4–8 weeks
Customer Support AI
Deploy AI that handles support volume without sacrificing quality—with clear escalation paths and human oversight.
What You Get
Outcomes
Tangible results you can expect from this engagement.
Deliverables
What's Included
Concrete outputs you receive at the end of the engagement.
- 1 Support workflow analysis and automation opportunity map
- 2 AI support agent with knowledge base integration and escalation logic
- 3 Internal knowledge assistant for human agents
- 4 Quality monitoring dashboard with accuracy and satisfaction metrics
- 5 Escalation rules engine and human handoff procedures
Who It's For
Recommended For
Measurement
Success Metrics
How we track and prove the impact of this engagement.
The Support Scaling Problem
Support teams face a familiar bind: ticket volume grows, but headcount budgets don’t grow proportionally. The typical response—more templates, faster triage, longer queues—improves efficiency at the margin but doesn’t change the fundamental math. When 60-70% of your tickets are variations on the same 50 questions, your skilled agents are spending most of their time on work that doesn’t require their expertise.
AI support changes this equation—when it’s built right. The qualifier matters. Poorly deployed support AI creates new problems: wrong answers that erode trust, frustrated customers trapped in bot loops, and agents who don’t trust the system enough to let it help.
We build support AI that handles routine volume reliably, escalates intelligently when it should, and gives your human agents better tools for the complex work that remains.
What We Build
Customer-facing AI support. The front line handles common questions—account inquiries, product information, standard troubleshooting, order status—with responses grounded in your actual documentation. Every response includes confidence scoring. When the system isn’t sure, it says so and routes to a human. Customers always have a clear path to a person.
Internal knowledge assistant. For human agents, we build an assistant that surfaces relevant documentation, suggests responses, and provides context from previous interactions. This reduces the time agents spend searching and copying, even for complex tickets the AI wouldn’t handle alone.
Quality monitoring. We build a scoring framework that continuously samples AI interactions and measures accuracy, helpfulness, and tone. This isn’t just a dashboard—it’s a feedback loop that identifies degradation early and flags knowledge gaps for your content team to address.
How Escalation Works
The escalation design is where most support AI fails. Either it escalates too much (defeating the purpose) or too little (causing bad experiences). We calibrate escalation thresholds based on your actual ticket data and adjust them over the first few weeks of operation.
When the AI escalates, it doesn’t just hand off—it transfers the full conversation context, its assessment of the issue, and the relevant documentation it found. The human agent starts with more context than a typical cold transfer, not less. Over time, we use escalation patterns to improve the AI’s capabilities and identify content gaps.
Measuring What Matters
We don’t measure success by deflection rate alone. A high deflection rate with poor satisfaction is a failure. We track a balanced scorecard: resolution rate, accuracy, customer satisfaction, escalation quality, and agent productivity. The goal is a system that customers are willing to use because it actually helps, not because they can’t find the button for a human.
Most clients see measurable impact within the first month of deployment—typically a 30-50% reduction in routine ticket handling time, with satisfaction scores for AI-handled interactions within 5 points of human-handled ones. The gap usually closes further as the system learns from escalation patterns and knowledge base updates.
Risk Management
Risks & Mitigations
We plan for what can go wrong so you don't have to.
AI gives incorrect answers that damage customer trust
We implement confidence thresholds, source-grounded responses, and a quality review loop. Low-confidence responses route to humans. High-confidence responses are sampled and scored regularly to catch drift.
Customers frustrated by inability to reach a human
Every interaction includes a clear, easy path to a human agent. We design the escalation to feel seamless, not like a penalty. The AI transfers full conversation context so the customer doesn't repeat themselves.
Support knowledge base becomes outdated, degrading answer quality
We build feedback loops that flag knowledge gaps—when the AI can't answer or agents override its suggestions, those gaps feed into a content update queue with priority scoring.
Architecture
System Architecture
FAQ
Frequently Asked Questions
Will this replace our support team?
No. It handles the routine questions that consume agent time—password resets, order status, standard troubleshooting. Your team focuses on the complex issues that need human judgment, empathy, and creative problem-solving. Most clients see their agents handling fewer but more meaningful interactions.
How does the AI know about our products and policies?
We integrate the AI with your existing knowledge base, help center content, and internal documentation. Responses are grounded in your actual content with source citations, not generated from general training data. If you need knowledge system work first, our Data & Knowledge Systems engagement can prepare the foundation.
What channels does this work with?
Email, chat (web and in-app), SMS, and most ticketing systems including Zendesk, Intercom, Freshdesk, and ServiceNow. We integrate with your existing tools rather than replacing them.
How do you measure if the AI is actually helping?
We track resolution rate, accuracy (sampled and scored), customer satisfaction for AI-handled interactions, escalation patterns, and time savings. You get a dashboard that shows exactly where the AI is adding value and where it needs improvement.
Ready to get started?
Let's scope a customer support ai engagement for your team. 30-minute call, no pitch deck.
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