Businesses drowning in repetitive questions
Sales and support teams answer the same queries every day on the phone, website chat and WhatsApp.
AI CHATBOTS · AI INTEGRATION · MACHINE LEARNING
AI/ML Development Services
We help businesses use AI where it genuinely saves time or improves decisions: assistants that answer from your own documents, AI features inside your website or app, automated document and email handling, and machine-learning models built on your data. Every project starts with a small, measurable pilot.
What AI/ML development means for a business
AI development is building software that can understand language, read documents, recognise patterns or make predictions. Today most business value comes from two approaches. Generative AI uses large language models (LLMs) through an API to write, summarise, answer questions and extract information. Machine learning trains a model on your historical data to predict or classify, for example which leads are likely to buy or how much stock you will need. The engineering work is connecting either approach safely to your data, your systems and your users.
Teams processing documents by hand
Invoices, purchase orders, forms and CVs are read and retyped into other systems.
Product companies adding AI features
You want smart search, summaries, recommendations or an assistant inside your existing web or mobile product.
Companies sitting on useful data
Years of sales, customer or operations data could support forecasts and better decisions.
AI and machine learning services
AI chatbots and assistants
Website, WhatsApp and in-app assistants that answer from your own content using retrieval-augmented generation (RAG), with hand-off to a human when needed.
AI integration into existing software
Adding summarisation, classification, drafting or smart search to your current website, CRM, portal or app through AI APIs.
Document and data extraction
Reading invoices, forms, PDFs and emails, pulling out the fields you need and sending them to your systems for review.
Workflow automation with AI
Routing enquiries, tagging tickets, drafting replies and generating reports automatically, with people approving the important steps.
Machine-learning models
Prediction and classification models such as lead scoring, demand forecasting and churn risk, trained and tested on your historical data.
Recommendation and search
Product and content recommendations and semantic search that understands what users mean, not just the words they type.
AI consulting and proof of concept
A short, fixed-scope pilot to test whether an AI idea works with your real data before you commit to a full build.
Monitoring and improvement
Tracking answer quality, cost and usage after launch, and improving prompts, data and models over time.
API, fine-tuning or custom model: which approach fits?
Choosing the right technical approach controls both cost and quality. We recommend the simplest option that meets the goal.
Use an AI model through an API
Fastest and cheapest to start. Suits chat, drafting, summarising and extraction. You pay per use, and your data is sent to the model provider under their terms.
Add retrieval (RAG) over your content
The model answers from your documents, policies and product data instead of general knowledge. This is the right choice for most company assistants and reduces made-up answers.
Fine-tune a model
Useful when you need a consistent style or format across many outputs and have good example data. More effort, and only worth it after a simpler version proves the use case.
Train a custom ML model
Best for predictions from structured data (numbers, categories, history), where language models are the wrong tool.
AI use cases by industry
Retail and e-commerce
Product Q&A assistants, description writing, review summaries, recommendations and demand forecasting.
Healthcare
Appointment and FAQ assistants, document summarisation for staff and triage of incoming enquiries, with strict privacy controls.
Education and training
Course assistants, question generation, admission query handling and student-support chat.
Manufacturing and B2B
Quotation drafting, specification lookup, purchase-order extraction and dealer support assistants.
Professional services
Contract and document summarisation, proposal drafting and internal knowledge search.
Marketing and sales teams
Lead scoring, enquiry routing, content drafts and call-note summaries in the CRM.
How we deliver AI projects
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1. Use-case workshop
We list where time and money are lost, pick one use case with clear value and agree how success will be measured.
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2. Data check
We review the documents or data the AI will use: quality, gaps, privacy and permissions.
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3. Pilot
A small working version tested on real examples, with an evaluation set of questions or records it must handle correctly.
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4. Build and integrate
Production version connected to your website, app, CRM or WhatsApp, with logins, logging, guardrails and human review steps.
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5. Launch and measure
Gradual rollout, monitoring of accuracy, usage and cost, and a feedback loop from your team.
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6. Improve
Regular updates to content, prompts and models as your business and the AI tools change.
Responsible and secure AI
Your data, handled carefully
We only use the data a use case needs, explain where it is processed and help you choose providers whose data terms suit you, including India's DPDP Act obligations.
Grounded answers
Assistants answer from approved sources, show where an answer came from where possible and say "I don't know" instead of guessing.
Humans in the loop
Anything that affects money, health or legal commitments goes to a person for approval.
Cost control
Usage limits, caching and model choice keep running costs predictable.
AI technology stack
Application layers use our confirmed web stack; AI providers and libraries are chosen per project.
