs. Nirmal’s approach ensures seamless integration and efficient project execution across industries.

Aadesh is an Analyst at Yantr.ai, Tech Mahindra, where he supports strategic planning and the development of AI-driven solutions. His analytical skills and insights are critical in shaping strategies that address operational challenges. Aadesh is passionate about using data to drive decision-making and optimize service outcomes.