Production Planning Agent
How an AI agent helped an aerosol packaging factory make production decisions in seconds — right from Telegram.
Client: Aerosol Factory →
Client
Aerosol Factory is a Russian manufacturer of aerosol tin packaging and ready-to-use aerosol products. The facility is located in Vladimir Oblast in a special economic zone, 90 km from Moscow.
Full production cycle: formula development, contract filling, testing and certification. Their own OKKE brands cover automotive care, household chemicals and disinfectants. Minimum production run: 10,000 units.
Vladimir Oblast, SEZ
10,000 units
Full — from formula to finished product
OKKE AUTO, OKKE PROF, OKKE SANI
Challenge
Warehouse stock, current orders and product specs were stored in different places. Making one production decision required manually gathering information from multiple sources.
Before answering "how much should we produce", the planner had to check several spreadsheets and systems. This slowed down operational decisions.
Different roles — sales manager, technologist, procurement — accessed data differently. There was no single tool that could understand a request in natural language.
Solution
We built an AI planning agent accessible directly from Telegram. The agent is connected to production data through a set of tools: product catalog, warehouse inventory, current orders.
The planner writes a request in natural language — for example, "How many units of product X should we schedule for production?". The agent queries relevant data, analyses the situation and returns a specific recommendation.
The workflow is orchestrated through n8n: receive message from Telegram, call LLM, call data tools, form a response, send it back to the chat.
Demo
Telegram — planner interface
n8n — workflow orchestration
Result
A production volume recommendation is generated instantly — the agent gathers the required data from different sources on its own.
No system training required. The planner communicates with the agent the same way as with a colleague — in Telegram, in a familiar interface.
The prototype passed response quality evaluation. The agent is ready to connect to real data channels and industrial use.
Stack
Interface for the planner — familiar messenger, no additional tools needed
Orchestration of the entire workflow: receive request, call LLM, data tools, response
Reasoning engine: understanding the request, selecting tools, synthesising the recommendation
Access to product catalog, warehouse inventory and current orders
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