Gathr is a 'data to outcome' platform leveraging cutting-edge technologies to enhance organizational efficiency with data-driven outcomes. The company has achieved significant success recently due to its unique offering. Rajeev Ranjan, Editor of Digital Terminal, interviewed Sameer Bhide, Director of Technology at Gathr Data Inc, to discuss their growth, market strategies, vision, and more.
𝐐.Rajeev: How has Gathr experienced growth in the Indian market in recent years?
A. Sameer: Gathr Data Inc has experienced more than 300% growth in the Indian market in recent years. Almost all global enterprises now have an IT hub in India. These IT hubs are increasingly autonomous in terms of acquiring solutions that can drive business outcomes across all global locations. This fits in very well with Gathr Data Inc’s business focus and hence, it’s in high demand in the Indian market. With waves of new startups in India, cloud and technology is at the forefront and that is also driving demand. Also, in a post pandemic world, where hybrid working models are popular in larger Indian cities, measuring and improving productivity is important for enterprises and this is also driving an uptake of Gathr Data Inc.
𝐐. Rajeev: In the current landscape, what are the two major challenges facing Gen AI processes?
A. Sameer: Availability & discovery of high-quality data & its subsequent processing is one of the biggest hurdles in successfully realizing GenAI use cases. The data landscape in organizations tends to be fragmented, especially when dealing with new kinds of data beyond the traditionally managed and curated structured datasets. Data and analytics teams have to go through the churn involved in data acquisition, maintaining lineage and mapping what datasets are AI ready. This requires significant time & staffing costs. Typically, enterprises almost always get exposed to this cost once a project has been greenlit post successful proof of value (PoV).
Protecting against IP leaks & governance on AI has been another major hurdle impacting the speed of delivery in GenAI initiatives. The ability to safeguard against abuse, un-intended access to data assets requires a mix of prompt engineering, application architecture, fine tuning and processes for data access.
𝐐. Rajeev: What key features or strategies differentiate Gathr in supporting Gen AI operational efficiency?
A. Sameer: Gathr is built ground up keeping efficiencies of cloud, processing scale, data engineering and analytics challenges in mind.
Gathr’s GenAI features dovetail into the platform’s data to outcomes journey very well. It means – the ease of use, visual canvas, zero code paradigm of Gathr’s extends to GenAI.
Gathr’s end to end, unified platform brings data engineering discipline to GenAI, enabling GenAI applications to be developed & managed with the same familiarity & robustness of a data pipeline.
Gathr’s users experience consistent interface right from data acquisition and data asset management to insights delivery & consumption when building GenAI applications.
GenAI integration in Gathr runs deep; it extends to business use cases like entity extraction, summarization as well as for internal platform features like code generation, asset discovery and assistance resulting in faster time to market and efficient increments with evolving business needs.
𝐐. Rajeev: Could you provide insights into Gathr's current sales model and its alignment with the company's overall business strategy?
A. Sameer: Gathr Data Inc is focused on direct sales to corporate and government clients who need to make better use of the data distributed in their various systems to help drive better outcomes. Many of our customers have made extensive investments in technology and have data in many systems that cannot be easily aggregated. Many have made investments in data warehouses but still lack the ability to seamlessly integrate new information or make use of the information that has been stored.
With Gathr, we work with customers to easily integrate and map data from their existing systems, and enrich this data through rules, machine learning, and GenAI capabilities. Our platform has a near zero learning curve and enables higher scalability. Sales teams work with customers to evaluate specific use cases and perform a proof of value to show how these data processes can be accelerated on Gathr. Moving forward, customers can choose from many different deployment models, from a completely SaaS-based solution to AWS and GCP-marketplace deployments or complete on-premises/private cloud options.
Gathr Data Inc’s strategy is to become long-term data partners with customers to help drive efficiency in data engineering and empower better decision-making with data driven outcomes. Commercial models follow a usage-based approach, allowing big and small customers to scale the products and their costs based on their requirements.
𝐐. Rajeev: Can you share a brief overview of Gathr's strategic plans for future growth and expansion?
A. Sameer: Gathr Data Inc is focused on becoming the leader in helping companies move and interpret data to directly impact business outcomes. Gathr’s no-code, web-based design and execution platform empowers companies to become self-sufficient in extracting and transforming data and using analytics web applications to help interpret and drive actions. Going forward, Gathr Data Inc is investing in GenAI and increasing the use of ML to help create applications in a more intuitive way, as well as providing more recommendations on how data can be analyzed.
These features are centered around the GathrIQ product, which combines many existing ML and AI capabilities already in the product with more innovative use of GenAI to make data ingestion, processing, and insights a breeze. As Gathr’s product and capabilities grow, the go to market will grow accordingly. Gathr Data Inc is focused on worldwide sales, targeting SMB to large enterprises, and increasingly working with system integrators, consulting partners and cloud companies to help support their offerings and projects.
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