Service 05 — AI Integration

AI that works inside your actual business — not a demo you show investors.

AI जो आपके असली बिज़नेस में काम करे — सिर्फ दिखावे के लिए नहीं।

మీ నిజమైన వ్యాపారంలో పని చేసే AI — ప్రదర్శన కోసం కాదు.

Most businesses are either completely ignoring AI or chasing it for the wrong reasons. The practical middle ground is where the value is — AI that handles specific, repetitive, high-volume tasks that currently cost your team time and attention every single day.

What AI is not (for most businesses)

Skip the hype. Most AI buzzwords don't apply to your operation.

  • You do not need a "generative AI strategy" — you need specific problems solved
  • A chatbot that hallucinates wrong prices or policies is worse than no chatbot
  • Sending sensitive customer or financial data to cloud AI APIs is a real risk
  • Buying an AI SaaS subscription for a feature you use 2% of is not ROI
  • AI cannot replace judgement, relationships, or hands-on service delivery
Where AI genuinely earns its place

High-volume, repetitive, information-heavy tasks.

  • Answering the same 30 customer questions your team fields every day
  • Reading, extracting, and filing data from invoices and documents
  • Generating first drafts of proposals, emails, and reports from structured data
  • Searching across large internal knowledge bases instantly
  • Flagging anomalies in data that humans would miss in high-volume operations
  • Qualifying and routing inbound leads before a human gets involved
AI solutions we build

Six practical AI integrations we deliver for Indian businesses.

Customer-facing

Website & WhatsApp chatbots

AI-powered chatbots trained on your specific business — services, pricing, FAQs, locations, timings, and booking flows. Answers customer questions instantly, qualifies leads, and escalates complex queries to your team.

  • Trained strictly on your business data — no hallucination on facts you control
  • Embeds on your website and/or WhatsApp Business API
  • Escalation flow to human agent with full conversation context
  • Lead capture: name, phone, enquiry type — logged to your CRM or dashboard
Internal Tools

Internal business copilots

An AI assistant embedded inside your business software or admin panel — helping staff draft communications, search policy documents, summarise customer history, or generate reports from data without leaving the system.

  • Connected to your internal database — answers questions about your own data
  • Draft email and WhatsApp message generation from structured context
  • Staff-facing knowledge base search across SOPs and documentation
  • Available via API to any module in your existing software
Document AI

Document processing & OCR

Automate the reading, extraction, and filing of data from invoices, purchase orders, medical reports, ID documents, and forms. Eliminates manual data entry for high-volume document workflows.

  • Invoice and PO data extraction into your ERP or accounting system
  • Medical report reading and patient record population
  • ID document verification and data capture for onboarding flows
  • Bulk document classification and folder routing
Offline / Private AI

Offline & on-premise AI systems

For businesses that cannot or will not send data to cloud AI providers — patient records, financial data, legal documents, or confidential processes. We deploy local LLM models (Qwen, Gemma, Mistral, LLaMA) that run entirely on your own hardware with zero external API calls.

  • Runs fully offline — no data leaves your premises
  • Integrated into your existing software via local API
  • Desktop GUI or web UI depending on use case
  • Model selection based on hardware capability and task complexity
Lead Intelligence

AI-powered lead qualification

An AI layer on top of your lead intake — automatically scoring, categorising, and routing inbound enquiries based on intent signals before your sales team touches them. Ensures high-value leads get priority attention immediately.

  • Lead scoring from form data, chat history, and behaviour signals
  • Automatic categorisation by service type, budget range, and urgency
  • Priority routing to the right sales person or team
  • Suggested follow-up message generated for each lead
Reporting AI

Natural language reporting & analytics

Ask your business data questions in plain English or Hindi — "What were my top 5 selling items last week?" or "Which staff member had the highest average bill value this month?" — and get instant answers without building reports manually.

  • Connected directly to your MySQL database via secure query layer
  • Plain language to SQL — no technical knowledge required
  • Answers displayed as text, tables, or charts as appropriate
  • Available inside your existing admin dashboard or as standalone tool
Our approach

How we decide what AI to build — and what not to.

1

Problem First, Technology Second

We start by identifying which specific tasks in your business are high-volume, repetitive, and currently costing significant staff time. Only then do we decide whether AI is the right tool — or whether a simpler automation would do the job better and cheaper.

2

Data Privacy Assessment

We assess what data the AI will touch and whether cloud API models are appropriate, or whether an offline/on-premise model is required. For healthcare, finance, and legal use cases, we default to offline unless explicitly agreed otherwise.

3

Model & Stack Selection

We select the right model and integration approach based on the task, budget, and data sensitivity — from OpenRouter API integrations (GPT-4o, Gemini, Claude) to locally deployed Qwen, Gemma, Mistral, or LLaMA models on your own hardware.

