Conversational AI & Copilots
Intelligent Assistants for Enterprise
Hybrid NLU + LLM architectures, enterprise copilots, omnichannel deployment, and voice AI - built for real-world conversations.
Why This Matters
Chatbots Are Dead. Copilots Are the Future.
The era of decision-tree chatbots is over. Users expect AI assistants that understand context, remember previous interactions, take actions on their behalf, and seamlessly switch between channels. Enterprise copilots that integrate with ERP, CRM, and ITSM are replacing static FAQ bots.
But building a production conversational AI system is harder than it looks. You need deterministic flows for high-stakes interactions (payments, approvals) combined with LLM flexibility for open-domain queries. You need omnichannel deployment across web, WhatsApp, Slack, and voice. And you need guardrails that prevent the AI from going off-rails in customer-facing scenarios.
We build hybrid architectures that combine the reliability of Rasa/Dialogflow intent classification with the flexibility of LLM-powered conversation. Our copilots execute actions (create tickets, approve requests, query databases) - they don't just answer questions.
Our Tech Stack
Production-Grade Tools We Deploy
Conversational Platforms
LLM-Powered Chat
Voice AI
NLU & Intent Classification
Orchestration
Channels
Analytics & Monitoring
Guardrails & Safety
Architecture Deep-Dive
How We Build It
Hybrid NLU + LLM Architecture
Intent classification with Rasa/Dialogflow for deterministic flows, with LLM fallback for open-domain queries. Predictable core flows with flexible conversational ability.
- Rasa/Dialogflow intent classification for high-stakes flows (payments, approvals)
- LLM fallback for open-domain queries the intent model doesn't cover
- Confidence-based routing: high-confidence -> deterministic, low -> LLM
- Slot filling with entity extraction for structured data collection
- Context carryover across conversation turns with LangGraph state
- Graceful escalation to human agents with full conversation context
Enterprise Copilot Design
Context-aware assistants that integrate with ERP, CRM, ITSM, and internal knowledge bases. Copilots that execute actions - not just answer questions.
- Tool-calling copilots: create Jira tickets, approve ServiceNow requests, query SAP
- RAG-powered knowledge retrieval from Confluence, SharePoint, internal wikis
- User-context awareness: copilot knows your role, department, and permissions
- Multi-step task execution: 'Book me a flight' triggers search -> compare -> book
- Proactive suggestions: copilot surfaces relevant information before you ask
- Audit trail of all copilot actions for compliance
Omnichannel Deployment
Single conversation engine deployed across web chat, WhatsApp, Slack, Teams, and voice. Channel-specific rendering with session continuity across channels.
- Single conversation engine serving all channels from one codebase
- Channel-specific rendering: rich cards on web, plain text on SMS
- Session continuity: start on WhatsApp, continue on web chat
- WhatsApp Business API via Twilio for customer-facing support
- Slack/Teams bots for internal employee copilots
- Unified analytics dashboard across all channels
Voice AI Pipelines
Real-time speech-to-text with Whisper/Deepgram, LLM-powered response generation, text-to-speech with ElevenLabs. Sub-second latency voice agents.
- Deepgram streaming STT with <300ms latency for real-time voice
- Whisper for batch transcription with 99%+ accuracy in 97 languages
- ElevenLabs TTS for natural-sounding voice responses
- End-to-end voice agent latency under 1 second (STT -> LLM -> TTS)
- Speaker diarization for multi-party call analysis
- Voice biometrics for caller authentication without passwords
Data Security, Governance & Safety
Enterprise AI demands enterprise-grade security. Every solution we deploy follows strict data sovereignty, safety, and compliance standards.
Data Sovereignty
- Your data stays in your infrastructure - always
- Deploy on your cloud (AWS, Azure, GCP) or on-premise
- No data leaves your environment
- Full compliance with regional data residency requirements
Model Safety & Guardrails
- NVIDIA NeMo Guardrails for content safety
- PII detection and redaction with Presidio
- Prompt injection defense and input sanitization
- Hallucination detection and factual grounding
Access Control & Audit
- Role-based access control for all AI systems
- Immutable audit logs for every interaction
- SOC 2 Type II, ISO 27001 compliance frameworks
- GDPR, HIPAA, and industry-specific regulations
Responsible AI
- Bias testing with Fairlearn and AI Fairness 360
- Model explainability via SHAP and LIME
- Transparency reports for stakeholders
- Continuous fairness monitoring in production
FAQ
Frequently Asked Questions
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