Neysa, an AI Compute and AI Acceleration cloud provider, and Pipeshift, a managed inference platform for open-source AI models, today partnered to launch production-grade real-time inference infrastructure fully deployed within India.
Shifting away from a token-based pricing model, the offering provides lowers latency anywhere between 50 pre cent to 300 per cent, predictable economics, and in-country data control.
Flagging how much of India’s inference infrastructure sits outside India, despite the country emerging as one of the largest inference-heavy AI markets, the companies said many Indian enterprises are encountering challenges around unpredictable latency, escalating token costs, shared infrastructure bottlenecks, and overseas data routing.
“Scaling open-source models introduces a dual bottleneck: volatile token economics and high Time-to-First-Token (TTFT) driven by shared rate limits and cross-region routing. By integrating Pipeshift’s inference-engine optimizations directly onto Neysa’s single-tenant, optimized bare metal, we eliminate this friction entirely. The upshot for enterprises is a seamless, OpenAI-compatible drop-in replacement that guarantees cold-starts, predictable and highly optimized token latency, and absolute sovereign data control at scale,” said Karan Kirpalani, Chief Product Officer, Neysa.
The platform is immediately available for enterprises evaluating open-source AI deployments across customer support, voice AI, enterprise copilots, workflow automation, and regulated AI workloads. It eliminates shared rate limits, cold-start delays, and cross-region routing overheads and smoother transition between newer GPU generations and open-source model releases without rearchitecting applications.
Speaking to businessline, Kirplani said the companies map infrastructure and investments directly to verifiable demand.
“If you look at the economics of AI right now, the numbers validate why we’re building this platform. The TAM in terms of the global addressable market has already hit massive scale. 2025 valuations, estimated conservatively, were between $110 billion to $140 billion. That reflects a macroeconomic shift away from just one-off model training towards continuous, constant recurring real-time inference.”
Stating that the serviceable available market in India, is the primary geography, the AI infrastructure market is valued at about $50 billion odd, the inference component is estimated to be about 70-75 per cent, he said.
Published on May 27, 2026