--- title: "AI agents for business in Kazakhstan | Cybernetica" url: "https://cybernetica.kz/en/approach" description: "AI agents for business in Kazakhstan: automating processes with a track record of 100+ projects. Book a process diagnostic and a pilot with results in weeks." --- # Implementing AI agents in real business processes — our approach AI agents for business deliver results faster than a traditional ERP project: an engineer comes to you, understands the process, and the agent ships a solution in days. Business process automation doesn't start with buying licenses — it starts with a conversation about where time and money are really being lost. **Cybernetica by the numbers:** 8 years in the market · 100+ enterprise projects · 60+ clients · 50+ specialists · Resident Astana Hub ## What matters in automation ### Speed decides Customization used to mean hiring a developer or waiting months in a queue. Now an AI agent delivers the task in days — supervised by engineers who check the quality of the result. ### Your data stays with you AI works with your systems, but the data itself never goes anywhere: the model sees only structure, not the content of documents and correspondence. ### The foundation is already there 8 years of our own ETL/DWH infrastructure and ready-made connectors to 1C. No need to build from scratch — we accelerate what you already have. ## How we implement AI agents in business Four steps from talking to an engineer to an agent that works in your systems like an employee. ### 01. An engineer comes to you We work the way Palantir made famous: a Forward Deployed Engineer (FDE) comes to you — an engineer who works at your site, not in our office. For a few days they observe the process and find where work is manual and where time is being lost. **Diagnostics — from a few days** ### 02. We map your business and data The engineer builds a process map and a unified data model: what each department does, where information flows, what's worth automating first. Data stays inside your perimeter — the map is built on top of your systems, nothing is exported anywhere. **Map — in one or two sessions** ### 03. An AI agent delivers the task Based on the map and a task described in words, the agent writes and deploys a solution in days, not months. Engineers review the result — architecture, security, and quality — before showing it to you. **Result — in days** ### 04. The solution runs in your 1C/ERP The finished solution is embedded into your accounting system and workflows. The agent doesn't stay a demo: it keeps working like an employee, and we maintain and update it. **Rollout — from 2–3 weeks** ## Three ways to start Three entry points with different levels of commitment — start small and gradually move toward full implementation. ### Process diagnostic We show, on your own process, exactly where time and money are really being lost — without changing your systems and without long commitments. **Results in a few days** ### Pilot We take one process and bring it to a measurable result, so you know whether it's worth going further. **Results in weeks, not months** ### Fast start with AI We train your team and launch the first tools — a second brain, ready-made agents, BAIqe in demo mode. We deliver a "wow effect" and prepare the team for deeper projects. **AI Enablement — 1–5 days** [Other digitalization tools](/en/products/digitalization) ## The platform: a path from diagnostics to agents Each product is part of one path: from seeing the business clearly to handing routine work over to agents. You can start at any stage. ### 01. See where money is being lost Before changing anything, you need to see how the business really works — not on paper, but in fact. #### Business map A living map of your business that you can update by voice: it shows who does what and where decisions are made by gut feeling. - Built in one or two sessions, not months - Doesn't turn into a file nobody opens - Ready-made context for AI agents and automation - A basis for prioritizing what to automate first #### Process Explorer We measure the real duration of processes from actual data — correspondence, document dates, system logs — not from what's written in the regulations. - Shows exactly where time is lost, not just "roughly somewhere" - Automation priorities based on money, not gut feeling - Example: releasing a product took 45 days — we found where 30 of them were lost - A conversation with management based on numbers, not opinions #### Process cost accounting We calculate the real cost of a contract, project, or process by allocating costs across time and resources. - Shows which contracts are actually profitable and which aren't - Pricing decisions based on data, not intuition - A base for recalculating unit economics - A continuation of Process Explorer: time → money ### 02. Bring order to your data A unified data system is the foundation everything else is built on: from reporting to AI agents. #### 1C and ERP implementation 1C, ERP, and industry solutions tailored to your business — not an off-the-shelf box, but a configuration built for your processes. - Ready-made industry expertise — faster and cheaper than starting from scratch - A unified data foundation for reporting and AI agents - 100+ enterprise projects in the team's track record - The solution is chosen for the industry, not just off the shelf [More about ERP implementation](/en/products/erp) #### Data buses and MDM We connect systems to each other and bring reference data in order — no duplicate counterparties or item records. - AI finds duplicates and suggests merging records - Unified reference data — a must for consolidation and BI - Systems stop being "islands" with data drifting apart - Checks before adding a new record [More about data buses and MDM](/en/products/18-shina-dannyh-1s) #### DWH without leaving the perimeter A single data warehouse for reporting and AI — the model sees only structure, and the data itself never leaves the company's perimeter. - 1,200 transactions per second, a full ERP export in ~2 hours - 0% load on your production 1C — data is read in the background - Critical for banks, subsoil users, and the public sector The data source can be any system, including SAP — we read it as a source, we don't implement it. [More about DWH](/en/products/21-etl-i-hranilishe-dannyh-dwh) ### 03. Plan on numbers Data turns into budgets, plan-vs-actual, and management reporting. #### BI and management reporting Budgeting, consolidation, and management reporting on your own data — without manually reconciling spreadsheets. - Reporting: was 15 days → now 2 hours - Consolidated budget across the group of companies, automatically - Plan-vs-actual and forecasts in real time - Platforms: CasPlan, Anaplan, Optimacros — we prepare the data for them [More about BI and management reporting](/en/products/14-bi-sistemy-i-sistemy-integrirovannogo-planirovaniya) ### 04. Give people simple access The complexity of accounting systems shouldn't be a barrier for employees and clients. #### BAIqe Work with 1C, CRM, and other accounting