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AI Development Services

Custom AI solutions built for your business

We build production-ready AI systems — LLM integrations, intelligent chatbots, computer vision, predictive analytics, and automation pipelines — tailored to your specific industry and workflows.

No lock-in to any single AI provider
Production-ready, not prototypes
Tamil Nadu team, serving all India
AI Processing Pipeline
📄
Input Data
🧠
AI Model
Output
📊
Analytics
🔄
RAG Pipeline
🔔
Actions
model: claude-sonnet
query: "Analyse Q3 sales trend"
context: business_data.json
response: Q3 revenue up 18.4% driven by Steel Rods category...
30+
AI projects delivered
80%
Avg. manual work eliminated
95%
Accuracy on custom models
3 wks
Average from brief to first demo
What We Build

Our AI development services

Every AI solution is built for your specific context — your data, your industry, your workflows — not a generic off-the-shelf integration.

🤖

LLM Integration & Custom AI Assistants

Integrate OpenAI, Claude, Gemini, or open-source models into your product. We build context-aware assistants trained on your business data, documents, and workflows.

Most Popular
💬

AI Chatbot Development

Intelligent chatbots for customer support, lead qualification, internal helpdesks, and onboarding — deployable on WhatsApp, web, or your mobile app.

High Demand
👁️

Computer Vision Systems

Object detection, quality inspection, face recognition, and document scanning using state-of-the-art vision models — deployable on edge devices or cloud.

Manufacturing
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Predictive Analytics & Forecasting

Demand forecasting, churn prediction, sales forecasting, and anomaly detection models trained on your historical data and deployed into your dashboards.

Data Science
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Document Processing & NLP

Extract structured data from invoices, contracts, forms, and reports. Auto-classify documents, summarise long texts, and route information to the right systems.

Automation
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AI Automation Pipelines

End-to-end automation workflows that combine AI decision-making with business logic — from data ingestion to action execution, fully unattended.

Enterprise
Our Approach

How we build AI that actually works in production

01

Discovery & Data Audit

We map your data sources, understand the problem you're solving, and evaluate what AI approach is actually right — not just what's fashionable.

02

Model Selection & Architecture

We choose the right model — LLM, custom-trained, or hybrid — based on your accuracy needs, latency requirements, and budget.

03

Prototype → Production

We build a working prototype in week 1, validate it with real data, then harden it for production — error handling, monitoring, fallbacks.

04

Integration & Deployment

We integrate the AI into your existing systems — CRM, ERP, website, app — and deploy with CI/CD pipelines and uptime monitoring.

05

Monitoring & Improvement

AI needs ongoing care. We set up logging, performance dashboards, and feedback loops so the model improves over time.

Phase 1 — Discovery
DATA SOURCES IDENTIFIED
✓ CRM — 24,000 customer records
✓ ERP — 3 years transaction history
✓ Documents — 1,200 PDFs / invoices
✓ Real-time API — production sensors
RECOMMENDED APPROACH
RAG pipeline + Claude Sonnet
Estimated accuracy: 94%+
Latency target: <2 seconds
Cost estimate: ₹12/1000 queries
Real-World Applications

AI use cases we've built across India

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Visual Quality Inspection

Camera-based AI that inspects products on the assembly line at 200 units/minute with 99.4% defect detection accuracy — replacing 8 manual inspectors.

Manufacturing
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AI Business Analytics (Jay AI)

Natural language queries on business data: "Which customers haven't paid in 60 days?" and "What's my best-margin product?" — answered instantly.

All Industries

AI Review Reply Generator

Reads Google and Facebook reviews and drafts personalised, on-brand replies in seconds — reducing response time from hours to under 60 seconds.

Hospitality · Retail
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Contract & Document AI

Extracts key clauses, obligations, and risk terms from legal documents — reducing contract review time from 4 hours to 8 minutes per document.

Legal · Finance
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Patient Triage Assistant

AI pre-screens patient symptoms and medical history before doctor consultation — reducing consultation time and improving diagnostic accuracy.

Healthcare
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Inventory Demand Forecasting

Analyses sales patterns, seasonality, and supply chain data to recommend optimal stock levels — reducing stockouts by 60% and dead stock by 40%.

Retail · Manufacturing
Technology

The AI stack we work with

We're model-agnostic — we choose the best tool for your specific requirements, not the one we're paid to promote.

LLM Providers

Anthropic Claude
OpenAI GPT-4o
Google Gemini
Meta LLaMA 3
Mistral AI

Frameworks & Tools

LangChain
LlamaIndex
Python / FastAPI
Pinecone / Chroma
TensorFlow / PyTorch
OpenCV
FAQ

Common questions about AI development

Not necessarily. Many powerful AI applications use pre-trained LLMs (like Claude or GPT) that require very little of your own data — just a well-designed prompt and context. For custom-trained models (e.g. computer vision or fine-tuned LLMs), we'll advise on the minimum viable dataset during discovery. We've built effective solutions with as few as 500 labelled examples.

It depends heavily on the type of AI and complexity. A simple AI chatbot integration starts around ₹25,000. A custom RAG-based business assistant typically costs ₹75,000–₹2,00,000. A full computer vision system or custom-trained model is ₹2,00,000–₹10,00,000+. We'll give you a precise quote after a free discovery call.

We assess this per project based on your requirements for accuracy, speed, cost, data privacy, and language support. For most Indian business applications, Claude and GPT-4o deliver the best results. For on-premise deployments with strict data privacy, we use open-source models like LLaMA or Mistral. We'll recommend the right fit — not the one we're biased toward.

No. When using APIs from Anthropic, OpenAI, or Google with enterprise agreements, your data is not used for model training. We ensure all API calls are made through enterprise/API tiers with data processing agreements. For sensitive data, we can deploy open-source models entirely on your own infrastructure with no third-party data exposure.

A simple AI chatbot or integration can be deployed in 2–3 weeks. A custom business intelligence assistant typically takes 4–8 weeks. Computer vision systems and full AI automation pipelines take 8–16 weeks. We always deliver a working prototype within the first week so you can see results early.

Related services

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