TechForward – Automated Customer Support

Reduced customer support response time by 85% with an AI agent. The system instantly resolves common tickets, freeing up the support team for complex cases.

The Challenge

TechForward runs a tech community on Circle.so platform with 5000+ members – developers and no-code enthusiasts. Every day, 30-50 technical tickets arrived (questions, problems, bugs) across different categories:

  • N8N (automation)
  • Make.com
  • RelevanceAI
  • Other no-code/low-code tools

Main Problems:

Delayed Response and Lack of Prioritization The support team (2-3 people) couldn’t keep up with responses. First response time was 4-8 hours, and on weekends even 24h. All tickets went to one list – critical bugs got lost among simple questions. Users didn’t know if their problem was being resolved, leading to frustration and repeated submissions.

Repetitive Questions Without Knowledge Base ~40% of tickets concerned the same problems. The team wasted time writing similar responses instead of creating systematic solutions. Lack of centralized knowledge base meant every question was treated as new.

Impossible Scalability Hiring additional support would cost $1,500-2,000/month. The community was growing 20% monthly (from 5000+ to potentially 10,000+ in a year), meaning constant need for team expansion. With the current model, maintaining service quality was impossible without drastic cost increases.

The company needed a solution that:

  • Responds immediately to tickets (< 5 minutes)
  • Automatically classifies and prioritizes problems
  • Generates intelligent AI responses based on history
  • Tracks each ticket’s status in real-time
  • Scales without additional personnel costs

The Solution

NexaroAI designed and implemented an intelligent “Tech CRM” system – a fully automated customer support platform that operates 24/7 without interruption.

How does it work?

🤖 Intelligent AI Support Agent The moment a user publishes a question on Circle.so, the system immediately detects it and launches an advanced AI Agent. The Agent searches through the history of similar problems in the community, and if it doesn’t find an answer – it reaches out to external knowledge sources. In less than 3 minutes, the user receives a detailed response with step-by-step instructions, documentation links, and a confidence level for the solution.

📊 Automatic Classification & Prioritization The system doesn’t just respond – it also monitors every ticket in real-time. AI analyzes the discussion under the post and automatically classifies the status: “New”, “Replied”, “Solved”, or “Needs Urgent Attention”. The support team sees live which problems require human intervention and which AI has already handled.

✅ Intelligent Ticket Closure When AI determines a problem has been resolved, it automatically marks the post as “Solved” and informs the user. If someone disagrees with the assessment – they can immediately call a moderator. The system learns from each such interaction, becoming increasingly accurate.

🎯 Central Dashboard The entire process is managed through a transparent dashboard in Airtable, where the team has a view of all tickets, performance metrics, and can quickly intervene in urgent cases.

What does this mean in practice?

Instead of waiting hours for a response, TechForward users receive help instantly. Instead of wasting time on repetitive questions, the support team focuses on truly complex problems. The system scales automatically – whether it’s 50 or 500 tickets daily, AI handles them all with the same speed and quality.

The Results

The company completely transformed its customer support approach. AI Support Agent system took over 70-80% of routine tickets, allowing the team to focus on complex problems and community growth strategy.

Before automation:

  • First response time: 4-8 hours (sometimes 24h+)
  • 30-50 tickets/day handled manually
  • Team: 3 people full-time on support
  • ~40% repetitive questions – wasted time
  • No prioritization system
  • User frustration due to lack of response

After automation:

  • First response time: < 3 minutes (AI Agent)
  • 70-80% of tickets handled automatically
  • Team: 1 person + AI (focus on Urgent/Complex cases)
  • Elimination of repetitive questions – AI responds based on history
  • Automatic classification: New → Replied → Solved / Urgent
  • User satisfaction: +45% in NPS surveys

Additional benefits:

  • Scalable support – AI has no ticket/day limit
  • 24/7 availability – users get response anytime
  • Consistent quality – AI always uses proven solutions
  • Knowledge base – every solution recorded in Airtable
  • Cost savings – ~$3,000/month (2 support positions)

The results in numbers

85% Less
Response time reduction
75% Tickets
handled automatically
24/ 7
AI Availability
<14 Days
Implementation time
CASE STUDY Q&A

Key Project Details

Does AI really answer technical questions well?

Yes! The system uses Google Gemini 2.0 with two tools:

SearchTool searches ticket history in Circle.so – about 60% of questions find answers in the internal base.

Perplexity (external knowledge) searches the internet from credible sources when internal base doesn’t have the answer.

Each response includes a confidence level (High/Medium/Low). In practice, ~75% of AI responses are considered helpful by users, with ~90% accuracy for simple and moderately complex problems.

What happens when AI can't help?

The system has 3-level escalation:

Level 1: AI tries to respond automatically in < 3 minutes.

Level 2: Every 1-2 hours workflow checks status. If problem unsolved > 1 day, changes to “Urgent Resolution”.

Level 3: Team sees urgent tickets in Airtable and intervenes manually.

Importantly – AI learns from each human response. After 3 months, accuracy increased from 70% to 85%.

How does automatic status classification work?

Workflow uses GPT-4o-mini, which analyzes ticket title, description, all comments and time since post creation.

Classification rules:

• “Solved” – problem resolved in comments
• “Not Replied” – no comments
• “Urgent Resolution” – unsolved > 1 day without response
• “Replied” – comments present but problem unsolved < 1 day

Team sees both status and AI justification in Airtable.

Can AI be customized for specific industry/product?

Absolutely! Workflow is fully configurable:

Knowledge Base: Connect any data source (Notion, Google Docs, custom API). SearchTool can search product documentation, FAQ, previous tickets.

AI Customization: Each AI Agent has editable system prompt – customize communication tone, detail level, formatting. Change AI models (Claude, Llama, GPT-4, Mistral).

Integrations: Add industry-specific tools (Jira, GitHub, Slack, HubSpot, Salesforce). System supports 50+ languages with auto-detect.

What are the system's operational costs?

For 1000 tickets monthly:

• Google Gemini 2.0: ~$15-25
• OpenAI GPT-4o-mini: ~$5-10
• Perplexity AI: ~$10-20
• Airtable: $20-50
• n8n hosting: $20-40
• Circle.so API: Free

Total: ~$70-145/month

For comparison: 3 support people = ~$4,500/month. ROI: 30-60x cheaper than human team.

System scales linearly – 2000 tickets = ~$140-290/month, without recruitment, training, vacation costs.

How long does implementation take?

Enterprise Package (Full Custom) – up to 14 days:

Week 1-2: Discovery & Design (process analysis, category mapping, prompt design, infrastructure setup)

Week 2-3: Development & Integration (workflow building, integrations, AI configuration)

Week 3-4: Testing & Training (historical data tests, fine-tuning, team training, beta launch)

Week 4+: Launch & Optimization with weekly check-ins for first 2 months

Standard Package (Fast-Track): Less than 7 days with pre-built templates

What about user data privacy?

GDPR-compliant system:

All data stored in EU-hosted Airtable. Google Gemini and OpenAI GPT-4o-mini operate on Enterprise/Business plans with zero data retention – API calls are not used for model training.

Perplexity is a public search engine without PII storage.

For ultra-sensitive data:

• Self-hosted AI models (LLaMA, Mistral) on own infrastructure
• On-premise n8n instead of cloud
• End-to-end encryption

System has complete logs with ability to anonymize/delete data on request (GDPR Right to be Forgotten).

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