Behind automation for deskless workers, with Maximl CEO Pankaj Pawan
In a survey conducted by Meta’s Workplace, 74% of deskless workers believe there are barriers to communication at work, especially in working as teams. It is safe to say that this is the new sphere being explored through automation, making the workplace better and efficient for deskless workers. The Chennai-based start-up, Maximl, is India’s first connected worker platform for deskless workers, digitising their on-field workflows. The start-up has a strong portfolio of some of India’s top refineries and is on an expansion plan to share its services abroad. Analytics India Magazine got in touch with Maximl’s co-founder and CEO, Pankaj Pawan, to learn more about the no-code/low-code platform’s tech and offerings. AIM: What was the pain point that Maximl was trying to solve? While starting Maximl, we observed a massive underutilisation of technology in process and manufacturing shop floors run by a 500M strong deskless workforce. Despite digital advancements, much of the manufacturing sector still relies on paper and spreadsheets for collaboration. There is massive underutilisation of digital tools in process and manufacturing shop floors that employ a whopping 500M strong deskless workforce. We launched Maximl with the objective of bringing standardisation and simplifying collaboration on the shop floor for the workforce. We spent a significant amount of time understanding the pain points of the workforce and realised they did most of the work but yet were the least digitally empowered section. We firmly believe that digital interventions could significantly improve safety and productivity on the shopfloors. Initially, we focused on a particular use case of enabling collaboration for O&G turnarounds, which were a big pain area for everyone. We helped them achieve real-time visibility across the teams and automated their manual workflows to focus on high-value tasks. We have come a long way since then and serve several industries across multiple use cases, but the goal remains the same – connecting people among themselves and with the machines to enable them to work in a more productive and safer environment. Maximl is the only tech company in India to have digitised over 80 massive-scale industrial maintenance projects. As of now, we have strong engagements with 8 of 10 Indian refining companies. We are also working with three of the top 5 Fortune 500 companies in the country. We also signed long-term contracts with Indian Oil to digitise all of their turnaround maintenance across nine sites. AIM: Please discuss how your flagship no-code/low-code services are helping various sectors in India. Our Connected Worker Platform enables heavy industries, especially manufacturing sectors, to gain digital control of their complex processes through machine learning. We are a one-stop solution to digitise all shop floor operations across maintenance, EHS, quality, and production. We automate on-field workflows, ensure effective training of frontline workers, knowledge sharing, measurement of compliance, and superior collaboration. As a result, we reduce variability in manufacturing outcomes. We enable companies to shift their focus on digital operational excellence and frontline workers’ empowerment. We firmly believe moving away from a traditional paper, spreadsheet, and tribal knowledge to a paperless and connected world will unlock massive new growth opportunities in the company’s value chain. AIM: Please explain the tech stack used behind creating a no-code or low-code platform. Being a SaaS platform that is the intelligent layer between people in Industry 4.0, the tech stack that Maximl uses is highly geared towards creating engaging experiences that drive the adoption of tech in a space that is used for traditional paper-based coordination. The platform is geared towards mobility, with curated experiences for mobile & tablet use across platforms – iOS & Android. Optimised algorithms for synchronisation ensure seamless use in low-connectivity settings, especially since our end users operate in environments with metallic surroundings, leading to a Faraday cage effect of poor connectivity. Intrinsically safe devices are used for hydrocarbon-rich environments. The digital transformation that our clients experience has always led to a massive onslaught of media interactions, with users uploading terabytes of images and videos on the platform within days. The tech stack leverages cloud services from Azure & AWS for seamless delivery of media to dashboards, viewed on both laptops as well as on monitoring displays and meeting room projectors. The platform is architected for a global scale, with multi-region deployments, in line with latency as well as compliance requirements, which come from the sensitive data that is held by the platform. The platform is based on a combination of monoliths and microservices, connected using an event-driven model. Our servers are hosted in the Americas, Europe, India and South Asia. The sensitivity of the data involved is addressed using multiple levels of safeguards that ensure both cost efficiency as well as data isolation. The powerful backend provides real-time computations and insights, reducing the time of analysis from over two days, using traditional analysis tools, to under minutes. The system analyses thousands of resources along with over 30000 variables about the people, project and plant, in order to