Vasilkoff.info - AI Project Estimator & Chat Support Web App

Executive Summary

• Product: Vasilkoff.info, our standalone AI estimator and support application
• Sector: AI-assisted intake, web apps, support automation
• Engagement: Product strategy, Next.js delivery, estimator logic, embeddable widget architecture
• Core stack: Next.js, React, custom AI logic, embeddable Vanilla JS and React widgets
• Outcome snapshot: A focused web app that turns early-stage website interest into structured project scope, instant answers, and professional offer generation

The Problem

Most service-company websites make visitors do too much work before they get clarity. Prospects have to browse multiple pages, guess what information matters, wait for someone to reply, and often repeat the same project description again in email or a discovery call.

That creates friction on both sides:

• visitors drop before giving enough project detail
• support questions interrupt the team with repetitive enquiries
• scoping quality varies depending on who handles the first contact
• business context stays trapped in human memory instead of being operationalized

We wanted a system that could qualify interest, answer common questions, and move people toward a usable project outline immediately.

Why It Was Difficult

A simple chatbot would not solve the real problem.

The experience needed to combine:

• domain-specific answers about Vasilkoff Ltd and its services
• practical intake logic that collects useful project information
• estimation behavior that feels structured instead of gimmicky
• a user experience fast enough for public website traffic
• a reusable widget model that could be embedded outside the main app

The hard part was not just generating text. It was converting early-stage curiosity into a more actionable sales and support workflow.

Our Solution

We built Vasilkoff.info as a standalone application rather than a hidden widget bolted onto the main site.

The app gives visitors one place to ask questions, describe their idea, and receive structured guidance. Behind that experience, we implemented domain-tuned AI logic focused on estimation, company knowledge, and support assistance. The main app is built with Next.js, and we also developed an embeddable chat widget available in both Vanilla JS and ReactJS so the same capability can be deployed in multiple frontend environments.

This makes the product useful in two ways at once:

• as a working intake and support experience for our own business
• as a reusable proof point for clients who need the same pattern in their own stack

What We Delivered

• A standalone AI estimator and support web app
• Domain-specific chat logic for company and project questions
• Structured intake flow for capturing project details
• Professional offer generation as part of the estimator workflow
• Embeddable AI chat widgets for Vanilla JS and React applications
• A Next.js application architecture optimized for smooth public-facing use

Results

• Faster path from interest to scope: visitors can move from a vague idea to a more structured project outline in one session instead of waiting for manual triage
• Lower support repetition: the system handles common company and service questions without requiring the team to answer the same basics each time
• Better handoff quality: the estimator gathers more useful information before a human conversation starts, improving the quality of the next step
• Reusable product capability: the chat and intake logic is not locked inside one site; it can be embedded elsewhere through Vanilla JS and React packages
• Real internal proof, not a lab demo: the product actively supports the Vasilkoff.com intake experience, making it a live operational showcase rather than a speculative prototype

Technical Highlights

Next.js as the application shell

The main product runs on Next.js to keep the interface fast, structured, and suitable for public traffic while still supporting a more application-like flow than a static marketing page.

Reusable widget delivery

A lot of AI demos stop at a single hosted site. We built both Vanilla JS and React widget paths so the same conversational capability can be embedded into different frontend stacks with less integration friction.

Domain-tuned AI logic

The useful part of the system is not generic chat. It is the domain tuning around project scoping, service explanation, and business-context retrieval.

Proof Artifacts

• Live product: vasilkoff.info
• Portfolio asset: /public/assets/portfolio/vasilkoff.info.webp
• Embedded usage across the main site includes the estimator and AI chat entry points linked from the homepage and pricing flows

Transferable Value For Clients

Vasilkoff.info is directly relevant if you need:

• AI-assisted project scoping
• website chat that qualifies leads instead of just greeting visitors
• support automation grounded in business-specific knowledge
• structured offer or proposal generation
• a conversational interface that can be embedded across multiple sites or products

This case study shows how we approach AI pragmatically: we use it to reduce friction, improve qualification, and make human follow-up better informed.

For a related example focused more on always-on live chat and visitor engagement, see SmartAIChats.

Work With Us

If you want users to get to scope, answers, or offers faster, contact us. We can adapt the same intake-first architecture for your business, product, or support workflow.