4

Constrained, Tested Deployment

Every AI feature is constrained to a specific scope — the chatbot only answers questions its data covers, the document processor only extracts fields you define, the copilot only accesses data you authorise. We test extensively for edge cases and failure modes before deployment.

5

Measurement & Iteration

After deployment we measure the actual impact — reduction in support ticket volume, time saved per document processed, lead response time improvement. AI integrations are iteratively improved based on real usage data, not assumptions.

AI models we work with

Cloud APIs and offline models — we choose what fits, not what is trendy.

Model / Provider Type Best for Data privacy
GPT-4o (OpenAI) Cloud API Complex reasoning, content generation, customer chat ⚠️ Data sent to OpenAI servers
Gemini (Google) Cloud API Multimodal tasks, document reading, Indian language support ⚠️ Data sent to Google servers
Claude (Anthropic) Cloud API Long document analysis, structured extraction, safe outputs ⚠️ Data sent to Anthropic servers
Qwen 2.5 / 3 Local / Offline Offline business copilots, multilingual (EN/HI/TE), fast on CPU ✅ Fully offline, no data leaves premises
Google Gemma Local / Offline Lightweight offline tasks, low-hardware deployments ✅ Fully offline
Mistral / LLaMA Local / Offline General-purpose offline LLM, open-source, strong reasoning ✅ Fully offline
OpenRouter API Gateway Model routing, fallback logic, cost optimisation across providers ⚠️ Routes to cloud providers
Investment

AI integration pricing depends heavily on scope — honest starting points.

Unlike websites or POS systems, AI projects range from a simple chatbot add-on to a full document intelligence platform. Pricing reflects the complexity of what is being built and integrated.

Add-on

Chatbot or FAQ bot

₹8,000–₹30,000

  • Trained on your business data
  • Website embed or WhatsApp
  • Lead capture integration
  • Human escalation flow
  • Delivery: 1–2 weeks
Module

AI feature inside existing software

₹20,000–₹80,000

  • Copilot, document extractor, or NL reporting
  • Integrated into your existing admin panel
  • Connected to your database and data model
  • Cloud or offline model depending on data
  • Delivery: 2–5 weeks
Full System

Offline AI platform or full pipeline

₹80,000–₹3,00,000+

  • On-premise LLM deployment and configuration
  • Full document processing pipeline
  • Multi-model routing and fallback logic
  • Desktop + mobile app interfaces
  • Delivery: 6–14 weeks

Cloud AI projects have ongoing API usage costs (typically ₹500–₹5,000/month depending on volume) billed to your own API account. Offline AI has no ongoing model costs. Get an exact quote →

FAQ

Common questions about AI integration projects.

This is the most valid concern about chatbots, and we take it seriously. We do not build open-ended chatbots that can freely generate answers about anything. Every chatbot we build is constrained to a specific knowledge base — your FAQs, services, pricing, timings, and policies. When a question falls outside that scope, the bot escalates to a human rather than guessing. The knowledge base is reviewed and approved by you before launch.

For customer-facing chatbots using general business information, cloud APIs (OpenAI, Google, Anthropic) are typically acceptable — they have enterprise data handling policies and do not use API-submitted data for model training by default. However, for sensitive data — patient records, financial transactions, personal IDs, legal documents — we recommend offline AI deployment where no data leaves your premises. We always discuss this explicitly before recommending an approach.

For smaller models like Qwen 1.5B or Gemma 2B, a standard office PC with 8GB RAM is sufficient. For mid-range models like Qwen 7B or Mistral 7B, 16GB RAM and a modern CPU handles most business tasks at acceptable speed. GPU acceleration significantly improves response times but is optional for most internal business use cases. We assess your existing hardware during scoping and recommend the right model size for what you have available.

Yes. Both cloud models (GPT-4o, Gemini) and certain offline models (Qwen 2.5 and above) have strong Hindi and Telugu language capability. For businesses serving customers who prefer regional languages, the chatbot or copilot can be configured to respond in the user's preferred language. Mixed-language (Hinglish, Tenglish) conversations are also handled well by modern models.

No. A website chatbot or WhatsApp bot can be added as a standalone integration without any existing business software. For internal copilots or document processing pipelines, we can build the surrounding software system alongside the AI layer if it does not exist yet. Many clients combine a software build and an AI integration into a single project.

The chatbot's knowledge base is managed through an admin panel — you or your manager can edit FAQs, update service descriptions, change prices, and add new policies without any developer involvement. Changes take effect immediately. For major overhauls (new service lines, complete restructuring), we provide a retraining service as a small add-on engagement.

Let's find the right AI for your business

Tell us the problem. We'll tell you honestly whether AI is the right answer.

Start by describing the task or workflow that is costing your team the most time right now. We will assess whether AI is the right tool, which approach fits your data and budget, and what the realistic outcome looks like — before you commit to anything.