provide real-time insights about optimal project planning & execution. All in all, the architecture and tech stack have been built to solve the biggest challenge: driving an industry used to traditional modes of operation into a digital world of Industry 4.0. The stack has successfully achieved this with thousands of users across 50+ sites and four continents and millions of dollars of savings through insights at each site. AIM: How does Maximl’s service help the refining sector? Share some real-life case studies of your products. Maximl’s platform helps refineries unlock the potential for productivity improvements of the large frontline workforce by more than 5 per cent and reduce the risk of safety incidents and delays that can save 2-4 crores in a turnaround by averting delays arising out of rework, improved decision making based on real-time data, and quicker signoffs during start-ups. The benefits of applying Maximl’s built-in-India platform have been experienced by most of the refineries and process companies in India and SEA. It helps connect project managers and planners with the large deskless workforce. Maximl’s solution: – Enables real-time monitoring of projects with data coming directly from the field across multiple sites. It provides improved visualisation of project control metrics. – Establishes a single source of truth connecting all the workforce on a single platform to speed up the execution of the project and prevent any miscommunication. – Reduces paper movements and helps refineries go paperless using the no-code capabilities of the platform, rapidly digitising workflows like issue management, safety walks, etc. and, at the same time, automates various reports associated with the turnaround and saves time, thereby improving productivity. AIM: How do you see the landscape of refining industries evolve with AI in the future, and how is it helping the Indian economy? The operations and controls in the refining sector is a very mature and digitally-led space and is already using many AI applications on top of the online machine data to improve throughput, yields, predict breakdowns, etc. The domain of reliability, which includes inspection and maintenance of assets, is the one that is highly unorganised, especially the on-field processes beyond the generation of a Work Order from an ERP and upload of an inspection report to an APM/EAM system. We believe that another frontier of application of AI is going to be on the human processes, which is largely a tribal knowledge problem today. Simply put, the factories of the world and in India are run by 30-years of experienced technicians and their tacit knowledge. With the influx and the tilting of balance towards the millennial workforce, both the average tenures and tribal knowledge sharing methods are at a serious threat today. This is the exact reason why there is a lot of push to digitalise the workflows, automate them and eventually drive superior decisions using AI. AIM: You have expanded your services abroad; how do you customise your solutions to different countries? What space are you leveraging there? There are both operational and cultural differences when you sell and implement a solution in new geography. One inherently good trait with manufacturing is that the theoretical processes are very similar across geographies as they are largely driven by global OEMs and technology providers such as SAP, IBM and Oracle. A large part of variability comes from the human factors – manual process flows, contracting models and adoption of the tech. Our no-code capabilities have matured enough to handle the variability across sites, org structures, approval process and varied experiences that are required by the major departments of a factory – Maintenance, Quality, EHS and Operations. Our platform has been multi-lingual from day one and is currently live at 10+ sites in Spanish, Portuguese and French. AIM: You have just signed a contract with Indian Oil and raised investments in a Pre-Series A round; how do these shape your local and global expansion plans? Maximl is currently present at 50+ global sites with 16 enterprise customers across India, SEA, LATAM, and Europe. We have successfully expanded our footprints globally and across sectors such as chemicals, CPG, oil & gas, warehousing, natural gas, power and utilities, and industrial OEM. We’re further planning to go deeper in LATAM, Europe and SEA by leveraging our partner network while also working on sales and marketing strategies to have a strong direct presence in the US along with the Indian market. We plan to be present at 100+ global sites across 20+ countries by the end of the current fiscal year.
The platform is based on a combination of monoliths and microservices, connected using an event-driven model.
The platform is based on a combination of monoliths and microservices, connected using an event-driven model.
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["machine learning", "AWS", "AI", "R", "ML", "RAG", "microservices", "Aim", "analytics", "Azure"]
["AI", "machine learning", "ML", "analytics", "Aim", "RAG", "AWS", "Azure", "microservices", "R"]
Avi Gopani is a technology journalist that seeks to analyse industry trends and developments from an interdisciplinary perspective at Analytics India Magazine. Her articles chronicle cultural, political and social stories that are curated with a focus on the evolving technologies of artificial intelligence and data analytics.