AI Agent Development — Intelligent Automation for Your Business
An AI agent answers your customers, takes orders, and runs routine back-office work on its own, 24/7, in Uzbek, Russian, and English — using your own data instead of a fixed script. Innosoft builds custom AI agents in Tashkent from 5,000,000 UZS, delivered in 10–45 days depending on complexity — on GPT-4o and Claude, integrated with your CRM, Telegram, and payment systems.
Updated: July 2026 · Written by the Innosoft AI engineering team, Tashkent
AI agents delivered
Years building with LLMs
Client satisfaction
Monitoring & support
What Is an AI Agent — and Why Does Your Business Need One?
An AI agent is intelligent software that independently performs tasks people used to do by hand. Unlike a simple scripted chatbot, an AI agent can make decisions, learn, and adapt to the situation. It combines a large language model with your business data, your systems, and carefully engineered guardrails — so it does not just chat, it gets work done.
Companies worldwide are moving to AI agents fast, and for a concrete reason: an agent automates staff workloads, reduces errors, works 24/7, and multiplies business efficiency. With Innosoft's AI agent development service, you get that advantage over your competitors — built locally, in your languages, integrated with the systems used in Uzbekistan.
We use GPT-4o, Claude, and other frontier AI technologies to build agents tailored to your business: customer conversations, data analysis, order management, document workflows, and dozens of other tasks. Everything is custom — no off-the-shelf template pretending to know your business.
Why Build Your AI Agent with Innosoft?
The capabilities and guarantees behind our AI agent development service
Always On, 24/7
An AI agent never sleeps, never takes a holiday, and never keeps a customer waiting. It handles conversations and business processes around the clock — including nights, weekends, and peak-season spikes.
Reasoning, Not Scripts
Unlike a rule-based bot, an AI agent understands intent, weighs context, and makes data-driven decisions. It handles questions nobody scripted in advance — and knows when to escalate to a human.
3–5x Efficiency Gains
Agents absorb the repetitive work — answering FAQs, processing orders, drafting reports — so your team focuses on judgment calls. Our clients typically see a 3–5x boost in operational throughput.
Data Analysis & Forecasting
Real-time analysis of large data volumes, trend detection, and business forecasting are built into our AI agent development service — turning raw operational data into decisions.
Natural Conversation in 3+ Languages
Our agents converse fluently in Uzbek, Russian, and English — often within the same dialogue. Customers talk to the agent like a person; no commands or menus required.
Security & Privacy by Design
All data is encrypted in transit and at rest. We build safety guards into the pipeline itself — agents never request sensitive credentials, and every deployment complies with GDPR principles and local regulation.
Deep System Integration
CRM, ERP, 1C, Bitrix24, Telegram, WhatsApp, your website, Payme and Click payments, email platforms — the agent works inside the systems you already run, not beside them.
Improves Over Time
Every deployment includes feedback loops: conversation reviews, knowledge base updates, and prompt refinements. Your agent gets measurably more accurate month over month.
Full Analytics & KPIs
A complete picture of agent performance: conversation volume, resolution rate, customer satisfaction, escalations, and the KPIs that matter to your business.
Custom AI Chatbots, Automation Agents, and Analytics Agents
Three families of AI agents — pick the one that fits your business, or combine them into a single ecosystem
Custom AI Chatbot — Intelligent Customer Service
A custom AI chatbot that holds real conversations with your customers 24/7 — on Telegram, WhatsApp, Instagram, and your website. It answers questions from your actual knowledge base, takes orders, and hands off to an operator when a human is genuinely needed.
- Natural dialogue in Uzbek, Russian, and English
- Accurate answers grounded in your company data
- Automatic order intake and qualification
- Telegram, WhatsApp, Instagram, and website integration
Business Automation AI — Process Agents
Agents that take over repetitive back-office work end to end: preparing and sending documents, updating your CRM and ERP, scheduling emails and notifications, and moving data between systems without human copy-paste.
- Automatic document preparation and delivery
- CRM and ERP record management
- Scheduled email and notification workflows
- Full automation of recurring multi-step processes
Analytics & Forecasting Agents
Agents that analyze large volumes of business data and return intelligent forecasts: sales projections, customer behavior analysis, segmentation, and automated reporting for strategic decision-making.
