AI-Powered Solutions · Conversational AI
AI agents built for your customers, your language, your systems.
We build custom conversational AI agents scoped to your specific query types — integrated with your CRM, knowledge base, and backend systems, and trained on your products and policies.
Our capabilities
Four types of conversational AI engagement.
Customer-facing query agents
LLM-powered agents trained on your product documentation, FAQs, and policies. Handle high-volume inbound queries across web chat, WhatsApp, Telegram, and voice IVR.
- Product and service enquiries
- Appointment booking and rescheduling
- Order status and tracking
- First-level complaint triage
Internal knowledge agents
RAG-powered agents that let your staff query internal documentation, SOPs, HR policies, and compliance materials in natural language — reducing search time and human escalations.
- Leave balance and policy queries
- IT password resets and access requests
- Procurement status queries
- Onboarding guidance for new staff
Voicebots
Custom speech-to-text and TTS pipelines with natural language understanding — built for phone-based customer service, automated intake, and guided workflows.
- Replace rigid DTMF IVR menus
- Natural language query resolution
- Automated intake and triage
- Seamless human handoff
Autonomous agents
Multi-step agents that plan, reason, and execute tasks across your systems — from order processing and document routing to multi-system lookups and approval workflows.
- Multi-system lookups and actions
- Approval workflow automation
- Document routing and processing
- Intelligent escalation with full context
Our process
From assessment to live agent.
Query Analysis
We analyse your inbound query data — email, chat logs, call recordings — to identify the high-volume, automatable queries that should be handled by the agent.
Agent Design
We design the conversation flows, define the escalation logic, and agree on tone of voice — aligned with your brand and the expectations of your customer base.
Integration & Training
We integrate with your knowledge base, CRM, and backend systems. We train the model on your specific products, policies, and terminology.
Pilot Deployment
We launch with a controlled user group — monitoring resolution rates, escalation reasons, and customer feedback closely before full rollout.
Ongoing Optimisation
Post-launch, we review performance monthly, add new query types, and refine the model based on real conversation data. The agent gets measurably better over time.
MLOps included
Your AI investment should get better over time — not silently degrade.
A conversational AI agent is not a set-and-forget deployment. Customer language evolves, your products change, and edge cases emerge. We build monitoring into every agent — tracking resolution rates, escalation patterns, and model drift.
- Resolution rate and escalation tracking
- Hallucination and out-of-scope flagging
- Customer satisfaction monitoring
- Model drift detection
- Scheduled retraining and knowledge base updates
Let's look at your inbound query volume.
Share your support channel data and we'll tell you what percentage of it can be automated — and what the ROI looks like.