Connect your ticketing systems, upload technical documentation, configure diagnostic routing rules, and go live.
Native two-way integrations with Zendesk, Freshdesk, Jira Service Management, Intercom, and Salesforce Service Cloud.
Upload API manuals, SDK guides, error code resolution tables, and engineering knowledge base docs for semantic search.
Define priority classification (P1 to P4), team assignment rules, and SLA warning notifications in plain English.
Choose a clear, analytical, step-by-step diagnostic tone and enable automatic translation across 100+ native languages.
Embed the chat widget in your SaaS web app, portal, or site to start deflecting support tickets 24/7.
An AI customer support chatbot is a specialized conversational AI agent engineered to handle the technical, issue-resolution side of the customer experience. Where customer service focuses on sales and proactive care, customer support is reactive and diagnostic — it steps in when something is broken, confusing, or needs expert intervention, and works to resolve the issue as fast as possible.
A modern AI customer support chatbot goes far beyond simple FAQ responses. It performs multi-step technical troubleshooting — walking users through diagnostic checks, parsing error codes against your documentation, and suggesting precise fix steps. When the issue requires human expertise, the AI automatically creates a structured helpdesk ticket, classifies its priority (P1 urgent through P4 low), routes it to the correct engineering team, and tracks SLA deadlines to prevent contract breaches.
The backbone of an AI support chatbot is Retrieval-Augmented Generation (RAG) — a semantic search layer that indexes your API documentation, SDK manuals, error code databases, and internal knowledge bases. This enables the AI to ground every response in your actual technical documentation, not guesswork. If your business needs help with sales inquiries, order tracking, returns, and CSAT management, see our AI Customer Service Chatbot.
Built specifically for helpdesk management, diagnostic resolution, ticket routing, and engineering team productivity.
Walks users through step-by-step diagnostic workflows, parses error logs, and recommends fix steps instantly.
Auto-creates structured helpdesk tickets in Zendesk, Freshdesk, or Jira with full diagnostic context and user metadata.
Classifies issue priority (P1–P4) and routes tickets to specialized engineering or support tiers based on urgency.
Indexes developer documentation, SDK guides, and help articles using RAG to deliver accurate, citation-backed answers.
Tracks response and resolution countdown timers against enterprise SLA tiers to ensure zero contract breaches.
Passes high-complexity cases seamlessly to on-call support engineers along with clean, summarized chat transcripts.
Verifies if the user's issue is resolved, logs root causes, and closes helpdesk tickets automatically upon user confirmation.
Provides real-time reports on Mean Time to Resolution (MTTR), deflection rates, SLA compliance %, and top error trends.
Dedicated technical support workflows configured to meet high-volume helpdesk demands.
Resolve webhook failures, authentication errors, SDK bugs, and API rate limit inquiries automatically.
Automate VPN resets, software license provisioning, SSO authentication, and workstation troubleshooting.
Guide customers through firmware updates, WiFi pair configuration, hardware resets, and warranty RMA claims.
Provide instant outage status reports, eSIM activation steps, and router configuration guidance around the clock.
Assist clinical staff with Electronic Health Record (EHR) login resets, medical device sync, and compliance logging.
Triage security alerts, assist with SSL certificate renewals, firewall configurations, and P1 incident logging.
Customer support is reactive and technical — it kicks in when users encounter errors, need diagnostics, or require escalation to engineering. Here's how it compares to customer service.
Reactive, issue-resolution focused — built for technical troubleshooting, helpdesk management, and engineering team productivity.
Proactive, experience-driven care — focused on sales assistance, order management, and building long-term customer loyalty.
Looking for an AI chatbot focused on sales assistance, order tracking, returns processing, and customer satisfaction? Our AI Customer Service Chatbot is built for front-office customer care teams.
Explore AI Customer Service ChatbotMonitor active technical tickets, SLA countdowns, routing queues, diagnostic logs, and support analytics in real time.
Flat-rate monthly plans with zero per-ticket fees, zero setup fees, and cancel anytime flexibility.
Ideal for growing SaaS apps and technical helpdesks automating ticket deflection.
For engineering teams and scaling technical helpdesks enforcing SLAs.
For large tech enterprises requiring custom SLA guarantees, Jira APIs, and dedicated success managers.
Everything you need to know about setting up and running an AI chatbot for technical troubleshooting, ticket routing, and SLA management.
Follow a technical issue from first error report through AI diagnosis, ticket creation, engineering escalation, SLA tracking, and verified resolution.
A developer reports: "Getting HTTP 500 on POST /v2/webhooks after upgrading to SDK v3.1." The AI immediately begins a structured diagnostic workflow, asking for error logs and environment details.
The AI searches the SDK v3.1 migration guide via RAG and identifies a breaking change: the webhook payload signature algorithm changed from HMAC-SHA1 to HMAC-SHA256. It provides the exact code fix with a documentation link.
The developer confirms the fix didn't work — a deeper issue exists. The AI creates a P2 ticket in Jira Service Management with full diagnostic context and routes it to the Backend API team with a 4-hour SLA.
The AI monitors the SLA countdown, sends a 30-minute warning to the on-call engineer via Slack, and hands off the full conversation transcript with parsed error logs for immediate investigation.
The engineer pushes a hotfix. The AI follows up with the developer to verify resolution, logs the root cause as "SDK migration regression," and auto-closes the Jira ticket — all within the 4-hour SLA window.
Deliver 24/7 technical troubleshooting, eliminate SLA breaches, automate ticket routing, and empower your engineering team.