AI-Powered Chat Interfaces for Apps & Websites

Seamless, intelligent, and real-time chat for modern digital products. Transform how users interact with your app or website using Tecorb's advanced AI/ML, NLP, and multi-modal platform.

Introduction to AI-Powered Chat Interfaces

In today's fast-paced digital environment, users expect seamless, intelligent, and real-time interactions within applications and websites. At Tecorb Technologies Pvt. Ltd., we build AI/ML-powered conversational interfaces that transform how users engage with digital products. By integrating cutting-edge natural language processing (NLP), voice recognition, and machine learning (ML) models, we deliver chat experiences that feel human, helpful, and highly contextual.

Next-Generation Conversational AI

Our chat interfaces leverage advanced AI models, voice/text processing, and dynamic backend integration protocols to intelligently understand user intent, retrieve relevant data, and respond in natural language.

Real-Time Processing

Whether embedded in mobile apps or web platforms, our chat UI bridges users with systems, services, and structured data seamlessly.

Core Architecture Overview

Our system architecture supports a full AI pipeline from user interaction to response generation:

Multi-modal Input

Process text and voice inputs through our NLP pipeline

Query Understanding (MCP)

Extract intent and context using our Model Context Protocol

Endpoint Resolution

Map user intent to appropriate API endpoints

Response Retrieval

Gather data from JSON endpoints and structured sources

LLM Processing

Format responses using LLaMA and Groq for natural language

Actionable Outputs

Display results with embedded action links

Voice & Text-Based Input

Users can interact using natural voice or text inputs. Our NLP modules convert voice to text (ASR) and normalize textual input to prepare it for semantic interpretation.

Model Context Protocol (MCP)

Our MCP extracts user intent and dynamically maps it to API endpoints. It ensures query context is preserved across turns and sessions for coherent conversations.

Understanding Message Intent with MCP

The MCP module parses the message, identifies domain-specific intents, and prepares structured queries that align with predefined or learned API routes. Once the intent is matched, the system issues backend calls to one or more JSON endpoints - internal APIs, third-party services, or business systems.

Processing Responses with LLMs and FAISS

Semantic Search Using FAISS

In scenarios where structured data isn't sufficient, we use FAISS for semantic similarity search. FAISS helps retrieve relevant information from large vectorized corpora like knowledge bases and PDF extractions.

LLaMA and Groq Integration

Raw data is converted into clear, coherent responses using large language models like LLaMA running on Groq chips for low-latency performance, creating human-like messages tailored to user context.

Response Rendering with Clickable Action Links

The final output is not just informative—it's actionable. We embed hyperlinks or buttons that point directly to relevant pages or features within your app or website.

Contextual Linking

We embed deep links to app pages or features, making responses actionable and creating seamless transitions between conversation and functionality.

Adaptive UX

Chat UI is responsive and context-aware. Mobile apps support deep linking and native transitions, while web interfaces integrate embedded frames, tabs, or modals.

Voice & Text Chat Integration

Whether the user is typing or speaking, the underlying system architecture remains the same. The voice is transcribed, contextualized, and routed like text. Users enjoy a consistent experience across interaction types.

Integrating Structured Data From 3rd-Party Systems

Our chatbots connect with tools like Salesforce, Zoho CRM, ServiceNow, Zendesk, SAP, and more. Data is pulled, filtered, and formatted into conversational replies that respect business rules and data governance policies.

CRM & ERP Connectivity

Each query syncs live with your systems, remembering user context and previous interactions.

Security & Compliance

HTTPS encrypted, OWASP compliant with data protection and JSON sanitization.

Multi-Modal Input Support

We support multiple input and response modalities:

Text and voice

Button-based UI interactions

API-driven triggers (e.g., event-based queries or CRM notifications)

This flexibility ensures that our AI chat solutions adapt to a wide variety of enterprise use cases.

Security, Scalability & Performance

Secured Query Routing

All interactions are HTTPS encrypted and comply with OWASP standards. Our middleware sanitizes JSON inputs/outputs and applies rate limits and authentication as required.

LLM Latency Optimization

We deploy our LLMs on Groq hardware for optimized performance, achieving ultra-low response latency even at scale.

Industry Use Cases

E-commerce: Product search, order tracking, recommendations

Healthcare: Appointment scheduling, symptom checking

Fintech: Balance info, fraud alerts, compliance/KYC

EdTech: Smart FAQs, content discovery, mentor chat

Travel: Booking, live itinerary, real-time advisory

Why Choose Tecorb?

1

Full-stack expertise in AI/ML, NLP, and vector search tech

2

Battle-tested with LLaMA, Groq, FAISS, and Model Context Protocol

3

Cloud-native, scalable, and secure SaaS architecture

4

Integration-ready with leading CRMs, ERPs, SaaS products

5

Dedicated support, customizations, and ongoing maintenance

Fixed Project Price

$1200

Full implementation, integration, and launch

Hourly Rate

$22/hour

For customizations & maintenance

Ongoing Support Plans

All packages include 3 months of standard support. Extended plans available:

Basic Support

$750/month

Email support, 48-hour response time

Premium Support

$1,500/month

Email + phone support, 24-hour response time

Enterprise Support

$3,000/month

Dedicated support manager, 4-hour response time

Security & Performance

Secured Query Routing

All interactions are HTTPS encrypted and comply with OWASP standards with proper rate limiting.

LLM Latency Optimization

Ultra-low response latency using Groq hardware for optimized performance even at scale.

Key Features

Voice & Text Recognition

Model Context Protocol

Backend Integration

LLMs & Semantic Search

API Query Orchestration

Multi-Modal Support

Ready to Transform Your User Interactions?

Implement our AI-powered Chat Interface to provide accurate, instant responses to your customers while reducing support costs.