Process Automation

Conversational AI — Intelligent Interactions at Any Scale

Modern conversational AI understands intent, maintains context, connects to enterprise systems, and resolves complex requests autonomously — across voice and text channels, 24/7.

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Capabilities

Conversational AI & Chatbots — deep expertise

Intelligent Virtual Assistants

NLU-powered virtual assistants for customer service, IT support, and HR queries — resolving 60–80% of requests without human intervention.

DialogflowAzure Bot FrameworkAmazon Lex

LLM-Powered Conversations

Generative AI chatbots grounded in your knowledge base through RAG architecture — accurate, contextual responses with source citations.

RAG ArchitectureGPT-4ClaudeKnowledge Base

Omnichannel Deployment

Unified chatbot across web, mobile, WhatsApp, Teams, Slack, and voice IVR — maintaining conversation context across channel switches.

WhatsAppMicrosoft TeamsSlackVoice IVR

Enterprise System Integration

Bots that take action — creating tickets, looking up orders, processing returns, updating records — across CRM, ERP, and ITSM in real time.

CRM IntegrationERP LookupsServiceNowTicket Creation

Conversation Analytics

Intent analytics, containment rate dashboards, and conversation flow analysis continuously improving bot performance.

Containment RateCSATIntent AnalyticsDeflection Rate

Live Agent Handoff

Seamless escalation to human agents with full conversation context transfer — no information loss when bots escalate.

Agent TransferContext HandoffCSAT Tracking

Bot Results

Conversational AI Containing Costs

5M+

Conversations handled annually

72%

Average containment rate

24/7

Availability without staffing cost

4.3/5

Average CSAT for bot interactions

Our Approach

From Chatbot Ideas to Deployed Conversational AI

Conversation Design

Map user intents, define conversation flows, identify escalation triggers, and design the knowledge base.

Platform Config

Configure NLU models, entity extraction, dialogue management, and channel integrations.

Training & Testing

Train on domain-specific utterances, test with real users, and iterate on low-confidence paths.

Launch & Optimize

Deploy across channels with live monitoring, fallback analysis, and monthly intent model updates.