- Real-time data analysis and visualization
- Sales and revenue forecasting
- Customer behavior and segmentation analysis
- Automated reports and KPI monitoring
RAG Development: How We Make AI Agents Accurate
The difference between a demo chatbot and a production AI agent is the pipeline around the model. Here is the multi-stage architecture we build — proven in our banking sector deployment.
RAG (Retrieval-Augmented Generation) grounds every answer in your official data, indexed in a vector database — so the agent cites your knowledge, not the model's guesswork.
Intent classification
The agent first determines what the user actually wants — a product question, a support issue, an order, or something out of scope.
Query rewrite & RAG search
The question is rewritten for retrieval, then matched against your indexed knowledge base using vector search — so answers come from your official data, not the model's imagination.
Context resolution & tool routing
A multi-turn context resolver keeps track of the whole conversation, while tool routing decides whether to search documents, call an API, create a ticket, or look up a record.
Safety guard
A dedicated safety layer blocks sensitive requests. In our banking deployments, the agent never asks for PIN, CVV, or OTP codes and returns a safe response when fraud is suspected.
Response validation
Before anything reaches the user, the draft answer is validated against the retrieved sources — a hard control against hallucinated responses.
Operator fallback
When the agent cannot resolve an issue confidently, it escalates to a human operator or creates a ticket — with the full conversation context attached.
RAG Pipeline Stages: What Each One Does and Why It Matters
The eight stages below are the exact architecture running in our banking AI agent deployment.
| Stage | What it does | Why it matters |
|---|---|---|
| 1. Intent classification | Classifies the incoming message: product question, technical issue, order, complaint, or out of scope. | Routing decides everything downstream. Misread the intent and every later stage works on the wrong problem. |
| 2. Query rewrite | Rewrites the raw message into a clean, self-contained search query (expanding pronouns, fixing typos, normalising UZ / RU / EN). | Real users write 'and what about the second one?'. Vector search cannot retrieve on that — the rewrite makes it searchable. |
| 3. Retrieval (RAG search) | Runs vector search over your indexed knowledge base and returns the top relevant passages with their sources. | This is what grounds the answer in your official documents instead of the model's general training. |
| 4. Multi-turn context resolution | Keeps state across the conversation: what was asked, what was already answered, which record is being discussed. | Support conversations are rarely one question. Without context the agent repeats itself and the customer gives up. |
| 5. Tool routing | Decides whether to answer from documents, call an internal API, look up a record, find a branch or ATM, or create a ticket. | An agent that can only talk is a chatbot. Tool routing is what turns it into an agent that acts. |
| 6. Safety guard | Blocks sensitive requests. In our banking deployment the agent never asks for PIN, CVV, or OTP, and returns a safe response when fraud is suspected. | In regulated sectors one unsafe reply is a bigger problem than a hundred unanswered questions. |
| 7. Response validation | Checks the draft answer against the retrieved sources before it is sent to the user. | The last line of defence against hallucination — an unsupported claim never reaches the customer. |
| 8. Operator fallback | Escalates to a human or opens a ticket when confidence is low, the topic is sensitive, or the customer asks for a person — with full conversation context attached. | Knowing when to stop answering is a feature. It keeps trust intact and stops nobody from repeating themselves. |
Retrieval-Augmented Generation was introduced in Lewis et al., “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks” (2020). For the tool-use and agent patterns we build on, see the Anthropic Claude tool-use documentation and the OpenAI function-calling guide.
Rule-Based Chatbot vs LLM Chatbot vs RAG Agent
Three different products get sold under the word “chatbot”, and they behave nothing alike. A rule-based bot follows a script, an LLM chatbot answers from the model's general training, and a RAG agent answers from your own documents and can act on your systems. Here is the honest comparison we walk every client through.
