The Kazakhstan-based developer tested a multi-agent system on its own tasks. The company now offers corporate process audits to businesses based on its use cases.
What happened
Rocket Tech has handed over a significant portion of its operational tasks to a multi-agent AI system. According to a case study published on its corporate blog on July 15, 2026, neural networks have taken over up to 80% of routine work in marketing, research, and management.
Instead of integrating disparate external services, the vendor created a unified digital environment. According to the company’s own data, this has freed up senior specialists’ time to focus on complex architectural and strategic tasks.
How the internal AI ecosystem works
The company detailed the mechanics of five key products that now support the team’s operations.
- Development: The autonomous AI engineer, Unit, functions as a middle-level developer. The system is integrated into the codebase and task trackers: it independently requests access, takes tasks from the backlog, writes production code, and conducts initial reviews.
- Corporate memory: The Tacit Knowledge Management platform automatically analyzes work communications in chats and on calls, saving important decisions in a unified database. According to the vendor, this solves the problem of lost agreements and accelerates the onboarding of new employees.
- Hiring: The Rocket Hunt Telegram bot collects applications, and built-in AI instantly conducts initial candidate scoring. Recruiters receive a filtered shortlist.
- Research: The Product Insight Lab pipeline automates user data collection. The system selects the research format, transcribes interviews, and generates reports using a database of AI personas.
- Content: Material production has been handed over to a full-cycle AI editorial team. The multi-agent system manages the process from finding a news hook to publication, while the human role is reduced to editor-in-chief functions.
Country and market
Rocket Tech has been operating in the market since 2011, specializing in business application development, with a presence in Kazakhstan and Uzbekistan. The publication of a detailed internal case study indicates a shift in the company’s positioning.
Previously, Finteqstan reported that fear of technology prevents Kazakhstanis from trusting AI assistants. At the corporate level, IT companies are trying to overcome this barrier through measurable efficiency and by demonstrating their own working tools.
The vendor is directly offering businesses the opportunity to audit their processes and develop similar solutions tailored to specific client needs.
What’s next
For the Central Asian market, the publication of such case studies marks a transition from testing external chatbots to creating integrated corporate systems. Companies are beginning to look for solutions capable of securely working with closed codebases, internal documents, and task trackers.
IT vendors are starting to use internal AI experiments as a showcase to sell deep corporate process automation services.
The future development of this trend will depend on how applicable these ready-made AI ecosystems, created by developers for themselves, prove to be for the specific needs of companies in the traditional real sector.