ReplyWise : AI Chatbot Platform
Summary
We built ReplyWise, a chat tool for business teams. It helps companies handle customer messages on their site, in apps, and on messaging platforms. Teams can do this without hiring more support staff.
The bot can pick up what a customer means and reply with help from the company's own knowledge base. It can also do other tasks, like taking a reservation or looking up an order. If a case needs a person, it can pass the chat to a human agent.
The platform combines:
The objective was to have a single place where businesses can:
Admin Dashboard
A central control panel that allows you to control all your chatbots and conversations within a single point.
- Setting up and managing chatbots and their personalities
- Chatbot setup and persona controls
- Live conversation monitoring
- Knowledge base management
- Agent handoff rules
- Performance analytics
Core Features Implemented
A breakdown of the core components built and delivered for this project.
Conversational AI Engine
A conversational chatbot that is able to remember context and hold a natural multi-turn conversation.
- Identifying intents and entities
- Context-aware follow-up questions
- Custom tone and brand voice
- Receiving support for ambiguous requests
- Sentences are kept on-topic with guardrails
Knowledge Base Assistant (RAG)
The company's own content is used for the responses, not guessing.
- Consumes PDFs, assistance articles, FAQs, and web pages
- Collects most pertinent parts of each question
- Produces responses based on agreed-upon resources
- Uses sources as appropriate
- Content will be automatically updated when it changes
Omnichannel Deployment
A chatbot that's deployed where customers already are.
- Website chat widget
- WhatsApp and SMS
- Facebook Messenger and Instagram
- In-app mobile chat
Smart Handoff & Lead Capture
The bot is able to know when to back off and when to sell.
- Escalates to a live agent when frustrated, when issues are more complex or on request
- Passes context of an entire conversation to the agent
- Records contact information and filters leads in chat
- Schedules appointments in calendar
- Syncs leads and tickets to CRM and Help Desk tools
Conversation Analytics Dashboard
Live analytics of the chatbot's performance.
- Resolution and deflection rates of the work and its consequences
- Key questions and gaps in content areas
- Customer satisfaction scores
- Handoff reasons, agent workload
- Lead conversion tracking
Execution Roadmap
Discovery & Strategy
Identified the most frequent support inquiries, analyzed help content and chat logs, established support metrics, and selected channels and integrations for a launch.
Core Development
Developed the chatbot engine, knowledge ingestion pipeline, Admin dashboard and first channel integrations.
Advanced AI Features
Incorporated retrieval tuning, multilingual editing and sentiment detection, live agent handoff and CRM and helpdesk syncing.
Optimization & Deployment
Real-world conversation testing, updated prompts and guardrails, faster responses, and deployed with monitoring.
Key Outcomes & Impact
24 hours a day, faster first response times
Use of predictive and proactive capabilities to anticipate customer needs
More qualified leads captured from conversations
Answers that are consistent and accurate in all channels
Reduces support expenses with increased volume
Identify information about customer needs and missing information content
Our support queue is not so busy, our response time is a lot quicker and our customers feel the difference. Markeltree built a chatbot that actually understands our customers. It has the ability to answer the simple questions by itself and pass the complex ones on with all the context.
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What our customers say
Markeltree’s AI solutions helped us optimize our data workflows and decision-making process. Their team clearly understood our objectives and delivered a practical, results-driven AI implementation.
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