| Criterion | Rule-based chatbot | LLM chatbot | RAG agent |
|---|---|---|---|
| How it answers | Matches keywords and buttons against a fixed script | Generates an answer from the model's general training | Retrieves passages from your indexed documents, then answers from them |
| Data source | Hard-coded scenarios written by a developer | The model's training data — not your company data | Your knowledge base: FAQs, price lists, policies, catalogs, CRM records |
| Out-of-script questions | Dead end — 'I don't understand, please choose an option' | Always answers, but may invent details (hallucination risk) | Answers from sources, or escalates to a human when nothing matches |
| Maintenance | Every new case needs a developer to edit the script | Prompt edits only; wrong facts are hard to fix | Update the document — the agent picks up the change on re-index |
| Typical cost with Innosoft | From 3,000,000 UZS (Telegram bot service) | 5,000,000 – 8,000,000 UZS (Starter tier) | 10,000,000 – 25,000,000 UZS (Business / Enterprise tiers) |
| Best for | Fixed flows: order forms, bookings, status checks | General assistants, drafting, brainstorming, internal tools | Customer support, banking, e-commerce — anywhere a wrong answer is expensive |
Not every business needs a RAG agent. If your flow is fixed — order intake, bookings, delivery status — a Telegram bot is faster and cheaper, and we will say so. RAG earns its cost when a wrong answer is expensive.
Business Automation AI Across Industries
We build custom AI agents for every sector — here is where they deliver the most value
E-commerce
Order intake, product Q&A, and customer management
Finance & Banking
Secure product consultations, transaction analysis, fraud-aware support
Healthcare
Patient data analysis and appointment workflows
Education
Personalized learning assistants and admissions support
Logistics
Route optimization and shipment status automation
HR & Recruiting
Candidate screening and interview scheduling
Marketing
Content generation and campaign analytics
Customer Support
24/7 first-line support with human escalation
Our AI Agent Development Process
Six stages from idea to a working AI agent — with a prototype you can test early and a clear scope at every step
Business Analysis
We study your company's needs, map exactly which tasks the AI agent will own, and define measurable goals. You leave this stage with a clear scope — not a vague promise.
Architecture & Prototype
We design the agent architecture, define data flows and integration points, and build an interactive prototype you can actually try before full development begins.
AI Model & Engineering
We configure GPT-4o, Claude, or the model best suited to your case, engineer the prompts and retrieval pipeline, and write the agent code.
Integration
Full integration with your CRM, payment systems, Telegram, and other platforms — the agent plugs into your existing stack, not a parallel one.
Testing & QA
Quality control across realistic scenarios: edge cases, adversarial questions, multi-turn conversations, and load — followed by targeted optimization.
Launch & Support
Production deployment with 24/7 monitoring, one month of free post-launch support, and continuous optimization based on real conversations.
AI Technologies We Work With
We are model-agnostic: for every project we pick the stack that fits the task, the budget, and the data sensitivity
OpenAI GPT-4o
Frontier language model
Anthropic Claude
Reasoning & long context
LangChain
Agent orchestration
RAG
Retrieval-Augmented Generation
Vector Databases
Semantic search at scale
Python
Core engineering language
Node.js
Backend & integrations
Telegram Bot API
Messaging channel
AI Agent Development Pricing
Transparent pricing in UZS, scoped to the complexity of your project — no hidden fees, no surprises after the contract
Compare all our services on the pricing page.
Starter AI Agent
5–8 mln UZS
Delivery: 10–15 days
A focused agent for customer conversations and simple task automation on one channel.
- AI chatbot on Telegram or your website
- Answers grounded in your FAQ and documents
- Uzbek, Russian, and English support
- Basic analytics dashboard
- 1 month of free support
Business AI Agent
10–15 mln UZS
Delivery: 20–30 days
A production agent with CRM integration, RAG over your knowledge base, and multi-channel automation.
- Everything in Starter
- Full RAG pipeline over your knowledge base
- CRM / ERP / 1C / Bitrix24 integration
- Multi-channel: Telegram, WhatsApp, website
- Payment integration (Payme, Click)
- Operator fallback and ticket creation
Enterprise AI Agent
15–25 mln UZS
Delivery: 30–45 days
A complete AI agent ecosystem for large organizations with complex pipelines and strict security requirements.
