How long does implementation take?

Timeline depends on the number of scenarios and source data quality. Implementation is usually split into stages.

Can you automate an existing process?

Yes. We analyze the current process and data, then decide which steps can be automated.

Do you need large data volumes to implement this?

Not always. Many classification and routing scenarios work well on moderate data volumes.

Can the AI solution integrate with CRM and ERP?

Yes. Integrations are designed as part of the architecture: APIs, data exchange, and result handling.

How is AI solution quality controlled?

We design accuracy metrics, manual review of edge cases, and gradual expansion of automation scope.

• AI AUTOMATION

AI and business process automation

We bring AI into business processes — request classification, scoring, data processing, and AI agents. From task analysis to launch, integrations, and further growth.

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AI AUTOMATION

Classification, agents & scoring

From process analysis to launching AI that saves your team real time.

Custom AI solutions for business

We build AI solutions around your company's real data and processes, not generic models. We design classification, scoring, and processing scenarios that deliver measurable results.

Full-cycle AI automation development

We take the project from data analysis to production launch: model selection, integration with data sources, accuracy testing, deployment, and further growth. We can also join existing processes.

AI solutions we build

01Request ClassificationAutomatically determining the type and priority of incoming requests.

02Scoring & EvaluationScoring leads, risks, and request quality based on data.

03AI AgentsAutomated assistants for handling routine requests.

04Document ProcessingExtracting and structuring data from documents and files.

05RoutingAutomatically distributing requests across teams and assignees.

06Data IntegrationsConnecting AI models to CRM, ERP, and internal company databases.

AI
automation
architecture and integrations

The architecture is designed around the company's data sources and business logic. We define models, processing pipelines, roles, and integration points — keeping the AI solution accurate and explainable as data volume grows.

If you need to connect existing systems: system integration.

Architecture layers

01Data sources

02Models & scenarios

03Processing pipelines

04Roles & oversight

05API

06Integration points

AI automation implementation stages

Task AnalysisWe study the business task, users, processes, data, and requirements for the first version of the AI solution.

Architecture DesignWe define system modules, data structure, user roles, APIs, integrations, and the implementation sequence.

DevelopmentWe implement the backend, frontend, business logic, integrations, and core user scenarios in stages.

Testing & LaunchWe verify critical scenarios, integrations, and system stability, then prepare the environment and launch.

Support & GrowthAfter launch we add new modules and features, optimize processes, and scale the system as the business grows.

AI automation implementation cost

The cost is calculated individually after analyzing the data and task. It depends on scenario complexity, data volume, accuracy requirements, and integrations. After discussing the project, we prepare a phased estimate.

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PROJECT ESTIMATE

A tailored AI project estimate

We define scenarios, models, integrations, and phased cost.

Custom AI automation

Custom AI solutions suit companies with specific data and processes. The system is designed around specific classification, scoring, and processing scenarios.

MVP and launching your first AI scenario

If you need to quickly validate an automation hypothesis, we build an MVP: one scenario, a basic model, and a data integration.

A separate service: MVP development.

AI automation FAQ

Cost depends on scenario complexity, data volume, and accuracy requirements. We first define the task, then prepare a phased estimate.

Let's discuss your project

Tell us about the process, data, and task you want to automate. We'll help define the architecture, the first scenario, and the best next implementation step.

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