AI agents & chatbots
5–25 mln UZS · 10–45 days
Runs on Telegram, your website, WhatsApp and Instagram. Built on a RAG knowledge base, so the agent answers strictly from your official documents instead of improvising.
AI solutions for business
Artificial intelligence services — AI solutions for your business
Artificial intelligence gives a business three concrete things: repetitive work done without a person, response times that drop from hours to seconds, and forecasts pulled out of data you already have. At Innosoft, AI solutions cost 5 to 35 million UZS (up to 60 million with attendance hardware) and go live in 10 to 60 days.
From 5 mln UZS Live in 10–60 days 4 AI systems in production
Updated: July 2026 · Written by the Innosoft engineering team, Tashkent
What is artificial intelligence?
Artificial intelligence (AI) is software that learns from data and then performs tasks people used to do by hand: understanding text, recognising images, predicting outcomes and making decisions. In business, AI is used to automate repetitive processes such as answering customer requests, processing documents, monitoring video and forecasting sales.
Language understanding (NLP)
Reads text and speech, writes replies, and extracts meaning from documents. This is the technology behind AI agents and chatbots.
Sight (computer vision)
Detects objects, faces, defects and events in photos and video. Quality control and attendance systems are built on it.
Prediction (machine learning)
Finds patterns in historical data: sales forecasts, demand planning, anomaly detection and fraud signals.
In practice these three strands work together. In a retail deployment, for example, an AI agent talks to the customer (NLP), cameras count footfall in the store (vision), and the system forecasts next week's stock requirement (machine learning). The table below is what we actually deliver, with the real price range for each.
AI solutions and prices — which one you actually need
Innosoft delivers AI in four directions: AI agents and chatbots (5–25 mln UZS), computer vision (15–50 mln UZS), AI integration and analytics (10–35 mln UZS), and face-recognition attendance (8–60 mln UZS). Each has its own page with the technical detail, tiers and case studies.
| Solution | What it does | Price (UZS) | Timeline | Learn more |
|---|---|---|---|---|
| AI agents & chatbots | Answers customer questions 24/7, takes orders, automates sales and first-line support | 5–25 mln UZS | 10–45 days | AI agent development |
| Computer vision | Image and video analysis: object detection, quality control, people counting, OCR | 15–50 mln UZS | 30–60 days | computer vision solutions |
| AI integration & analytics | Adds AI to the CRM, 1C or ERP you already run: document automation, sales forecasting | 10–35 mln UZS | 20–45 days | AI integration service |
| Attendance & face recognition | Logs staff check-in and check-out automatically through a camera or terminal | 8–60 mln UZS | 14–30 days | attendance system |
Computer vision
15–50 mln UZS · 30–60 days
Turns a camera feed into structured data in real time — a defective part on the line, a safety incident, footfall in a store, or text pulled out of a scanned document.
AI integration & analytics
10–35 mln UZS · 20–45 days
No rip-and-replace. We put an AI layer on top of the systems your team already uses, and your data stays exactly where it is today.
Attendance & face recognition
8–60 mln UZS · 14–30 days
A packaged product: real-time dashboard, Telegram bot reports, and payroll integration with 1C. Hardware scope drives the upper end of the price range.
Full tier-by-tier pricing for every Innosoft service is on our pricing page — see all service prices.
Which business needs which AI
Choosing AI starts with your problem, not your industry. The table below covers the five situations we see most often in the Uzbek market: the pain, the solution that fits it, and a realistic budget range.
| Business type | Typical problem | Solution that fits | Budget |
|---|---|---|---|
| Retail & e-commerce | Too many customer questions for the team to keep up with; no visibility into what will run out of stock and when | AI sales agent + demand forecasting | 5–20 mln UZS |
| Restaurants, cafes & HoReCa | Orders arrive by phone and Telegram, get written down by hand, and operators make mistakes under pressure | Telegram AI ordering agent + accounting integration | 5–15 mln UZS |
| Clinics & medical centers | The front desk is permanently busy, appointments only happen by phone, and nobody answers at night | AI reception agent (scheduling, services, pricing questions) | 8–20 mln UZS |
| Manufacturing | Quality control depends on the human eye, defects surface late, and shop-floor attendance is guesswork | Computer vision quality control + face-recognition attendance | 15–50 mln UZS |
| Professional services & offices | Documents and reports are assembled by hand, and there is no reliable record of how staff time is spent | AI integration (document automation) + attendance system | 8–35 mln UZS |
Your industry is not on the list? This table covers the most requested cases, but an AI solution follows the process rather than the sector — we also build for logistics, education, construction and public sector organisations. In the consultation we review your process and, if AI is not the right fit, we say so.
