Turnkey AI agent development

An agent that knows your playbooks, not the internet

Unlike off-the-shelf SaaS, a custom agent accounts for your business specifics, security requirements and your stack. We train it on your data, embed it into your CRM, ERP, 1C and EDMS, and hand over all the source code.

Start a pilot from 200,000 RUB · a pilot in 2 weeks
Sales

AI sales agent

Qualifies leads, answers routine customer questions, prepares proposals, runs the deal in the CRM and assigns tasks to managers. Lowers the cost per lead and shortens the sales cycle.

amoCRMBitrix24TelegramWhatsApp
Support

AI customer support agent

Handles requests in chats, messengers and email 24/7. Resolves up to 80% of routine questions and escalates complex cases to an operator.

Knowledge baseEmailChats
Marketing

AI marketing agent

Generates copy, creatives, newsletters and posts. Analyzes campaign performance and picks hypotheses to test.

Ad platformsAnalytics
Analytics

AI data analytics agent

Collects data from corporate sources, builds reports and dashboards, and answers business questions in natural language.

CSVExcelJSONParquetPostgreSQL1C
Legal

Legal AI — a lawyer's agent

Analyzes contracts, checks documents against the law and drafts opinions on the key parameters.

ConsultantPlusGarantEDMS1C:DO
Telegram

Telegram bots, with or without AI

Intake, bookings, payments, notifications, Mini Apps. A classic button-and-flow bot — or one with an AI agent inside that understands free text.

Bot APIMini AppsYooKassaamoCRM
Voice

A voice agent for call centers

Takes inbound calls, books appointments, confirms orders, answers routine questions by voice and transfers to an operator when needed. Response latency — under a second.

AsteriskMango OfficeSpeech-to-TextCRM
Custom

A custom AI agent

Resume screening, procurement and proposal comparison, correspondence quality control, an internal assistant over your knowledge base. The architecture is tailored to your case.

HRProcurementQA
What it looks like in action

The agent doesn't just answer — it calls your systems

Three real scenarios. The grey rows with an icon are tool calls: the agent queries an API, a database or a document, gets the data and only then formulates the answer.

Sales agentWhatsApp · amoCRM
We need 40 office chairs delivered to Kazan. How much, and when?
get_stock(sku="KR-204", qty=40)→ 56 pcs
get_price(sku, 40, "Kazan")→ 7 890 ₽
amocrm.create_lead(...)→ #10482
56 in stock. For orders of 40+ the price is 7,890 RUB each, 315,600 RUB total. Delivery to Kazan in 3–4 days. I emailed you the proposal and created the deal — your manager Irina will get in touch within an hour.
Analytics agentCSV · Excel · JSON · Parquet
Here are the exports for July and August. Which regions dropped in revenue?
load("jul.csv", "aug.xlsx")→ 48,210 rows
compare_by("region")→ 14 regions
Urals−18%
Siberia−11%
South−6%
Three regions dropped, the Urals the most: −18%, mostly due to the Furniture category (−31%). The other 11 regions grew. I built a cleaned dataset in Parquet and a Urals breakdown in Excel — shall I send it?
Legal AIEDMS · ConsultantPlus
Review supply contract #DP-114 from the counterparty
read_document("DP-114.docx")→ 42 clauses
search_law("penalty, supply")→ art. 521
check_counterparty(inn="7719…")→ active
cl. 7.2 — a 1%-per-day penalty with no cap. Risk: a court may reduce it under art. 333 of the Civil Code; we recommend a 10% cap.
cl. 4.1 — payment "within a reasonable time". Vague; should be replaced with calendar days.
The remaining 40 clauses — match the company's standard form.
Two risks, both favoring the counterparty. I drafted a protocol of disagreements and placed it in the EDMS for the lawyer's approval.
Under the hood

Architecture that stays with you

We don't lock into a single vendor: OpenAI and Claude where accuracy matters; DeepSeek and Qwen where price matters; GigaChat and YandexGPT when data must stay in Russia; open-source in a closed perimeter when nothing may go outside. We build agents on Pydantic AI and OpenAI Agents SDK with tool calling — the agent doesn't just answer, it calls your systems itself. Backend — Python/FastAPI, NestJS, Go or Spring Boot.

OpenAIClaudeDeepSeekQwenGigaChatYandexGPTLlama / Mistral on-premise
LLM OpenAI, Claude, DeepSeek, Qwen, GigaChat, YandexGPT — chosen by data requirements and budget
RAG Answers from your knowledge base, not from the model's memory
Vector databases Indexing of documents, regulations and correspondence
Data protection & security Personal data — only on servers in Russia, anonymization before sending to the model, an on-premise perimeter on request
Tool calling The agent calls your APIs and functions: CRM, 1C, warehouse, payments, documents — with parameter validation and confirmation of critical actions
Agent frameworks Pydantic AI, OpenAI Agents SDK, LangGraph — tools, handoffs, guardrails
Backend Python + FastAPI, NestJS, Go, Spring Boot — matching your stack
Integrations CRM, ERP, 1C, EDMS and messengers via APIs and connectors
Evaluation Accuracy, hallucination rate, latency and cost per request
Stages

From audit to production monitoring

1

Audit

Processes, tasks for the agent, a spec and metrics. Free.

2

Architecture

LLM, RAG pipeline, integrations, decision logic.

3

Development

Code, data indexing, prompt engineering, tools.

4

Tests

Evaluation on real cases; measuring quality and cost.

5

Launch

Production, team training, monitoring, SLA.

Let's start with a free audit

We'll review your processes, name the tasks worth handing to the agent first, and estimate the cost within one business day.

Get a Quote
Get a Quote