Question 1

What does Navtechy build?

Accepted Answer

Navtechy builds custom AI systems and full-stack web applications for businesses worldwide. Core services: AI chatbots powered by GPT-4, Claude, and Gemini; retrieval-augmented generation (RAG) pipelines connecting LLMs to your business data; fine-tuned language models trained on proprietary datasets; SaaS platforms built with Next.js and Node.js; and workflow automation systems. We have shipped 50+ projects across SaaS, e-commerce, healthcare, education, and enterprise software — including three live SaaS products we built from scratch. Engagements run from focused AI chatbots in 4 weeks to enterprise LLM deployments over 5 months.

Question 2

How long does development take?

Accepted Answer

Development timelines depend on scope and complexity. AI chatbots and RAG systems typically take 4–8 weeks from scoping to production. Full SaaS platforms with integrated AI features take 12–20 weeks. Automation and workflow integrations take 2–4 weeks. All projects begin with a discovery and scoping phase (1 week), followed by architecture design (1 week), then agile development sprints of 2 weeks each with live previews and direct access to the engineering team. QA runs in parallel during the final sprint. Deployment to AWS, Vercel, or GCP is included, along with a post-launch support window. Timelines are agreed upfront — we do not move goalposts after the technical spec is signed off.

Question 3

Do you work with startups and small businesses?

Accepted Answer

Yes. We work with early-stage startups, growth-stage businesses, and enterprise clients. We have built SaaS products from a blank repo for pre-seed founders, added AI features to existing platforms for Series A companies, and delivered enterprise LLM systems for established organisations. For startups, we act as a full engineering team — handling architecture, development, and deployment so you can focus on the product. We are also comfortable inheriting partially-built codebases and working within tight timelines and budgets. Our engagement starts at the Scope tier, which puts professional AI engineering within reach for small businesses and early-stage teams.

Question 4

What AI technologies does Navtechy specialise in?

Accepted Answer

Large Language Models (LLMs), retrieval-augmented generation (RAG), custom AI chatbots, AI workflow automations, and model fine-tuning. We integrate with all leading AI providers — OpenAI (GPT-4, GPT-4o), Anthropic (Claude 3), Google (Gemini), and open-source models including LLaMA 3 and Mistral. For RAG pipelines, we use LangChain and LlamaIndex with vector databases such as Pinecone and pgvector. We are model-agnostic — we select the best AI architecture for your use case based on accuracy, latency, cost, and data privacy constraints.

Question 5

What is a RAG system?

Accepted Answer

A RAG (Retrieval-Augmented Generation) system is an AI architecture that combines a large language model with a retrieval layer connected to your own data — documents, databases, knowledge bases, or APIs. Unlike a base LLM that answers only from training data, a RAG system first searches your specific content, retrieves the most relevant passages, and passes them to the LLM to generate an accurate, grounded response. This prevents hallucination and keeps answers current without expensive model retraining. Common use cases: internal knowledge bases, customer support bots, document Q&A tools, and enterprise search. A RAG build typically takes 4–8 weeks.

Question 6

Which industries has Navtechy worked with?

Accepted Answer

SaaS, e-commerce, healthcare, education, hospitality, and enterprise software. In SaaS, we have built complete platforms from zero and added AI features to existing products. In e-commerce, we have built recommendation engines and AI support systems. In healthcare, we have delivered HIPAA-aware document processing. In education, AI tutoring and assessment systems. In hospitality, booking and operations automation. Our engineering expertise is industry-agnostic — we focus on understanding your business problem first and engineering the right technical solution second.

Question 7

What tech stack does Navtechy use?

Accepted Answer

Next.js and React for frontend, Node.js for backend APIs, and Python for AI and machine-learning workloads. TypeScript across most projects for type safety. PostgreSQL for relational data, MongoDB for document-based systems. We deploy to AWS, Vercel, and GCP depending on project requirements. For AI, we integrate OpenAI, Anthropic, and Google APIs, and use LangChain / LlamaIndex for RAG and agent pipelines. We are not dogmatic about stack — we recommend what is right for your project, factoring in your team, scaling needs, and existing infrastructure.

Question 8

Do you offer a free consultation before committing?

Accepted Answer

Yes. We offer a free 30-minute scoping call before any commitment. In this call, we assess your project requirements, ask questions about your existing infrastructure and data, suggest the right technical approach — RAG system, fine-tuned model, full-stack build, or a simpler API integration — and provide a timeline estimate. No sales pressure, no obligation. The call is designed to give you enough information to make a confident decision, regardless of whether you work with us.

Question 9

Can Navtechy take over a project that another team started?

Accepted Answer

Yes. We regularly perform code audits and take over partially-built projects. We start with a structured codebase assessment — reviewing architecture decisions, identifying technical debt, security issues, and performance bottlenecks, and documenting what exists before writing a single line of new code. We then produce a remediation and continuation plan for your sign-off. Common scenarios: a previous agency went dark mid-build, an in-house team ran out of capacity, or an MVP-stage product needs to scale. Transparent documentation is produced throughout so your team is never dependent on us.

Custom AI and full-stack systems, built to ship.

Shipped products. End to end.

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What we build.

Custom LLM development

RAG systems

AI chatbots

Workflow automation

We don’t build templates.
We don’t ship “good enough.”
We engineer systems that command authority.

Who we are.

Delivery-first. Deep expertise.

How we work.

Discovery & architecture

Prototyping & UX

Engineering sprints

Integration & QA

Launch

Handoff & support

Frequently asked.

Start with a scoping call.