Founder & CTO, Eunix Tech
Rajesh leads Eunix Tech's engineering practice, building production-grade applications, AI systems, and platform modernizations for global clients. He writes about the practical side of shipping software: what works in production, what fails, and why.
Is your Lovable app production-ready? A 2026 guide to Supabase RLS, secrets, hosting options, and when to harden vs. migrate a Lovable MVP to custom code.
Learn how API monitoring helps businesses detect failures, track performance, reduce downtime, and improve API reliability with proactive monitoring.
Learn how custom API integration services connect AI with CRM, ERP, cloud, and business applications to automate workflows and improve operations.
Connecting two systems is easy. Keeping them connected through retries, rate limits, duplicate payments and API changes is the real work. Here is how reliable API integration services are built.
Most legacy systems do not need a ground-up rewrite. Here is how to modernize them in phases: assess first, wrap with APIs, replace components gradually, and know when a rewrite is the right call.
What AI software development services include, which types of AI software you can build, and a practical framework for taking an idea to production, from testing and security to cost drivers and choosing a partner.
A practical guide to connecting AI with your CRM, GPT-style LLM APIs and SQL Server, including safe natural-language queries, AI-ready data and how to scope the work.
AI data analytics helps teams spot patterns, ask questions in plain language and automate reporting. Here is how it works, where it fails, and how to measure the return.
Predictive analytics with AI helps teams forecast outages, project risk, claims and demand before they happen. Here is how it works, where it pays off, and when a simpler method is the better choice.
A demo chatbot answers questions on a good day. A production-ready AI assistant stays grounded, secure and reliable on every other day. Here is what separates the two.
How to add an AI chatbot to software you already run: auth, backend proxying, data access, rate limits, fallbacks, cost control and security, without rebuilding the app.
How AI in software development changes every phase of the lifecycle, from planning to maintenance, and what it means for team shape, risk, and the AI features you ship.
A practical guide to AI code generation for business engineering teams: which tools to use, how to set policy, review and security rules, protect IP, and measure real ROI.
Eunix Tech has launched Praxismith, an interactive platform that teaches teams to work with AI and AI agents with production-grade discipline.
Learn how AI data engineering works, how to build reliable AI-ready data pipelines, the role of AI tools, generative AI, agentic AI, governance, and best practices.
Learn how LLM application development works, including LangChain, RAG, APIs, architecture, security, deployment, tools, and best practices for enterprise AI applications.
What is machine learning as a service? How MLaaS works, its benefits, cloud options, use cases, and how to choose a provider or when to build custom instead.
Learn how AI model deployment works, including infrastructure, deployment steps, production challenges, tools, security, monitoring, scaling, and costs.
Learn how AI model development works, including data preparation, model training, fine-tuning, testing, deployment, security, costs, and business use cases.
Learn how machine learning development works, including ML models, use cases, technology stack, development process, costs, challenges, and deployment.
Learn what RAG development is, how Retrieval-Augmented Generation works, its architecture, technology stack, costs, use cases, and development process.
Learn about AI chatbot development costs, features, technology stacks, development steps, integrations, and how to choose the right AI chatbot development company.
Learn how generative AI development works, including use cases, development stages, technologies, costs, deployment, security, and choosing a GenAI partner.
Explore AI consulting services, generative AI strategy, use cases, costs, and how to choose the right AI consulting partner for your business.
Learn how AI agent development works, including architecture, use cases, security, costs, testing, and how businesses can build reliable AI agents.
Can you add AI to existing business software without replacing it? Yes. See how AI integrates with CRM, ERP, databases and support tools, and what it takes.
Understand AI software development costs in 2026 - the factors that drive budget, cost by development stage, AI model and infrastructure expenses, maintenance, and how to estimate your own project.
What is AI automation development? See how businesses automate complex workflows with AI agents, which workflows to start with, and when not to use AI at all.
Learn how AI application development works, from prototype to production. Explore development steps, technologies, costs, testing, security, scalability, and AI services.
Learn how LLM evaluation measures AI accuracy, reliability, and performance. Explore evaluation metrics, testing frameworks, benchmarking, observability, and tools.
