Technical resources written by our founding engineers — reference architectures, decision frameworks, and templates drawn from our own builds and our founder's 20+ years of enterprise software experience.
We are a new company — these are reference designs and our own internal product, not client projects. They represent how we approach common engineering challenges and the technical depth we bring to every engagement.
Our reference design for a Prophet + XGBoost demand forecasting pipeline integrated with Shopify and 3PL APIs, with an LLM anomaly-narration layer for non-technical operators.
A strangler-fig migration from a monolithic EC2 deployment to EKS — with dual-write database migration, Datadog observability, and feature-flag traffic shifting.
How we approach building a complete test suite (unit, integration, e2e) from zero — using Playwright, Jest, GitHub Actions, and page-object model for long-term maintainability.
We built our own Friday One covering attendance, payroll (with full Indian statutory compliance), leave management, performance reviews, and biometric device integration.
We built our own GEO platform to track brand visibility across ChatGPT, Gemini, Perplexity, and all major AI answer engines — with citation monitoring, competitive benchmarking, and content signal tracking.
Our AI-powered audit platform runs SEO, performance, accessibility, security, GEO readiness, mobile, and revenue-leakage analysis from a single crawl — with branded PDF/HTML/CSV reports, scheduled audits, and white-label deliverables.
Free to download — we'll send the PDF directly to your email.
Before you spend a rupee on AI infrastructure, run through these 47 questions to assess your data readiness, team capability, and ROI potential.
A decision framework for evaluating custom development versus off-the-shelf software. Covers total cost of ownership, maintenance burden, vendor lock-in risk, and worked examples.
The exact checklist our team uses when auditing a startup's codebase during due diligence. Architecture, security, scalability, and team assessment.
A concise overview of our services, team structure, technology expertise, and engagement models — formatted for sharing with stakeholders.
Deep-dive technical papers written by our founding engineers, drawing on 20+ years of enterprise software experience.
Our founder's analysis of AI adoption patterns, tooling choices, ROI measurement, and team readiness gaps — drawn from direct experience implementing AI systems in enterprise environments.
A detailed comparison of both architectural patterns — operational cost, team velocity, incident rates, and when each genuinely serves a growing organisation better than the other.
A practitioner's guide to DPDP compliance for product teams — data localisation, consent flows, breach response, and audit trails.
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