- Everything in Business
- Multi-stage pipeline: intent, RAG, safety guard, validation
- Multiple coordinated agents
- Custom security and compliance controls
- SLA-backed dedicated support
- Team training and handover
AI Agent Development Cost in Uzbekistan — 2026 Price Table
Real ranges we quote, in Uzbek som. Prices are the same for clients in Tashkent and in the regions.
| Agent type | What's included | Price (UZS) | Timeline |
|---|---|---|---|
| Starter AI agent | One channel (Telegram or website chat), answers grounded in your FAQ and documents, UZ / RU / EN, basic analytics | 5,000,000 – 8,000,000 UZS | 10–15 days |
| Business AI agent | Full RAG pipeline over your knowledge base, CRM / ERP / 1C / Bitrix24 integration, multi-channel (Telegram, WhatsApp, website), Payme & Click, operator fallback | 10,000,000 – 15,000,000 UZS | 20–30 days |
| Enterprise AI agent | Multi-stage pipeline (intent → RAG → safety guard → validation), several coordinated agents, custom security and compliance controls, SLA support, team training | 15,000,000 – 25,000,000 UZS | 30–45 days |
Every tier includes multilingual support (Uzbek / Russian / English), one month of free post-launch support, and 24/7 monitoring. Final pricing depends on integrations and data volume — get an exact quote in a free consultation. Ongoing model and infrastructure costs (LLM API usage) are billed separately at cost.
AI Agents We Have Shipped
Not concepts — production systems running for real businesses. Here are three of them.
AI Agent for the Banking Sector
A RAG-based agent that gives bank customers fast, accurate, and secure answers 24/7 — on loans, cards, deposits, payments, and mobile app issues. It also finds branches and ATMs, escalates to an operator, or opens a ticket when needed. We built the full multi-stage pipeline: intent classification, query rewrite, RAG search, multi-turn context resolver, tool routing, safety guard, response validation, and operator fallback. The agent never asks for PIN, CVV, or OTP and returns a safe response when fraud is suspected. Operator workload dropped, and customers now get answers from official bank data around the clock. The client name is confidential.
Edem Bystro — AI Order System for HoReCa
An AI agent that takes orders via Telegram for restaurants, cafes, and hotels in Uzbekistan. Kitchens write in plain language — "50kg chicken, 20kg beef for tomorrow" — and the agent confirms the order, calculates the total, and completes it with no operator involved, 24/7, in under three seconds. 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
For a food delivery company, we built a Telegram AI agent that receives orders from chefs via Telegram groups, confirms them, and transfers them to the accounting system through the REGOS API. Suppliers get real-time notifications when warehouse stock runs low. Delivered in one month.
What Every Project Includes
1 Month Free Support
Post-launch support at no cost: fixes, adjustments, and knowledge base tuning while the agent settles in.
24/7 Monitoring
Round-the-clock monitoring of uptime, response quality, and error rates from day one.
UZ / RU / EN Languages
Multilingual conversation support is standard in every tier, not a paid add-on.
Continuous Optimization
Updates and improvements driven by real conversation data and user feedback.
AI Agent Development — Frequently Asked Questions
Everything clients ask us before starting an AI project — pricing, timelines, security, and technology
AI Agent Development in Uzbekistan
About the provider
Innosoft is a software development company in Tashkent, Uzbekistan that builds custom AI agents, RAG systems, Telegram bots, CRM platforms, and websites. Our office is in the Yunusabad district, U-Enter Business Center, 3rd floor. We have been building with large language models since 2023 and have delivered production AI agents for banking, food delivery, and HoReCa clients in Uzbekistan. AI agent projects start at 5,000,000 UZS and ship in 10–45 days. We work in Uzbek, Russian, and English; contact us on +998 77 016 87 88 or via the contact page.
Innosoft is a professional IT company based in Tashkent, and AI agent development is one of our core specializations. We build artificial intelligence agents for enterprises and startups across Uzbekistan — from banking-grade RAG systems to Telegram ordering agents for food delivery businesses.
Our service goes far beyond a simple chatbot. We deliver the full cycle: business analysis, AI model selection, prompt and pipeline engineering, RAG development over your knowledge base, integration with CRM and payment systems, testing, and ongoing support. Because we work locally, your agent speaks Uzbek natively, integrates with Payme and Click, and connects to the systems businesses here actually use — 1C, Bitrix24, REGOS, and Telegram.
If you need business automation AI to cut costs, reduce errors, and scale your customer service without scaling headcount, talk to the Innosoft team. We will turn your idea into a working intelligent system — and show you a prototype before you commit to the full build.
Related services: Telegram bot development, CRM development, and the full services catalog. For budgets across all services, see our pricing.
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Web development, Telegram bots, SEO, and more — see everything we build.
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