75% of L1 tickets auto-resolved, knowledge base gaps detected weekly, L2 tickets routed with full context in under 30 seconds.
You are a SaaS founder at $1M-$10M ARR, and support is eating your team alive. Ticket volume scales faster than revenue, every new feature ships new questions, every integration adds a new failure mode, and every pricing tier creates billing confusion.
You hired a support manager at $55-65K/year, but they spend 60% of their time on password resets, "how do I export my data" questions, and billing inquiries that follow the same script every time. The real cost is not the salary. It is the opportunity cost of your best support people doing data entry instead of relationship building. When a $500K/year enterprise account files a critical bug report, it is behind 14 password reset tickets in the queue. By the time a human gets to it, the customer has already emailed your CEO directly, and now it is a fire drill instead of a routine fix.
Knowledge base decay makes it worse. Your docs go stale within two weeks of a product update, so customers learn to skip them and go straight to support. Your support team writes the same answer 30 times a month, but those answers never make it back into the help center because the feedback loop is manual and nobody owns it. You are paying $55K/year for someone to re-answer questions your docs should handle.
Alex is your AI Support Lead. He auto-resolves 75% of L1 tickets, how-to questions, billing inquiries, password resets, with answers grounded in your actual knowledge base, not hallucinated. Complex tickets get routed to your human team with full context: customer plan, recent actions, error logs, and a suggested investigation path. Every week, Alex surfaces the top 10 recurring questions that your help center does not answer, and drafts the articles to fill those gaps.
That is why you need Alex.
Each step is automated. Alex only escalates when human judgment is required.
Alex classifies the ticket by topic, urgency, and account tier (free, pro, enterprise). For L1 queries (how-to, billing, password reset), Alex composes a response grounded in the knowledge base and the customer’s specific configuration, then resolves the ticket.
Alex extracts reproduction steps, browser/OS details, error logs, and account context, then routes to the appropriate human specialist with a structured brief and suggested investigation path.
Alex re-classifies the ticket, gathers additional diagnostic information, and escalates to a human agent with the full conversation history and a note explaining why the initial response failed.
Alex clusters the past week’s tickets by topic, identifies the top 10 questions that lack help center articles or have outdated answers, and drafts new or updated articles for your team to review.
Alex immediately flags the conversation and routes to the appropriate human specialist without attempting resolution. Cancellation requests go to the founder with full account context and churn risk score.
Alex sends a Slack digest: total tickets handled, auto-resolution rate, average response time, escalations by category, and any enterprise account tickets that need founder attention.
Clear boundaries. Alex works autonomously within defined limits and escalates everything else.
Alex connects to the platforms you already use. No new software to learn.
Alex is deployed gradually with measurable checkpoints at every stage.
Monitoring mode first, then gradual rollout.
Pilot begins with a single ticket category: password resets and account access, to establish baseline accuracy. Weeks 2-3 expand to billing FAQ and feature how-to queries.
Full validation before production deployment.
These AI employees share data and coordinate with Alex to cover your full operation.