If vLLM already solved LLM serving, why did SGLang appear?
Background
TIFIN scales AI-powered wealth management across India’s largest financial institutions
TIFIN is a global fintech platform that builds AI-powered products for the wealth and asset management industry. In India, TIFIN serves the country’s largest mutual funds and wealth management firms.
TIFIN’s platform identifies growth vectors for financial advisors and delivers hyper-personalized investment journeys to individual investors. Every recommendation depends on models that analyze investor behavior, match portfolios to life goals, and surface the next best action for an advisor in real time.
Running these models in India introduces two pressures at once.
- The first is data sovereignty. Investor data, portfolio holdings, and advisor interactions must stay within Indian borders under SEBI, RBI, and DPDP Act regulations. Moving this workload to a US-incorporated general-purpose cloud creates jurisdictional exposure that Tier-1 Indian financial clients cannot accept.
- The second is unit economics. TIFIN’s commercial model depends on running AI at scale across millions of investor interactions. Cost structures that inflate with volume would have made the business model unworkable.
TIFIN needed AI infrastructure that could deliver enterprise-grade reliability and cost efficiency at the same time.
“We faced a strategic paradox: scaling our AI required enterprise grade resilience, yet global consumption models were commercially inefficient. We needed a partner to bridge this gap, delivering enterprise-grade stability without compromising our unit economics.”
– Kiran Nambiar, Chief Product Officer, TIFIN India & CEO, MyFi
The Opportunity
Moving financial AI workloads into sustainable production
TIFIN had already proven the value of AI for wealth outcomes through early deployments. The question was no longer whether AI could drive better investment decisions. The question was whether the underlying infrastructure could sustain production workloads for regulated Tier-1 financial clients without breaking on cost, latency, or compliance.
To scale responsibly, TIFIN needed infrastructure that could deliver:
- Predictable unit economics: Global general-purpose cloud consumption models were incompatible with TIFIN’s objective of efficient, sustainable growth. As inference and training volumes scaled, standard cloud pricing would have diluted the ROI of every new enterprise deployment.
- Enterprise-grade reliability: TIFIN’s incumbent local neocloud provider offered better unit economics than a general-purpose cloud, but could not deliver the resilience needed for business-critical training workloads. Chronic outages and latency spikes were interrupting production runs and eroding trust with financial clients.
- Sovereign data handling: Investor data had to remain within Indian borders, managed under Indian law, with no exposure to foreign data requests. This was a regulatory requirement.
- Deep AI infrastructure expertise: The local provider’s lack of AI-specific engineering depth was forcing TIFIN’s own team to divert focus from model innovation to infrastructure troubleshooting.
The Solution
Building a dedicated AI platform for production financial workloads
TIFIN moved its production AI workloads onto Neysa Velocis, consolidating training, experimentation, and inference onto a single AI-native platform.
Neysa Velocis delivered the stability, tooling, and security posture TIFIN expected from a Tier-1 cloud, with a cost structure aligned to TIFIN’s high-volume commercial model.
The core components of the deployment:
Speed and Simplicity
Spin up GPU-powered workloads in minutes. Reduce time-to-result with low-latency access and optimized pipelines that simplify everything from provisioning to inference. No multi-dashboard sprawl, no vendor lock-in.
Security and Control
Enterprise-grade, multi-layered security designed for regulated environments. Role-based access, policy enforcement, real-time audit trails, and zero-trust architecture, all built in.
Scalability
From 1 to 1,000+ GPUs, scale as your models grow. Neysa Velocis is architected to support elastic scaling, hybrid burst, and workload-aware optimization.
Cost-Effectiveness
Stop burning cycles on idle infra. Transparent billing, spot-aware scheduling, and multi-tiered GPU pricing deliver superior tokens-per-dollar efficiency.
The Neysa Partnership
Engineering a production AI stack for regulated financial workloads
The partnership focused on giving TIFIN the reliability, visibility, and control required to serve the most demanding customers in Indian financial services. See how Jocata brings the same production AI stack to credit, fraud, and compliance decisions.
- Hyperscaler-grade stability: Velocis delivered instant, reliable GPU provisioning backed by 99.95% system uptime, replacing the chronic outages and intermittent drops TIFIN had experienced on the previous neocloud provider. Training workloads now run without interruption.
- Frictionless MLOps workflows: With on-demand Jupyter notebooks and a unified control plane, TIFIN’s R&D teams stopped managing compute and started focusing entirely on model innovation.
- Streamlined path to production: Integrated inference endpoints replaced the manual handoffs that had previously slowed deployment, accelerating time-to-market from experimentation to live commercial rollout.
- Sovereign-by-design data handling: All compute, training data, and model weights stay within Indian borders under Indian law, giving TIFIN a clean compliance posture for Tier-1 mutual fund and wealth management clients.
The Impact
Sustainable AI economics and production-grade resilience for India’s financial leaders
The migration to Neysa Velocis transformed TIFIN’s infrastructure from an operational constraint into a commercial advantage.
65% reduction in GPU cloud spend compared to hyperscalers.
By aligning infrastructure costs with value generation, TIFIN achieved sustainable unit economics at scale.
99.95% system uptime.
The chronic outages and latency spikes from the previous infrastructure provider gave way to consistent, enterprise-grade reliability.
Significantly faster path to production.
Integrated MLOps workflows and inference endpoints compressed the time from model experimentation to live commercial deployment.
Sovereign compliance for regulated financial clients.
All investor data, model weights, and compute remain within India, meeting SEBI, RBI, and DPDP Act requirements by architecture rather than by configuration.
“Neysa has been a force multiplier. Velocis provides the mission-critical stability and instant scalability of a global hyperscale AI cloud, but with an efficiency that transforms our GPU infrastructure from a cost center into a distinct competitive advantage.”
– Uttung Malkan, Head of Enterprise Business, TIFIN India
Take the next step
Ready to move your enterprise AI use cases to production? Contact our team today to request a technical demonstration and explore our managed inference solutions.