Our AI projects — systems running in production
Four real deployments: a RAG-based AI agent for a bank, a Telegram ordering system for HoReCa, an agent integrated with REGOS for a food supply company, and a 50-plus tool AI platform. Every one of them is delivered and live.
AI agent for the banking sector
RAG · safety guard · operator fallback
An agent that answers customer questions on loans, cards, deposits, payments and mobile app issues around the clock. We built the full multi-stage pipeline: intent classification, RAG retrieval, query rewrite, multi-turn context resolution, tool routing, safety guard and operator fallback. The agent never asks for a PIN, CVV or OTP, and returns a safe response whenever fraud is suspected. The client name is confidential.
Edem Bystro — AI order system for HoReCa
Telegram · accounting · courier integration
An intelligent system that takes and processes orders through Telegram for restaurants, cafes and hotels in Uzbekistan. The AI agent accepts an order in plain language — “50kg chicken, 20kg beef for tomorrow” — confirms it, calculates the total and completes it without an operator, 24/7. It is integrated with the client's accounting system and courier delivery, so every order is tracked from intake to hand-off. Delivered end to end: landing site, AI agent and Telegram integration.
Telegram food-ordering AI agent
REGOS API · stock monitoring
For a food delivery company we built a Telegram AI agent that receives orders from chefs in Telegram groups, confirms them and transfers them to the central accounting system through the REGOS API. Suppliers get real-time notifications when warehouse stock runs low. Stack: Python, OpenAI, Telegram Bot API, PostgreSQL. Delivered in one month.
Davirix — 50+ online tools platform
SaaS · AI tools · zero data storage
PDF tools, image tools, converters and AI tools (AI Writer, AI Image Generator, AI Summarizer) on a single platform. We delivered the full cycle: UI/UX design, frontend and backend. The guiding principle is “Zero Complexity”: no signup required, files are never stored on the server (zero data storage), and processing happens in the cloud.
How to implement AI in your business — 5 stages
Every AI implementation here follows five stages: business audit (3–5 days), data preparation and technology selection (5–10 days), prototype and development (10–30 days), integration and testing (5–15 days), and launch with monitoring (3–7 days). Total delivery runs from 10 to 60 days depending on the project.
1
Business audit and AI opportunity map
3–5 daysWe walk through your processes and identify which tasks AI can automate profitably. You get a ranked list of opportunities with a cost estimate and an expected impact for each. This stage can legitimately end with the conclusion that you do not need AI yet — and we will say so plainly.
2
Data preparation and technology selection
5–10 daysAI quality is data quality. We collect and clean whatever the solution will learn from: your knowledge base, documents, camera footage or CRM records. This is also where we lock in the model (GPT, Claude or a local open model), the infrastructure (cloud or your own servers) and the final budget.
3
Prototype and development
10–30 daysYou get a small working prototype first and test it with your own real questions. Once you approve it, we build the full version: prompt and pipeline engineering, RAG retrieval, computer vision model training, or the integration code — whichever the project needs.
4
Integration and testing
5–15 daysThe AI is connected to the systems you already run: CRM, 1C, Telegram, payment providers (Payme, Click) and your website. Then we test it against realistic scenarios — answer accuracy, edge cases, safety limits and the rules for handing a conversation to a human operator.
5
Launch, training and monitoring
3–7 daysWe deploy to production and train your team on the admin dashboard. During the first weeks we monitor real responses and tune the configuration based on what actually happens, then move the project into ongoing support.
The business audit and AI opportunity map are included free of charge in the consultation.
The honest section
When you do not need AI
Artificial intelligence is not the answer to every problem. In the six situations below, an AI project usually burns money and time — and in those cases we tell the client directly and offer a cheaper alternative. This is a practical conclusion drawn from projects we chose not to sign.
Turning it down costs us a contract and saves you a budget. It is a trade we are comfortable with, because the projects that go ahead are the ones that work.
Your process is not written down yet
Automating chaos only makes the chaos faster. If your order-intake rules, pricing policy or response standards are not documented, fix that first. In most of these cases a simple CRM or a scripted Telegram bot is cheaper and more useful than AI.
