Pyivot Solutions is a Data Analytics and Business Intelligence startup helping Manufacturing, Trading, Retail, Logistics, and E-commerce businesses transform data into actionable insights — and competitive advantage.
Pyivot Solutions was founded on a simple belief: every business deserves data-driven decision-making — not just the ones that can afford large enterprise BI teams.
We specialize in building affordable, scalable, production-ready analytics solutions for SMEs in manufacturing, trading, retail, and e-commerce — using world-class tools like Power BI, SQL Server, Python, and Azure.
Every engagement includes full documentation and team training, so you own the solution completely and can grow it independently.
Most projects deployed within 2–4 weeks. Agile sprints with weekly demos.
Enterprise-quality solutions at SME budgets. Transparent, no-surprise pricing.
We train your team, so you're not dependent on us forever. Self-sufficiency is the goal.
Post-launch support and flexible retainer packages for continued improvements.
Full-stack data solutions — from strategy and architecture to deployment and training.
Custom dashboards, reports, and KPI monitoring systems designed for your specific business operations and decision-makers.
Automated ETL pipelines, SQL databases, and data warehousing solutions that unify data from all your business systems.
Predictive models, demand forecasting, and advanced analytics that let you anticipate market changes before they happen.
Deep domain knowledge built through real project work — not just generic BI templates.
OEE, production, quality
Sales, margins, inventory
GMV, retention, LTV
SLA, route, vendor
Footfall, category, shrink
P&L, cash flow, risk
Real impact metrics from real client projects — anonymized to protect confidentiality.
A 3-plant manufacturing company was tracking OEE manually in Excel, with a 2-day reporting lag. We built a live Power BI system connected to their SCADA and ERP via automated SQL ETL.
An e-commerce brand was losing revenue to stockouts while carrying excess inventory in slow movers. We built a Python demand forecast model with Power BI integration to optimize replenishment.
A 100 Cr+ trading firm had 4 people manually compiling daily MIS reports for 8 business units. We automated the entire process and built a CFO-level financial dashboard with daily refresh.