QUANTIPHI
“ Enterprises have issued top-down mandates to find and deploy agentic AI solutions,” he says.
“ This isn’ t about individual use cases anymore,” he adds.“ It’ s about platform-level transformation.”
Kanishk says market research suggests the agentic AI opportunity could exceed US $ 200bn by 2029.
However, he argues that simply accessing AI models through Application Programming Interfaces proves insufficient for organisations seeking enterprise-scale deployment – as current adoption patterns reveal persistent challenges.
He says that industry data indicates that 70 % of enterprises require a full year to resolve return on investment questions related to agentic AI implementations, often stemming from dependency on external AI providers.“ When you don’ t own your stack, you’ re not just delaying value realisation – you’ re making sustainable returns nearly impossible,” Kanishk argues.
“ You’ re paying rent on someone else’ s innovation, while competitors build equity in their own capabilities.”
How Quantiphi’ s evolution mirrors industry platform consolidation Quantiphi’ s evolution further reflects broader industry patterns in the transition from custom AI solutions to platform ecosystems.
The company’ s early work centred on bespoke applications: predictive analytics for manufacturing clients, recommendation engines for retail
organisations and pioneering NLP implementations. Now with the development of baioniq alongside Qollective. CX, Quantiphi’ s first systematic approach to scalable AI capabilities, the company can combine conversational AI, document processing and workflow automation for deployment across multiple clients rather than requiring custom development for each implementation.
These LLM advances created what Kanishk describes as“ an inflection point” that accelerated baioniq’ s development, using accumulated
68 October 2025