You have little or no data
An AI agent needs a knowledge base to answer from, and a computer vision model needs hundreds to thousands of labelled images. Without product descriptions, a question-and-answer archive or a decent image set, the result will land noticeably below what you expect.
Your request volume is small
If you get 10–20 similar questions a day, an AI agent takes a long time to pay for itself. Canned replies and a basic Telegram bot will do the job. AI agents start producing real economics when hundreds of repetitive requests arrive daily.
The cost of an error is high and nobody reviews the output
A medical diagnosis, a legal opinion or a financial transaction should not be decided by AI on its own. In these domains AI can only assist — a human approves the final decision. If you are not ready to build that review step, it is better not to start the project.
The only reason is that a competitor has it
AI is a tool, not a goal. Without a measurable problem — operator hours, error rate, response delay — the project stays a demo forever. In consultations we say this out loud and save you the budget.
Your budget is under 5 mln UZS
The realistic minimum for a quality AI solution is 5 mln UZS (a basic AI agent). Below that, only simple automation makes sense: a Telegram bot or an off-the-shelf SaaS product. We are happy to build that too — we just will not call it AI.
What to do instead: in many cases a straightforward Telegram bot, a CRM system or a web platform delivers results several times cheaper and faster. AI can be added later, once the process is stable and the data has accumulated.
Why run your AI project with Innosoft
We hand over AI as a system that runs, not as a demo that impresses: knowledge base, safety layer, integrations and monitoring included. Six points that make the difference.
RAG — no invented answers
The AI answers only from your documents. In our banking deployment, response validation and operator escalation rules are built as a separate layer of the pipeline.
Security inside the build
Confidential fields never reach the model, access is restricted by role, and where required the whole system runs on your own servers (on-premise).
Connects to what you already run
1C, Bitrix24, amoCRM, REGOS, Telegram, Payme and Click — our integration track record is documented in the portfolio, not claimed in a slide.
You see the prototype first
Before the full budget is committed, you test a small working version with your own real questions. If the result does not convince you, we do not scale it up.
Pricing in the open
The ranges are on this page and on the pricing page. API and server costs are itemised separately in the quote — there is no “we will tell you later”.
No model lock-in
GPT, Claude or a local open model — the architecture is built so the model can be swapped. If pricing or policy changes, changing the model does not break the project.
The technologies we work with
Technology is chosen per task — there is no universal stack. Below is what we have actually used in delivered projects.
OpenAI GPT
Conversation and reasoning
Anthropic Claude
Long context, analysis
RAG
Answers from your knowledge base
Vector DB
Semantic search
LangChain
Agent orchestration
Computer vision
Object and face detection
Python
AI backend
Node.js
Integration layer
PostgreSQL
Data storage
Telegram Bot API
Messaging channel
REST / Webhook
CRM, 1C, REGOS connectivity
On-premise
Runs on your own servers
For the underlying capabilities and safety guidance we build on, see the Anthropic Claude developer documentation, the OpenAI function-calling guide and Google's Responsible AI practices.
AI services — frequently asked questions
The twelve questions we are asked most often in consultations, answered directly: price, timeline, security, model choice and support.
How much do AI services cost in Uzbekistan?
AI agents and chatbots cost 5–25 mln UZS, AI integration and analytics 10–35 mln UZS, computer vision 15–50 mln UZS, and a face-recognition attendance system 8–60 mln UZS depending on hardware. The exact figure depends on task complexity, data volume and the number of integrations. After a free consultation you receive a written quote.
How long does an AI implementation take?
A straightforward AI agent goes live in 10–15 days, a mid-complexity solution in 20–30 days, and computer vision projects in 30–60 days. The process has five stages: audit (3–5 days), data preparation (5–10 days), development (10–30 days), integration and testing (5–15 days), and launch (3–7 days).
Which AI solution fits my business?
If you handle a high volume of customer requests, start with an AI agent. If your problem involves cameras or images, computer vision. If the data already lives in your CRM or 1C, AI integration and forecasting. If you need reliable staff time tracking, a face-recognition attendance system. The "Which business needs which AI" table on this page maps the most common situations.
Is our data secure?
Yes. Data moves over encrypted channels, access is restricted by role, and confidential fields (passwords, card numbers, PINs) are never sent to the model at all. In our banking deployment we built a dedicated safety guard layer: the agent never asks for a PIN, CVV or OTP, and returns a safe response whenever fraud is suspected.
Which AI model do you use — GPT or Claude?
