Consumer electronics D2C
- Challenge
- Support and sales needed shared conversation context.
- Simplileap solution
- WhatsApp bot with CRM handoff on low-confidence intents.
- Outcome
- CSAT 4.1/5 on bot-resolved threads.
// Automate
Conversational AI Integrations
Conversational AI is a platform, not a single tool. We integrate the right combination of NLU, LLM, channel APIs, and CRM systems to create a coherent conversational experience across every touchpoint.
// Key benefits
What makes this service valuable
Multi-channel orchestration
Web chat, WhatsApp, SMS, voice, and email, managed through a single conversational AI backbone with channel-appropriate UX adaptations.
Existing platform enhancement
Enhance existing chatbot platforms (Intercom, Drift, Zendesk) with LLM capabilities, without replacing the platform your team already knows.
CRM context integration
Conversation history, customer data, and interaction context available to the conversational AI in real time, enabling personalised, context-aware responses.
// Details
Unified conversational AI across channels
Conversational AI integration brings together multiple components: the LLM or NLU engine, the channel APIs, the knowledge base, the CRM, and the analytics layer. Getting these working together reliably is the integration challenge.
We design conversational AI architectures that are channel-agnostic, the conversation logic is written once and deployed across channels with minimal adaptation.
// What this includes
- Conversational AI architecture design
- NLU engine integration (Dialogflow, Rasa, AWS Lex)
- LLM integration for free-text understanding
- Multi-channel deployment
- CRM and context integration
- Analytics and conversation quality tracking
- Continuous improvement pipeline
// Deliverables
What you receive
Every engagement produces clear, documented deliverables. Here is exactly what is included in our conversational ai integrations service.
- 01Conversational AI architecture and integration
- 02Multi-channel deployment setup
- 03CRM and context integration
- 04Analytics and monitoring setup
- 05Improvement pipeline documentation
// In practice
How conversational ai integrations engagements run
Omnichannel bots share one NLU core but channel-specific payloads — WhatsApp template messages, web widget session state, and voice SSML for IVR handoffs. CRM context (open tickets, subscription tier) is injected before each LLM call via your existing REST APIs. Channel-level CSAT and containment rates are reported separately so web vs WhatsApp tuning stays honest.
// Stack & frameworks
Stack we use for this
AI & LLM
- OpenAI / Anthropic APIs
- LangChain pipelines
- RAG architectures
- Confidence thresholds
Integration
- Salesforce / HubSpot
- Zapier / Make
- Custom webhooks
- ERP connectors
Governance
- LangSmith observability
- PII handling
- Audit logs
- Rollback procedures
// Delivery
Simplileap execution framework
01
Architecture mapping
Dependencies, API contracts, compliance constraints, and performance budgets documented before sprint one.
02
Secure sprints
Two-week increments with GitHub access, demo recordings, and QA checkpoints, client visibility at every stage.
03
QA & handover
Automated tests on critical paths, security review, runbooks, and knowledge transfer to your team.
// Proof
Real deployments from Bangalore
// Engagement models
How teams engage us
Currency
| Package | Ideal for | Investment | Includes |
|---|---|---|---|
| Workflow automation | Ops teams | ₹3L – ₹10L |
|
| AI / LLM integration | Product teams | ₹4L – ₹12L |
|
| RPA implementation | Back-office | Scoped per process |
|
// Company and service positioning
Company and Service positioning is reviewed for production delivery standards by Harsha Parthasarathy (Co-Founder, Strategy & Operations 24+ years IT veteran, IBM, Global Delivery, Program Management) and Keshav Sharma (Co-Founder, Engineering and Lead Architect, Full-stack engineering, product delivery and technical standards).
CIN
AAU-8582
Startup India
DIPP83124
Founded
November 2020
Office
Residency Rd, Bengaluru, India
// FAQ
Common questions about conversational ai integrations
Should I build a custom chatbot or use a platform?+
Platform (Intercom, Drift) for customer-facing chat where your team needs to manage conversations and you want out-of-the-box CRM integration. Custom for specific requirements, non-standard channels, or when platform cost at scale is prohibitive.
Ready to get started with conversational ai integrations?
Share your requirements with our team. We respond within one business day with a clear plan from discovery to delivery.