Conversational AI
Next-gen interfaces that feel human, perform at scale.
We build voice and chat interfaces powered by large language models that handle real customer conversations — resolving queries, qualifying leads, and delivering support at a quality level that makes users forget they are talking to software.
Conversations That Convert and Resolve
The era of brittle decision-tree chatbots that frustrate users with 'I did not understand that, please choose from the options below' is over. Modern conversational AI — built on LLMs with proper context management — can handle the full complexity of real human dialogue: ambiguous questions, mid-conversation topic changes, nuanced complaints, and multi-turn negotiations.
CodeWingz builds conversational AI systems for two primary use cases: customer support (resolving queries, answering product questions, processing requests) and sales (lead qualification, product recommendation, demo scheduling). We handle the full stack: the LLM reasoning layer, the integration with your knowledge base and CRM, the streaming chat or voice interface, and the handoff mechanics to human agents.
Every system we build prioritises three things: response quality (accurate, on-brand, empathetic), latency (fast enough that conversation feels natural), and controllability (your team can update responses, adjust tone, and route edge cases without touching code).
Service Inclusions
LLM-Powered Chat
Context-aware chat interfaces that maintain conversation history, handle topic switches, and resolve complex multi-part queries — deployed on your website, app, or WhatsApp.
Voice AI Interfaces
Full-duplex voice agents with streaming STT (Deepgram/Whisper) and TTS (ElevenLabs/Azure) achieving sub-800ms end-to-end latency for natural phone and web voice interactions.
Intent & Entity Recognition
Fine-tuned classification models that detect user intent with high accuracy, extract key entities, and route conversations to the right response strategy or human agent.
Knowledge Base Grounding
RAG integration with your product docs, FAQs, and support manuals so the AI always responds from verified information — no hallucinated product specs or policies.
CRM & Helpdesk Integration
Native integrations with Salesforce, HubSpot, Zendesk, Intercom, and Freshdesk. Conversations are logged, leads are created, and tickets are raised automatically.
Analytics & Improvement Loop
Conversation analytics dashboard tracking resolution rate, satisfaction scores, and drop-off points — with a feedback pipeline that turns flagged conversations into training data.
A Process Built for Clarity
No black boxes. No surprise invoices. Every project at Codewingz follows a disciplined four-phase process designed to reduce risk and maximise value at every stage.
Conversation Design
We map your most frequent conversation types, define persona and tone guidelines, and produce conversation flow diagrams for all primary use cases and edge cases.
Knowledge Ingestion
Your product documentation, FAQ content, and support history is processed into a vector knowledge base. We identify gaps and recommend content additions.
LLM Configuration & Prompting
System prompt engineering, guardrails configuration, persona calibration, and response templating for on-brand, accurate outputs across all conversation types.
Integration Build
API connections to your CRM, helpdesk, booking system, or e-commerce platform. Handoff mechanics to human agents with full conversation context transfer.
Quality Testing
Adversarial testing with real customer query variations. Measurement against resolution rate, accuracy, and tone benchmarks. Red-teaming for brand safety.
Deployment & Iteration
Live deployment with conversation monitoring. Weekly review of flagged interactions and monthly model/prompt updates based on analytics.
The Tech Stack
We select technologies based on performance, scalability, and long-term maintainability, not trends.
Deepgram
The fastest, most accurate speech-to-text API.
ElevenLabs
The most realistic AI speech software.
Twilio
Cloud communications platform as a service.
Retell AI
Infrastructure for ultra-fast voice agents.
Next.js
The React framework for the web.
Pinecone
The vector database for LLMs.
Real-World Impact
EduPath Learning
The Challenge
“An online learning platform with 80,000 students was spending 40% of their support team's time answering repetitive questions about course access, certification timelines, and refund policies. Response times averaged 6 hours, leading to student frustration and churn.”
The Solution
We deployed an LLM-powered support agent with RAG grounding across 2,400 knowledge base articles and integration with their LMS API (to check enrollment status and progress in real time). The agent handles chat on their web app and WhatsApp, with a seamless handoff to human support for billing disputes and technical issues.
Key Performance Indicators
Common Inquiries
Everything you need to know about our specialized services.
What Are Your Customers Asking Most?
Share your top 10 support queries and we will scope a conversational AI that resolves them — faster, at scale, and on brand.