It depends on the task. For conversation and complex reasoning we use OpenAI GPT or Anthropic Claude; for image analysis, computer vision models from the YOLO family and similar; and where privacy requirements are strict, open models running on your own servers. The choice is finalised together with you at stage two and can be changed later without rebuilding the project.
Can AI run on our own servers?
Yes, on-premise deployment is available. The model and the database sit inside your infrastructure and nothing leaves it. This option is typically chosen for banking, healthcare and government-related projects. Because of hardware requirements and licensing, the price is higher than the cloud option.
Is AI worth it for a small business?
If you have hundreds of repetitive requests or manual operations a day, yes. If the volume is small, a simple Telegram bot or a CRM will be cheaper and more effective. We do this arithmetic openly in the consultation and will not recommend AI when it does not pay off — see the "When you do not need AI" section on this page.
Do your AI solutions work in Uzbek?
Yes. Our AI solutions work in Uzbek, Russian and English, and can switch language inside a single conversation. To raise quality in Uzbek specifically, we populate the knowledge base in Uzbek and test responses against real customer questions before launch.
Can AI integrate with our existing CRM or 1C?
Yes. Our solutions connect to 1C, Bitrix24, amoCRM and other systems over API, as well as Telegram, WhatsApp, your website, payment providers (Payme, Click) and warehouse software. In our Telegram AI agent project we integrated fully with the REGOS accounting system.
What happens when the AI gives a wrong answer?
Errors cannot be driven to zero, so we make them controllable instead. Solutions are built on RAG, meaning answers are retrieved from your documents rather than invented. When the agent's confidence is low it escalates to a human operator or opens a ticket instead of guessing. Every conversation is logged and reviewed.
Are there monthly costs after launch?
There can be two: model API usage (typically 300,000 to 3 mln UZS per month depending on volume) and server or hosting fees. Computer vision projects also carry one-off hardware costs for cameras and GPU servers. All of this is itemised in the quote — there are no hidden charges.
Do you provide support after launch?
Yes. Every project includes technical support for 3, 6 or 12 months depending on the tier. That covers monitoring, bug fixes, knowledge base updates and response quality improvements. When the included period ends, you can continue on a monthly support agreement.
Key AI terms, explained without the jargon
Four terms come up in almost every AI conversation. Knowing what they actually mean makes it much easier to judge whether a proposal you receive is serious.
LLM (large language model)
The model behind text-based AI — GPT and Claude are examples. It predicts and generates language extremely well, but on its own it knows nothing about your company. Everything useful comes from what you connect to it.
RAG (retrieval-augmented generation)
The technique that grounds answers in your documents. Your content is indexed; when a question arrives, the relevant passages are retrieved first and the model answers from them. This is what separates a reliable agent from a plausible guesser.
Computer vision
Models that read images and video rather than text. They detect objects, faces, defects and events, and are trained on labelled examples from your own environment — which is why image data matters more than model choice here.
Hallucination
When a model states something confidently that is not true. It cannot be eliminated, only controlled — through RAG grounding, response validation against sources, and escalating to a human when confidence is low.
Related services
An AI solution rarely stands alone — it is built on top of a website, a bot or a CRM. The pages below cover the services that usually sit alongside it.
AI agent developmentAgents and chatbots — from 5 mln UZSComputer vision solutionsImage and video analysis — from 15 mln UZSAI integrationAI on top of your existing systems — from 10 mln UZSAttendance systemFace recognition — from 8 mln UZSTelegram bot developmentStraightforward automation without AIAll servicesThe full Innosoft services catalog
About the provider
Innosoft is a software development company based in Tashkent, Uzbekistan that builds artificial intelligence solutions, web platforms, Telegram bots and CRM systems. In the AI direction we have delivered production systems for banking, HoReCa, food logistics and SaaS clients. AI projects start at 5,000,000 UZS and go live in 10 to 60 days. We work in Uzbek, Russian and English; you can reach us on +998 77 016 87 88.
Every project is adapted to the realities of the Uzbek market: conversation in Uzbek, Payme and Click payments, local accounting software such as 1C and REGOS, and Telegram as the primary customer channel rather than an afterthought.
If your requirements are not defined yet, that is a perfectly good starting point. The first step is reviewing your processes and establishing where AI helps — or where it does not. That work is done as part of a free consultation. For budgets across every service, see our pricing.
Updated: July 2026 · Innosoft engineering team, Tashkent