KPMG India aqui-hires AI-led startup Recommender Labs
KPMG India has announced the aqui-hire of Mumbai-based AI-led decision-science services company Recommender Labs. With this, KPMG is poised to build its own Centre of Excellence (CoE) specialising in decision-science and AI-driven solutions. It will build unique assets, enable quick go-to-market, and build the ability to respond with AI-led offerings, by combining its capabilities with that of Recommender Labs.
Following the acqui-hire, Sanjaya Sharma, Founder and CEO of Recommender Labs, will join KPMG as a Senior Advisor.
Akilesh Tuteja, Partner and Head, Risk Consulting, KPMG in India, said in a press release:
“Recommender Labs is known for its AI-led decision science services for clients across a range of industries and client requirements, and has proven case studies across domains such as customer experience technology, ecommerce, fintech, and edtech. The acqui-hire will help us unlock the value of AI for our spectrum of clients and their varied business needs that we address on a daily basis. We also aim to build KPMG’s Centre of Excellence in AI-led decision making to develop solutions for our customers.”
Founded in 2016, Recommender Labs uses AI capabilities to support users during decision-making processes by generating recommendations. The company also offers custom implementation of machine learning (ML) applications and ready frameworks that are customised for each of their clients.
Sanjaya, who will now be building IPs and advanced analytics platforms, said:
“KPMG’s acquisition of RLPL (Recommender Labs Private Limited) is aptly timed as AI has started advancing positive push from the government to utilise technological advancements to reduce financial losses and increase output efficiency. The existing and in-pipeline AI-based products and services will enable KPMG to take its technology offerings to the next level.”
Recommender Labs’ product offerings include:
- Universal Recommender Engine, that helps identify and recommend best-fit products to customers in a retail scenario.
- Chatbot Authoring Framework, a natural language processing chatbot offering decision-tree based conversations and frequenty-asked-questions bank.
- Credit Risk Engine, helping identify potential defaulters from customers that have applied for lending products specifically catering to SMEs.
- Recruitment Applications, helping augmented profiling through interactive mechanisms and offers insights on best-fit candidates.
- Gamification Template, which offers mechanisms and engaging UX elements to capture and engage customers.