Transform customer support with intelligent AI agents that handle routine inquiries, reduce ticket volume by 60%, and free your team to focus on complex issues that require human expertise.
Customer-facing organizations overwhelmed by support tickets, struggling with long response times, or experiencing agent burnout. Ideal for B2C companies, SaaS businesses, healthcare providers, retail, and any organization with high-volume customer inquiries.
60% fewer L1 tickets
AI agents handle routine inquiries automatically, freeing human agents for complex issues
30-50% improvement
AI agents provide instant, accurate answers, resolving issues on first contact
40-60% reduction
Faster resolution times as AI handles routine queries and agents focus on complex cases
15-25% CSAT increase
Faster response times and 24/7 availability improve customer experience
Intelligent chatbots with natural language understanding, intent classification, and conversational flows. Trained on your ticket history and knowledge base for accurate, context-aware responses
Intelligent escalation to human agents when AI reaches limits, with context handoff and priority routing. Seamless transition from AI to human without customer friction
Integration with your existing knowledge base, FAQs, and documentation. AI agents retrieve and synthesize information from multiple sources to provide comprehensive answers
Deploy across web chat, mobile apps, email, SMS, and social media. Consistent experience across all channels with unified conversation history
Real-time dashboards tracking resolution rates, customer satisfaction, escalation patterns, and AI performance. Insights to continuously improve chatbot responses
We analyze your ticket history to identify common inquiry types, review your knowledge base, and interview support agents. We design conversation flows, define escalation rules, and map intents to responses. We identify which inquiries AI can handle vs. those requiring human agents.
We build the chatbot system, train AI models on your ticket history and knowledge base, configure intent classification, and set up escalation workflows. We integrate with your support platform (Zendesk, ServiceNow, Salesforce) and test conversation flows with real scenarios.
We deploy the chatbot, train your team on monitoring and optimization, and launch with a pilot group. We monitor performance, gather feedback, and continuously improve responses based on real conversations. We refine escalation rules and expand AI capabilities over time.
6-8 weeks
From analysis through deployment and initial optimization
2-4 hours/week
Stakeholder interviews, ticket analysis, knowledge base review, conversation flow validation, and user acceptance testing
Timeline factors:
$35,000 - $100,000 setup + retainer
Project-based pricing for implementation, with optional monthly managed service ($3K-$8K/month) for ongoing optimization, content updates, and performance monitoring.
Our customer support modernization directly impacts support operations and customer experience metrics.
First-contact resolution rate (%)
Average handle time (minutes)
Customer satisfaction (CSAT)
Net Promoter Score (NPS)
Ticket backlog (#)
Ticket volume (#/month)
Agent utilization rate (%)
Response time (minutes)
Escalation rate (%)
Cost per ticket ($)
Customer effort score (CES)
Agent satisfaction score
We use modern AI platforms and integrate with your existing support infrastructure. Our approach is flexible—we select the best-fit solution for your environment.
Risk: AI provides incorrect answers, sounds robotic, or frustrates customers, leading to poor experience and increased escalations
Safeguard: We train AI on your actual ticket history and knowledge base for accurate, context-aware responses. We implement confidence thresholds—when AI is uncertain, it escalates to humans. We use LLMs fine-tuned for customer service with guardrails to prevent hallucinations. We continuously monitor and improve based on customer feedback and escalation patterns.
Risk: When AI escalates to humans, context is lost, forcing customers to repeat information and creating frustration
Safeguard: We design seamless escalation workflows with full context handoff. Human agents receive complete conversation history, customer information, and AI's analysis. We use warm handoffs (agent joins conversation) rather than cold transfers. We ensure escalation is smooth and transparent to customers.
Risk: Support agents resist AI, fear job loss, or don't trust the system, leading to poor adoption and manual workarounds
Safeguard: We position AI as a tool that frees agents from repetitive work to focus on complex, high-value interactions. We involve agents in design and training. We provide clear communication about how AI enhances their role. We measure and celebrate wins (reduced ticket volume, improved CSAT) to build trust. We offer Service #9 (Change Management) to support adoption.
Challenge: Fast-growing SaaS company with 50K+ customers was receiving 2,000+ support tickets per week. Support team of 15 was overwhelmed, average response time was 8 hours, and CSAT was declining. 70% of tickets were routine questions (password resets, feature questions, billing inquiries) that agents answered repeatedly.
