Mitra is a website-embedded AI FAQ chatbot built for Nfilade Security Solutions / MyNetSec to help customers resolve common Tier-1 support queries through self-service.
The chatbot was implemented using Botpress Cloud Webchat and integrated into the company website with lightweight HTML and JavaScript. It gave customers a simple conversational interface for frequently asked questions, reducing repetitive manual support workload and helping resolve approximately 50% of Tier-1 support queries without human intervention.
| Area | Details |
|---|---|
| Status | Complete |
| Problem | Reduce repetitive Tier-1 support workload while giving customers faster self-service access to common answers |
| Approach | Botpress-powered FAQ assistant embedded in a customer-facing website, with guided responses and escalation for unsupported queries |
| Tech | Botpress Cloud, Botpress Webchat, HTML, JavaScript, browser session storage |
| Reproducibility | Setup, deployment, test scenarios, and web-embed artefacts are documented in docs/, deployment/, and tests/ |
| Validation | Common Tier-1 query testing, fallback and escalation-path review, and deployment-focused frontend/security hygiene |
| Observed outcome | Approximately 50% of Tier-1 support queries were resolved through self-service in the documented deployment context |
| Key design choice | Used a maintainable conversational platform instead of over-engineering a custom NLP stack for a narrow FAQ workflow |
| Scope | Customer-support automation prototype; outcome metrics should be interpreted within the documented query set and deployment context |
Project type: Conversational AI chatbot integration Use case: Customer support automation Platform: Botpress Cloud Frontend integration: HTML, JavaScript Chatbot name: Mitra Business outcome: Around 50% Tier-1 support query resolution through self-service
Customer support teams often handle the same basic questions repeatedly. These questions are usually important, but they do not always require manual support.
Typical examples include:
- How do I contact support?
- How do I access my account?
- Where can I find service information?
- How do I raise a support request?
- What should I do if I face a login issue?
Before Mitra, customers depended more heavily on static FAQ pages or manual support channels. This created unnecessary waiting time for users and repetitive work for the support team.
The real problem was not “build a chatbot.”
The real problem was:
Customers needed quick answers to repeated support questions, and the support team needed fewer low-complexity tickets.
A full custom NLP system would have been excessive for this scope. A faster and more maintainable solution was to use a conversational AI platform, configure the support flow, and embed it directly into the customer-facing website.
That is why Botpress was a practical fit.
Mitra was built as a Botpress-powered FAQ assistant and embedded into the company website using the Botpress Webchat script.
The chatbot acts as a first-response support layer. Users can ask questions in natural language, receive guided responses, and resolve common issues without submitting a ticket.
For unclear or unsupported questions, the chatbot can guide the user toward human support or the appropriate escalation path.
- Website-embedded chatbot interface
- Branded assistant named Mitra
- Conversational FAQ support
- Customer self-service for common Tier-1 queries
- Botpress Cloud Webchat integration
- Session-based chat experience
- Lightweight HTML and JavaScript deployment
- Scalable first-response layer for support automation
| Area | Technology |
|---|---|
| Chatbot Platform | Botpress Cloud |
| Webchat Embed | Botpress Webchat |
| Frontend | HTML, JavaScript |
| UI Theme | Prism |
| Session Handling | Browser session storage |
| Deployment Context | Website-based customer support |
| Use Case | FAQ automation and Tier-1 support deflection |
Customer visits website
|
Botpress Webchat loads
|
Customer asks a support question
|
Mitra matches the query to a relevant FAQ or support flow
|
Chatbot returns a structured response
|
Customer resolves the issue or escalates to human support
The chatbot was embedded using Botpress Cloud’s webchat script and configuration file.