Learn how LLM architecture works and how to design reliable AI applications for production. Explore components, architecture patterns, deployment, security, and scaling.
Learn the complete AI product development process, idea validation, fairness in AI, generative AI, product strategy, and best practices for successful AI products.
Explore MVP development services for startups, from product strategy and UX design to development, testing, launch, and post-launch iteration.
What do product engineering services include? Discovery, design, build, QA, deployment and ongoing support. See the process, benefits, and how to choose a partner.
How much does an MVP cost? There is no flat price, but you can budget with confidence. See what drives MVP cost, how it splits by phase, and how to reduce it.
Learn everything about custom AI software development: benefits, development process, costs, use cases, and how to choose the right AI development company.
Is your AI MVP hitting scalability or performance issues? Learn why AI MVPs fail, what to audit before rebuilding, and how to avoid costly mistakes.
AI takeoffs can cut hours of counting down to minutes. They can also miss the one thing that loses you the bid. Here is an honest map of where AI takeoff tools save real time and where a human estimator still has to look.
AI can read a construction invoice in seconds. Trusting it with your money is a different problem. Here is what AI invoice processing really takes in production: coding, matching, exceptions, and a clean path into Procore and QuickBooks.
A construction company ran its back office on PDFs, spreadsheets, and phone calls. Estimates took days. We built AI agents for invoices, estimates, and takeoffs that run in production every day. Here is how.
AI estimating tools demo beautifully and claim 97% accuracy. Then they hit your real drawings and break. Here is why AI estimating fails in production, and the checklist to run before you trust one with a bid.
Should your construction company buy an AI estimating or invoice tool, or build a custom system? A practical, vendor-neutral guide to making the right call, and avoiding the trap of stitching five subscriptions together.
A B2B company spent $100,000 on an AI automation project that never worked. We rescued it, fixed it, and delivered 3x ROI in 60 days. Here is exactly how we did it.
Your AI project failed. Should you fix it in-house or bring in specialists? Here is how to make the right decision, and when calling an expert AI automation consultant is the smart move.
You think your failed AI project was expensive? The real cost is the inefficient workflows you are still running every single day. Here is how to calculate the hidden tax you are paying.
Your automation project failed. Now what? Here is a proven 5-step process to rescue it, rebuild it right, and deliver the ROI you were promised.
Your AI project failed. You spent months and thousands of dollars, but it never delivered the ROI you were promised. Here are the 5 real reasons why, and what you can do about it.
Stop building toy projects. Here are 5 real-world AI automation projects that will make your portfolio stand out to recruiters and land you your first automation engineering role.
How AI automation and AI agents help SMEs in 2026. Learn how to automate operations, lower costs, and compete with the efficiency of large companies.
The top AI automations for founders in 2026. Save 20+ hours per month, reduce errors, and work more efficiently. Practical examples, real ROI data, and step-by-step workflows.
A 2026 comparison of AI app builders - Lovable, Bolt, v0, Replit, Base44, Bubble and Google AI Studio - with stack, code ownership and pricing models.
Should you build your next AI application in Replit or stick with local development? Here's our comprehensive analysis.
Fix Claude tool use bugs in production: bad arguments, missed tool calls, tool_use_id errors, loops, 429 and 529 retries, logging and evals.
A practical 2026 guide for CTOs: what Vercel v0 generates, the gaps before launch, a readiness checklist, and a phased plan to take a v0 app to production.
Copilot Business and Enterprise security in 2026: data retention, content exclusion, public code filter, agent risks, and the GitHub settings that reduce them.
Struggling with Replit AI errors? Our comprehensive guide covers the most common issues and their proven solutions.
We tested the top 3 AI coding assistants with real Python projects. Here's which one actually makes you more productive.
Your B.Tech curriculum is 90% theory. But recruiters want 100% practical skills. Here's how to fill the gap and get hired.
Legacy post from an earlier phase of the company
We saw a gap between B.Tech/MCA degrees and the real-world skills needed in AI. Here's why we're launching a project-first AI automation internship in Sahibzada Ajit Singh Nagar ( Mohali ).
Legacy post from an earlier phase of the company