systems by voice, text, or photo — without learning interfaces. - 150+ ready-made actions out of the box - Data stays inside the perimeter: the LLM sees only structure - Checks for duplicates and math before saving - One window for several systems at once [More about BAIqe](/en/products/53-baiqekz-sozdaem-ai-resheniya-dlya-biznesa) #### Mobile apps and portals Apps and portals for employees, clients, and counterparties built on top of your data — without a large development team. - Auto-updates from the database - Faster and cheaper on a ready-made ecosystem - Counterparties serve themselves - A new channel without hiring a mobile team [More about mobile apps and portals](/en/products/45-mobilnye-prilozheniya-na-baze-1spredpriyatie) ### 05. Hand routine work to AI agents The final stage of the journey: routine work is done by agents, not people. #### Subscription-based customization Customization built on your own system, by subscription — without an in-house developer. Tasks are delivered by agentic development, not old-school hiring. - Customization in hours instead of weeks - A predictable subscription package instead of an hourly estimate - The result stays inside the client's perimeter - Documentation and tests are part of the result #### Automation beyond ERP We automate what ERP doesn't cover: manual data collection, Excel calculations, reports between systems. - The agent collects data on its own, on schedule - The report is always up to date, not dependent on one employee - Results in days, without customizing the ERP itself If you already use Bitrix24, we connect its new AI tools (Vibe) to the data across your entire environment. [More about Bitrix24](/en/products/40-bitriks24) #### Agents in the org structure Agents with skills, access rights, and a reviewer are built into the company like employees — working continuously, not one-off. - A place in the org structure and workflows, not a one-off demo - Rights and business rules are built into the agent - From signal to action — minutes, not days #### Digital employee by subscription A subscription to a ready-made role — "accountant," "analyst," "warehouse operator" — with a set of skills and updates. - Pay for the role-result, not development hours - Ready-made skills from day one - Customization for the company on request - Regular updates at no extra cost ## We applied this approach to our own company We didn't have a clear picture of our own business: project profitability, employee output, and cost were calculated manually — or not at all. Our CFO, who isn't a programmer, used BAIqe and agentic development to build project analytics, cost recalculation, and downtime monitoring with alerts to the management chat in 3 days — without writing a single line of code by hand. Output and profitability multiplied afterward. - **3 days** — to full automation - **0 lines** — of code written by hand - **several times** — higher output and profitability Similar results — with our [clients](/en/clients). ## Why this is safe The main barrier for enterprise isn't technology — it's the risk of a data leak. We solved this at the architecture level. ### Data never leaves the perimeter AI works with your systems, but the LLM sees only the data structure — the documents, correspondence, and records themselves stay with you. ### Access rights and logging Every action the agent takes goes through your company's access rights and is recorded in a log — you can see who did what. ### Work under NDA All projects run under NDA, and the data stays inside the client's perimeter, not in the vendor's cloud. ### For critical industries This is essential for manufacturing, subsoil users, banks, and the public sector — anywhere a data leak is unacceptable. ## Questions and answers ### What is an AI agent and what can it do for a business? An AI agent is an artificial-intelligence-based program that doesn't just answer questions — it performs tasks in your systems: fills out documents, reconciles data, generates reports, and notifies employees. Implementing artificial intelligence in this form doesn't require the business to understand the technology — you describe the task in words, and the agent delivers it and keeps working like an employee. ### How is an AI agent different from a chatbot? A chatbot answers questions in a conversation — and that's where its job ends. An AI agent is connected to your systems — 1C, ERP, CRM — and takes action: creates a task, updates a record, generates a report. This is AI for business in the literal sense: not advice, but a result inside the system. ### Is it safe to connect AI to 1C and ERP? Yes: the data never leaves the company's perimeter — the model sees only structure, not the content of documents. Access rights and logging are configured for your company, and all projects run under NDA. ### Do we need to change our accounting system to implement AI? No — we work on top of your existing 1C or ERP, we don't offer to replace it. The agent connects to what you already have through a connector, not through a migration to a new system. ### How long does implementation take? First results appear in days or weeks, not months: a process diagnostic takes a few days, a pilot — a few weeks. That's a fundamental difference from classic ERP projects, which are measured in years. ### Where should we start if the company hasn't worked with AI yet? Start with a diagnostic of one process or a fast start with AI (AI Enablement) — training the team and launching the first tools in 1–5 days. This lets you see the effect without major investment and prepares the team for deeper projects. ## Book a diagnostic or a pilot Digital transformation of business in Kazakhstan doesn't start with a big program — it starts with one process: we'll show you where time and money are being lost and what's worth automating first — without long-winded promises. - Process diagnostic and impact assessment — from a few days - A pilot with results in weeks, not months - Work under NDA: your data stays with you ## Access for AI agents (MCP) **Cybernetica MCP server:** `https://mcp.cybernetica.kz/mcp` Connect this endpoint as an MCP connector in Claude, ChatGPT, Cursor, or another Model Context Protocol client for direct structured access to all company data — the product catalog, client cases, pricing, blog posts, and vacancies — with full-text search and no HTML parsing. Access is public, read-only, and requires no authentication. The Markdown language is selected by the page URL: Russian has no prefix, Kazakh uses `/kk`, and English uses `/en`. Send `Accept: text/markdown` to that URL or pass its path to `/api/agent-markdown?pathname=...`. The public REST API accepts `?locale=ru|kk|en`; Russian is the default. The MCP server tools take the same optional `locale` argument: if a record has no translation into the requested language, it comes back in Russian with a note saying so. ### Other resources for agents - [API catalog](https://cybernetica.kz/.well-known/api-catalog) - [OpenAPI](https://cybernetica.kz/api/openapi.json) - [LLMs.txt](https://cybernetica.kz/llms.txt)