Structured analytics for fixed income, treasury, and risk workflows—combining financial modelling, machine learning, and workflow automation.
About Quant Shastra
Quant Shastra is an institutional analytics platform built for fixed income, treasury, and valuation workflows. We combine financial modelling, machine learning, and workflow automation to support pricing, spread-over-G-Sec analysis, sector-wise yield interpretation, portfolio surveillance, and decision-ready reporting.
In markets where liquidity can be uneven and information is fragmented, Quant Shastra helps teams move beyond spreadsheet-heavy processes toward more scalable, explainable, and operationally reliable analytics.
Platform Capabilities
Each capability is a distinct analytical module—structured for enterprise workflows, designed for domain depth.
Structured workflows for G-Secs, SDLs, corporate bonds, CPs, CDs, and related derivatives, with cash-flow modelling, spread-over-G-Sec analysis, sector-wise yield analysis, relative value screens, curve construction, and market-implied pricing.
Machine learning models deployed for scenario analysis, anomaly detection, stress testing, liquidity signals, spread-widening alerts, downgrade watchlists, and portfolio surveillance across issuer, sector, rating, and tenor buckets.
AI-assisted portfolio analysis and suggestion workflows that convert holdings data into actionable insight across duration, modified duration, DV01, carry and roll-down, issuer concentration, sector allocation, curve positioning, and scenario impact.
RAG-based monitoring of market-moving developments, rating actions, issuer disclosures, and covenant events, combined with AI-assisted analysis of term sheets and financial documents covering call/put structures, reset clauses, covenants, and key economic terms.
Decision-ready dashboards, valuation notes, pricing-exception logs, sector and issuer heat maps, committee packs, and audit trails designed for teams operating within RBI, FIMMDA, AMFI, and SEBI-oriented valuation, disclosure, and control environments.
Stakeholder Value
Our Foundation
Founded by finance professionals with experience across leading global and Indian institutions. Our approach is shaped by institutional experience in valuation, yield-curve modelling, structured products, spread analysis, and analytics-led workflow design.
Core Analytical Pillars
Infrastructure
Cloud-native architecture built for secure data workflows, scalable analytics, model execution, and reporting.
Get Started
Quant Shastra helps institutional teams turn fragmented market, portfolio, and document inputs into structured, decision-ready analytics.