Application layer
- Node.js
- PHP / Laravel
- React
- WordPress
- Shopify / WooCommerce
Channels
- Website chat
- Mobile apps
Engagement models
Pick the way of working that fits an AI project. You can switch models later as the work changes.
Fixed-scope project
Best for a pilot or proof of concept: a fixed scope, a fixed evaluation set and a clear go/no-go decision at the end.
Dedicated developer or team (monthly)
Best for ongoing products. A developer or small team works on your project full time, follows your priorities and joins your tools and stand-ups.
Hourly / time and materials
Best for maintenance, small changes and evolving scope. You pay for the hours actually used, with a log of what was done.
Why choose Icon Web Solution
10+ years in business
Icon Web Solution has been building and marketing websites for more than ten years. We have seen what still works after launch day, and we plan every AI project with that in mind.
A real office in Ahmedabad
Our team works from TF 15 Adishwar Gold Complex, Ahmedabad 380049, Gujarat, India. You can visit, meet the people doing the work and review progress in person.
Live work you can check
Apple PVC, SGVP Holistic Hospital, Pomelo and JHB Collections are live sites we built. Open them on your phone and judge the quality yourself.
Build and growth under one roof
Design, development, SEO and digital marketing sit in the same company, so the site that gets built is also the site that gets found and converts.
AI that plugs into real systems
We already build the websites, stores, apps and back ends AI needs to connect to, so the AI is not a demo sitting on its own.
Honest about where we are
AI/ML is our newest service line. We start every client with a measured pilot, and we will publish our AI case studies only once they are real and approved.
What affects the cost of an AI project?
Use case complexity
An FAQ assistant over a few documents is far simpler than an agent that takes actions in several systems.
Data preparation
Clean, digital, well-organised data is quick to use; scanned, scattered or inconsistent data needs preparation.
Integrations
Each connected system (CRM, ERP, WhatsApp, website) adds build and testing time.
Accuracy requirements
Higher accuracy targets need larger evaluation sets, more tuning and human review flows.
Running costs
AI APIs are billed per use; volume, model choice and caching decide the monthly cost.
Security and privacy
Sensitive data may need private hosting, extra access controls and audit logging.
AI/ML development FAQs
What AI services do you offer?
We build AI chatbots and assistants, add AI features to existing websites and apps, automate document and email processing, and develop machine-learning models for predictions such as lead scoring and demand forecasting.
How much does AI development cost?
Cost depends on the use case, data preparation, integrations, accuracy targets and running costs for AI APIs. We recommend starting with a fixed-price pilot so you see results before committing to a full build.
How long does it take to build an AI chatbot?
A pilot assistant that answers from your own content can be ready in weeks. A production assistant connected to your CRM, WhatsApp and other systems takes longer, depending on integrations and testing.
Can AI be added to my existing website or app?
Yes. Most AI features are added through APIs, so your current website, app or CRM can gain search, summaries, assistants or automation without being rebuilt.
Will the chatbot give wrong answers?
Any AI can make mistakes, so we reduce the risk: answers come from your approved content, the assistant is tested against real questions before launch and it hands over to a human when unsure.
Is my data safe when using AI?
We use only the data a use case needs, explain where it is processed and choose providers and settings that match your privacy requirements, including obligations under India's DPDP Act.
What is the difference between AI and machine learning?
AI is the broad field of software that performs tasks needing human-like intelligence. Machine learning is one part of AI where models learn patterns from data to make predictions. Generative AI, such as ChatGPT-style models, is another part focused on creating text and other content.
Do I need a lot of data to use AI?
Not for most generative AI projects; your existing documents, FAQs and product data are often enough. Predictive machine-learning models do need a reasonable amount of clean historical data.
Can the AI assistant work on WhatsApp?
Yes. An assistant can be connected to the WhatsApp Business Platform as well as your website and app, sharing the same knowledge base.
Do you have AI case studies?
AI/ML is our newest service line, and our first AI projects are being delivered now. We will publish case studies once they are complete and approved by the clients; until then we start every engagement with a measurable pilot.
Have a task you think AI could handle?
Tell us the task, how it is done today and roughly how often. We will tell you honestly whether AI is a good fit and what a pilot would involve.
Tell us the task, how it is done today and roughly how often. We will tell you honestly whether AI is a good fit and what a pilot would involve.
Discuss an AI Use Case Call +91 88663 03099
TF 15 Adishwar Gold Complex, Ahmedabad 380049, Gujarat, India · info@iconwebsolution.com · +91 88663 03099 · +91 74053 75923