How long does it take to build a custom AI application in India?

A typical custom AI application takes 8–16 weeks from discovery to production deployment. A focused proof-of-concept or MVP can be delivered in 4–6 weeks. AVIX Labs follows a phased approach: 2-week discovery, 4–8 weeks build, 2–4 weeks testing and deployment.

What is the difference between RAG and fine-tuning for enterprise AI?

RAG connects a language model to your organisation's data in real time—ideal when your information changes frequently or is proprietary. Fine-tuning trains the model on your data to adjust its behaviour—better for specialised tasks with stable datasets. For most enterprise use cases, RAG is faster, cheaper, and more maintainable.

How much does custom AI application development cost in India?

Custom AI application development in India typically ranges from ₹5 lakhs for a focused proof-of-concept to ₹25–50 lakhs for a full-scale production system. AVIX Labs provides fixed-scope engagements with transparent pricing after a 30-minute discovery call.

Do you build AI applications on AWS Bedrock or Azure OpenAI?

Yes. AVIX Labs builds production AI systems on AWS Bedrock, Azure OpenAI, Google Vertex AI, and open-source models including Llama and Mistral. We select the model and infrastructure based on your requirements. All code and infrastructure is fully owned by you.

What industries does AVIX Labs build AI applications for?

AVIX Labs builds AI applications for healthcare and life sciences, financial services and fintech, legal and professional services, manufacturing and supply chain, and enterprise SaaS companies.

Can you integrate AI into our existing systems?

Yes. We integrate AI capabilities into existing applications, APIs, and workflows without requiring a full rebuild. This includes connecting to your databases, internal tools, and third-party platforms.

Do you build custom AI solutions or use pre-built models?

We do both. We use leading models like OpenAI, Claude, and open-source models, and customize them with your data, workflows, and business logic to build reliable, production-grade systems.

How do you ensure AI applications work reliably in production?

We focus on production readiness from day one — including architecture design, prompt and model optimization, evaluation pipelines, monitoring, and fallback mechanisms to ensure consistent and accurate performance.

Can you build AI applications using our internal data?

Yes. We design secure pipelines to use your internal data such as documents, knowledge bases, and structured data, enabling accurate and context-aware AI responses through techniques like RAG.

How long does it take to build an AI application?

Timelines depend on complexity. Simple AI features can take a few weeks, while full-scale AI systems with workflows, integrations, and production deployment typically take 6–12 weeks.

Do you support deployment and scaling of AI applications?

Yes. We deploy AI applications on scalable cloud infrastructure with CI/CD, monitoring, and performance optimization to ensure they handle real-world usage and scale as your business grows.

What industries can benefit from AI application development?

AI applications can be applied across industries including finance, healthcare, SaaS, and enterprise operations — especially where automation, knowledge access, and decision support are critical.

AI-Powered Applications Built for Production

We design and build intelligent web applications and enterprise-grade platforms using modern architecture and AI. From knowledge bases to autonomous workflows — engineered to run at scale from day one.

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The Challenge

AI has massive potential. Execution is the hard part.

Most companies know AI can transform their operations. But turning that potential into production systems that actually work is where most initiatives stall.

Long timelines with no production output — months of consulting before any working system

Custom ML models that are expensive to build, slow to train, and rarely necessary for your use case

Proof-of-concepts that never survive contact with real data, real users, or real infrastructure

AI solutions that exist in isolation — disconnected from the workflows and systems your teams actually use

We take a different approach — production-first, fixed-scope, and built to ship.

Key Capabilities

What we build

Knowledge Bases with Semantic Search (RAG)

Retrieval-Augmented Generation (RAG) systems give AI perfect memory of your business knowledge. We ingest your documents, policies, manuals, and data into a searchable knowledge base — with source citations, no hallucinations.

Internal knowledge base Q&A
Product documentation search
Policy and compliance querying
Legal and regulatory research
Medical literature search

Intelligent Assistants and Chatbots

AI conversational interfaces connected to your real systems and data. These go beyond FAQ bots — they retrieve live information, take actions, and escalate intelligently to humans.

Customer support automation
Employee help desk
Sales assistant
Onboarding guide
IT support bot

Document Intelligence and Extraction

AI that reads, understands, and extracts structured data from unstructured documents — invoices, contracts, forms, reports, emails. Handles scanned PDFs, mixed formats, and complex layouts.

Invoice and receipt processing
Contract clause extraction
Form digitisation and validation
Report summarisation
Email triage and routing

AI Workflows and Agents

Multi-step AI systems that reason, make decisions, use tools, and complete complex tasks autonomously — with human-in-the-loop checkpoints where needed.

Lead qualification and enrichment
Research and analysis automation
Multi-system data orchestration
Compliance monitoring
Automated reporting pipelines

Our Process

How we build AI applications

Discovery & Scoping

Deep dive into your use case, data sources, integration requirements, and success criteria. We assess feasibility, recommend architecture, and define the scope with a clear written proposal.

Architecture & Design

System architecture design: data ingestion pipeline, AI model selection, retrieval strategy, API design, integration mapping, security and access controls.

Development

Agile sprints with weekly demos. Core AI functionality first, then integrations and features. Continuous testing including accuracy and edge-case validation.

Testing & Validation

End-to-end accuracy testing with real data, load and performance testing, security review, user acceptance testing.

Deployment

Production deployment on AWS, CI/CD pipeline, monitoring dashboards, documentation, team training, knowledge transfer.

Foundation Models

Models we build on

Anthropic Claude (Sonnet 4, Opus)

Complex reasoning, document analysis, long-context tasks, safety-critical applications

OpenAI GPT-4o / GPT-4 Turbo

General-purpose AI, vision, function calling, code generation

AWS Bedrock

Enterprise deployment, regional data residency, AWS integration, managed inference

Google Gemini Pro

Multi-modal applications, Google Workspace integration, long-context retrieval

Meta Llama 3

Open-source deployment, on-premise or VPC requirements

Technology Stack

Built with enterprise-grade tools

AI / LLM

OpenAI, Anthropic, AWS Bedrock, LangChain

Vector Databases

Pinecone, Weaviate, Qdrant, pgvector

Backend

Python, Node.js, FastAPI, AWS Lambda

Frontend

React, Next.js, TypeScript, Tailwind CSS

Storage

AWS S3, PostgreSQL, MongoDB, Redis

Monitoring

Datadog, AWS CloudWatch, LangSmith

Every Project

What's included

Complete source code (you own 100%)
Production AWS deployment
CI/CD pipeline
Monitoring and alerting dashboards
Security and access controls (RBAC)
Complete technical documentation
30-day post-launch support
Knowledge transfer sessions

FAQ

FAQs – AI Application Development

Common questions about AI application development

We build production-ready AI applications including knowledge bases with semantic search (RAG), AI assistants and chatbots, document intelligence systems, and AI-powered workflows or agents tailored to business operations.

Explore More

Related services & resources

Intelligent document processing

Automate invoices, contracts & document workflows with AI

AWS cloud deployment

Production-grade AWS infrastructure for AI workloads

How we build AI systems

Our discovery-first delivery process explained

Healthcare AI applications

HIPAA-compliant AI for clinical and administrative workflows

Fintech AI applications

Fraud detection, risk scoring & banking automation

View case studies

Real AI systems we've built and deployed in production

Speak with an expert

Connect with an AVIX product expert to learn more about our AI application offerings.

Contact Sales

Or email: [email protected]