<script src="https://cdn.botpress.cloud/webchat/v1/inject.js"></script>
<script src="https://mediafiles.botpress.cloud/b53b849f-1eb2-493a-9746-fc818d576c5c/webchat/config.js" defer></script>A simplified initialization example is shown below:
<script>
window.botpressWebChat.init({
composerPlaceholder: "Chat with Mitra",
botConversationDescription: "Customer support chatbot for FAQ self-service",
botName: "Mitra",
themeName: "prism",
themeColor: "#2563eb",
useSessionStorage: true,
showBotInfoPage: true
});
</script><!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Mitra FAQ Chatbot</title>
<meta
name="description"
content="Mitra is a Botpress-powered AI FAQ chatbot built for customer self-service and Tier-1 support automation."
/>
<script src="https://cdn.botpress.cloud/webchat/v1/inject.js"></script>
<script
src="https://mediafiles.botpress.cloud/b53b849f-1eb2-493a-9746-fc818d576c5c/webchat/config.js"
defer>
</script>
</head>
<body>
<script>
window.addEventListener("load", function () {
window.botpressWebChat.init({
composerPlaceholder: "Chat with Mitra",
botConversationDescription: "Customer support chatbot for FAQ self-service",
botId: "b53b849f-1eb2-493a-9746-fc818d576c5c",
hostUrl: "https://cdn.botpress.cloud/webchat/v1",
messagingUrl: "https://messaging.botpress.cloud",
clientId: "b53b849f-1eb2-493a-9746-fc818d576c5c",
webhookId: "0bb8fa12-c2b5-4dd9-923f-4fd1679c208b",
lazySocket: true,
themeName: "prism",
botName: "Mitra",
frontendVersion: "v1",
useSessionStorage: true,
showBotInfoPage: true,
showPoweredBy: true,
theme: "prism",
themeColor: "#2563eb",
allowedOrigins: []
});
});
</script>
</body>
</html>The chatbot’s value was measured through support deflection.
Primary success metric:
Tier-1 self-service resolution rate = resolved chatbot queries / total Tier-1 support queries
Observed result:
Approximately 50% of Tier-1 support queries were resolved through self-service
This means the chatbot helped reduce repetitive support workload while giving customers faster access to basic help.
My contribution included:
- Configuring the Botpress chatbot experience
- Embedding the chatbot into the customer-facing web interface
- Customizing the assistant identity as Mitra
- Setting up webchat behavior and session handling
- Aligning chatbot responses with FAQ and support needs
- Testing the assistant against common Tier-1 customer queries
- Improving the web embed structure for cleaner deployment
- Reviewing the implementation for basic frontend and security hygiene
The project was designed around a practical build-vs-buy decision.
| Option | Pros | Cons | Decision |
|---|---|---|---|
| Build custom NLP chatbot from scratch | Full control, deeper ML ownership | Slower, harder to maintain, unnecessary for narrow FAQ scope | Not selected |
| Use static FAQ page only | Simple, low cost | Poor user experience, no conversational flow | Not enough |
| Use Botpress webchat | Fast deployment, maintainable, conversational interface | Platform dependency | Selected |
Botpress was the right choice because the business needed fast support automation, not research-grade NLP.
Customers were asking repeated Tier-1 support questions. Support teams were spending time on issues that could be answered through existing FAQ knowledge.
The problem was narrow, repetitive, and support-focused. A low-code chatbot platform was more suitable than building a custom NLP model from scratch.
Use Botpress Cloud Webchat to deploy a branded FAQ assistant directly on the website.
Configure the chatbot, embed it into the web page, test common support queries, and use the assistant as a first-response customer support layer.
Relevant keywords for this project:
- AI FAQ chatbot
- Botpress chatbot
- customer self-service chatbot
- Tier-1 support automation
- conversational AI
- support deflection
- website chatbot
- customer support automation
- AI helpdesk assistant
- FAQ automation
Potential next steps include:
- Add analytics for unanswered questions
- Connect chatbot logs to support dashboards
- Add human handoff for unresolved queries
- Integrate with CRM or ticketing tools
- Add multilingual support
- Improve FAQ coverage using conversation data
- Add semantic search or retrieval-augmented generation for richer answers
- Create an admin workflow for updating FAQ content