Our foundation
Born from domain frustration, built on engineering depth
Virinchi Software was founded in 2012 by engineers who had spent years watching technically capable firms ship software that failed in production — not because the code was wrong, but because the builders didn't understand the domain they were building for.
Payment processing teams that had never seen a clearing-house integration. HealthTech teams shipping clinical workflows without a single conversation with a clinician. Enterprise platforms designed by architects who had never operated one at scale.
The founding insight was simple: domain depth is not a nice-to-have. It is the engineering advantage. We built Virinchi around vertical expertise from the start — and that decision has shaped every hire, every service, and every project since.
Our mission
Make AI the default layer in every product we build — an architectural core that makes the product genuinely more valuable with every data point it processes.
12 years of evolution
How we got here — and stayed ahead
Founded on a simple insight
Virinchi Software was born from a frustration shared by its founders: software built by developers who didn't understand a domain almost always failed in production. The founding team — engineers from enterprise financial systems, payment processing, and logistics — built around domain depth from day one.
Mobile-first before it was obvious
As mobile usage overtook desktop, we built out dedicated iOS and Android practices. Native Swift and Kotlin expertise, offline-first architecture, biometric auth, and device-native AI features — capabilities most firms still treat as specialisations became our baseline.
Domain specialisation deepens
We made a deliberate choice: stop taking every project, and go deeper into FinTech, HealthTech, eCommerce, and Industrial Automation. This meant investing in compliance knowledge — HIPAA, PCI-DSS, KYC/AML, FDA SaMD — not just coding ability.
AI embedded, not bolted on
Machine learning moved from research experiments to production infrastructure. Our engineers shipped recommendation engines, fraud detection systems, demand forecasting models, and clinical NLP tools — all integrated directly into client platforms, not wrapped in separate AI dashboards.
Generative AI — ready before the hype
When LLMs went mainstream, our MLOps plumbing was already in place. We launched a dedicated Generative AI practice and shipped the industry's first RAG-based compliance document search engines and LLM-powered clinical coding assistants within months of GPT-4's release.
Software + marketing under one roof
We expanded beyond pure engineering to offer AI-powered digital marketing — SEO, GEO (Generative Engine Optimisation), AI Overview citations, and performance marketing. Today, we're an IT services company and marketing agency that builds custom software and uses AI to grow the businesses we serve.
How we build your product
Six disciplines. Built layer by layer.
Each layer activates in sequence — Discovery first, Scale last. AI and human expertise work together at every stage.
Who builds your product
Deep specialists, not generalists
Every discipline exists because a production challenge demanded it — not because of a job description.
Mobile Engineering
Native-first. AI-enabled.
Swift + SwiftUI for iOS, Kotlin + Jetpack Compose for Android, React Native for cross-platform — with on-device ML via Core ML and TFLite. Our mobile engineers have shipped apps used by millions across banking, health, and retail.
Backend & APIs
Distributed systems at production scale.
Python, Node.js, Go, and Java — event-driven microservices, REST and GraphQL APIs, real-time data pipelines. Designed for horizontal scale, async communication, and observability from the first commit.
AI & Machine Learning
Production AI — not proof-of-concept.
Custom LLM fine-tuning, RAG pipelines, multimodal AI, MLOps with drift detection, model serving and evaluation frameworks. We ship AI systems that remain accurate in production over time.
Compliance Engineering
Regulation as architecture, not an audit.
HIPAA, HITECH, GDPR, PCI-DSS, SOX, KYC/AML, FDA SaMD, ISO 27001 — embedded on every FinTech and HealthTech project, not brought in at the end. Compliance-first architecture costs less to maintain and far less to audit.
Modern Web & Frontend
Pixel-perfect. Lighthouse 95+.
Next.js, React, TypeScript, Tailwind — built for performance (SSR, SSG, streaming), accessibility, and measurable conversion. Atomic design systems, Figma-to-production with zero ambiguity.
Cloud & DevOps
Infrastructure that scales quietly.
AWS, GCP, Azure — multi-cloud and cloud-native. Kubernetes orchestration, Terraform IaC, zero-downtime CI/CD pipelines, OpenTelemetry observability. Incidents detected in seconds, not discovered by users.
SEO & Digital Marketing
Rank on Google. Get cited by AI.
Technical SEO, GEO (Generative Engine Optimisation), AI Overview citations, LLM SEO, content strategy, and paid search — we run the full marketing stack. Your brand visible on traditional search and the new AI-powered search layer.
AI adoption timeline
We adopted AI early — and stayed disciplined
Our first production ML model shipped in 2018 — a fraud scoring system, serving <80ms predictions in real time. When GPT-4 arrived in 2023 we shipped production RAG systems within weeks — not because we moved fast, but because our MLOps infrastructure was already in place.
How we think
Principles that govern every engagement
Engineered for production
Real data volumes, real user loads, real failure modes. Every architectural decision is made by engineers who have operated systems at scale.
Compliance-first by design
Regulatory requirements embedded in architecture from sprint one. HIPAA, GDPR, PCI-DSS, KYC/AML — not bolted on before launch, not discovered in audits.
AI adoption ahead of the market
First production ML deployment in 2018. When generative AI matured in 2022, our MLOps infrastructure was already in place. We track fundamentals, not trends.
Domain expertise over generalism
Deep knowledge of FinTech, HealthTech, eCommerce, and Industrial means we understand your constraints before you have to explain them.
Outcomes over delivery velocity
Milestones are tied to working software that creates measurable value. Sprint velocity and lines of code are internal metrics.
Full ownership, zero lock-in
Every system, model weight, pipeline, and documentation artefact is yours from day one. No vendor dependency. No licensing. No platform fee.
The team behind the work
120+ engineers who chose depth over breadth
Our team is structured in vertical pods — not a pool of generalists assigned to whatever project has capacity. A FinTech AI engineer on your project has shipped production fraud detection before. A HealthTech backend engineer understands HL7 FHIR before you explain what it is.
Senior engineers — not just project managers — are client-facing on every engagement. You speak directly to the people writing the code.