Solution: Deployed AI chatbot trained on 6 months of ticket history and product documentation. Handled L1 inquiries (password resets, feature questions, billing) with 85% accuracy. Integrated with Zendesk for seamless escalation. Deployed across web chat and mobile app.
Impact: Reduced ticket volume by 65% (from 2,000 to 700 per week). Improved average response time from 8 hours to 2 minutes for AI-handled inquiries. Increased CSAT from 72% to 88%. Freed agents to focus on complex technical issues, improving resolution time for those by 40%. ROI: $450K annual savings from reduced support costs.
Challenge: Large healthcare system with 200K+ patients received 5,000+ patient inquiries per week via phone and email. Call center was overwhelmed, patients waited 15+ minutes on hold, and appointment scheduling was inefficient. High agent turnover due to burnout from repetitive questions.
Solution: Implemented AI chatbot for patient inquiries (appointment scheduling, prescription refills, insurance questions, general health information). Integrated with Epic EHR for appointment booking and patient records. Deployed across web portal, mobile app, and SMS.
Impact: Reduced call volume by 55%, eliminating hold times. Improved first-contact resolution from 45% to 78%. Increased patient satisfaction (CSAT) from 68% to 85%. Reduced agent turnover by 30% as agents focused on complex patient needs. Enabled 24/7 patient support. ROI: $600K annual savings plus improved patient experience.
Older chatbots used rule-based systems that required exact keyword matches and couldn't understand context. Our AI uses large language models (LLMs) trained on your actual ticket history, so it understands natural language, context, and intent. It sounds human, handles variations in how customers ask questions, and learns from conversations. We also ensure seamless escalation to humans when needed, so customers never feel trapped.
Typically, AI handles 60-70% of L1 inquiries (routine questions like password resets, feature questions, billing, FAQs). The remaining 30-40% require human agents (complex technical issues, emotional situations, escalations). We analyze your ticket history to identify which inquiries AI can handle, and we start conservatively—AI only handles inquiries it's confident about, then we expand as it improves. We also track escalation rates and continuously optimize.
We train AI on your actual ticket history and knowledge base, so it learns from real customer interactions and your documented answers. We implement confidence thresholds—if AI is uncertain, it escalates to humans. We use retrieval-augmented generation (RAG) to ground responses in your knowledge base. We continuously monitor accuracy, track escalation patterns, and improve based on feedback. We also implement guardrails to prevent hallucinations and ensure AI stays within its knowledge domain.
We design seamless escalation workflows. When AI reaches its limits (uncertainty, complex issue, customer requests human), it smoothly transfers to a human agent with full context—conversation history, customer information, and AI's analysis. The agent joins the conversation (warm handoff) so the customer doesn't have to repeat information. We also provide AI-assisted responses to agents, suggesting answers based on similar past tickets.
No—AI augments your team, not replaces it. AI handles repetitive, routine inquiries that agents find tedious, freeing agents to focus on complex, high-value interactions that require human empathy and problem-solving. Most clients see agents become more satisfied as they work on interesting challenges rather than answering the same questions repeatedly. We position this as enabling agents to do their best work, not eliminating jobs.
You'll see working prototypes within 4-6 weeks, and full deployment takes 6-8 weeks. Most clients see 40-50% ticket reduction within the first month as AI handles routine inquiries. We start with a pilot (specific inquiry types or channels) to validate, then expand. We continuously optimize based on real conversations, so performance improves over time. Full impact (60%+ ticket reduction) typically achieved within 2-3 months.
Yes, we integrate with all major support platforms. The AI chatbot works alongside your existing ticketing system—it can create tickets, update tickets, retrieve ticket information, and escalate to agents within your platform. We ensure seamless integration so agents see AI conversations in their normal workflow. We can also integrate with your CRM, knowledge base, and other systems for a unified experience.
Let's discuss your support challenges and explore how AI agents can handle routine inquiries while your team focuses on what matters most.
Build a better knowledge base with semantic search so AI agents and human agents can find answers instantly. Perfect complement to support modernization.
Track support performance metrics, CSAT, resolution rates, and AI chatbot performance in real-time dashboards.
Last updated: November 2025