01 · AI Support Architecture
OpenClaw + AI-IDE
We build a stack where the agent has access to the product, documentation and API.
OpenClaw · Claude Code · Support · Automation
AI technical support agent
A mix of OpenClaw and an AI IDE (Claude Code) that handles basic support tasks: from answering users to automatically configuring the product.
3 modulesOnline / OfflineSupport / Tech Leads
Our clients
Clients and partners
Tech support is drowning in routine. The OpenClaw + AI-IDE combo turns it into an AI employee that not only answers but acts.
What you get
Key Takeaways
- Deploy an AI agent on the OpenClaw + Claude Code stack
- Set up automatic knowledge-base updates
- Teach the agent to act, not just answer
- Deploy proactive monitoring
- Connect the agent to your existing stack via API
- Set up feature request detection
- Implement escalation with full context
- Learn to calculate ROI: $0.02–0.10 per ticket versus $15–25
- Build an architecture where the agent works 24/7
Program
Workshop Program
02 · First-Line Automation
We close 80% of tickets
The agent answers users, updates documentation and configures the product automatically.
03 · Proactive Support
Monitoring and escalation
Proactive monitoring, feature-request detection and escalation with full context.
Schedule
Upcoming Dates
June 12Friday, 14:00 MSKRUB 20,000 / person
June 19Friday, 14:00 MSKRUB 20,000 / person
June 26Friday, 14:00 MSKRUB 20,000 / person
More
Other Workshops
Mission 01
Accelerating development of large projects with AI
How to stop drowning in legacy and start delivering value faster.
Mission 02
Accelerating the entire development cycle (Time-To-Use) with AI
From "AI as a chatbot" to "AI as an engineering accelerator" — integrating AI into the TTU methodology.
Mission 03
A personal AI assistant with OpenClaw
From zero to a digital worker in 2 hours — self-hosted, multichannel, zero routine.
Discuss the AI workshop
Let's learn
Choose a workshop and come with a real process
First we solve the practical task, then we show how it was assembled so the team can repeat the approach safely and independently.
Related Cases
AI ingredient recognition by barcode
- Processing sped up from 30 minutes to 2 per batch of 10 images
- Recognition accuracy for composition is 80-95%
OSNO-VA: AI accountant
- Built an AI platform
AI SDLC loop for Fix Price
Learn moreRelated solutions
Articles on the topic
- Ponytail, Caveman, and RTK: three layers of token savings in AI development
- Developer and PM estimate: L10-L60, workflow and AI
- Pricing Automation in E-commerce: How to Choose Tools Without Giving Pricing to a Black Box
- Karpathy's Lens: Understanding vs. Execution
- How we cut token costs without losing quality
