Cortex Intellect creates intelligent systems powered by artificial intelligence that help companies automate business processes, manage large volumes of data, improve customer interactions, and optimize daily operations.
We develop AI agents, virtual assistants, generative tools, and comprehensive software solutions, integrating them into existing IT infrastructure or creating new products from scratch.
Key benefits:
Ready-made AI tools handle typical tasks well, but they don't always take into account the specifics of a company's internal processes, data structure, rules for interaction between departments, and software infrastructure requirements.
We develop solutions tailored to specific business models and existing workflows. This allows us to create not just standalone AI functions, but fully-fledged tools that become part of a company's daily operations.
Depending on the task, we can implement:
During development, we consider not only functionality, but also requirements for security, performance, scalability, and further development of the system.
Each solution is designed around a specific task: from automating a single operation to creating a complete intelligent platform.
The potential of artificial intelligence is most noticeable when it becomes a full-fledged participant in business processes, rather than simply an additional tool for employees.
The AI receives a request from a potential client, analyzes the content of the request, determines their needs, and qualifies the lead. It then stores the information in the CRM, prepares a personalized offer, or forwards the request to the responsible manager.
This allows us to speed up the processing of applications, reduce response times, and ensure more consistent work with potential buyers.
The system receives documents, recognizes text, and extracts the necessary information. It then validates the data against specified rules, identifies possible errors, and transfers the structured information to a CRM, ERP, or other corporate system.
This approach is suitable for processing invoices, contracts, applications, delivery notes and other documents.
The manager formulates the question in plain language. The AI accesses connected data sources, analyzes the necessary metrics, and generates a response in a user-friendly format.
The system can generate reports, compare periods, identify deviations, and help find the causes of changes in business indicators.
The AI agent receives a task, determines the sequence of actions, and interacts with the necessary software systems. It can verify information, create records, update statuses, generate documents, and notify employees of the results.
Depending on the scenario, individual actions may be performed automatically or require confirmation from a responsible employee.
The system receives product information, takes into account brand requirements, and generates the necessary materials: product descriptions, advertising texts, images, and other content formats.
Finished materials can be automatically submitted for review, approval, or publication in connected channels.
AI is most beneficial when it has access to the necessary information and can interact with the tools a company already uses.
We integrate AI solutions with existing software products, databases, and external services. This allows us to unite disparate information sources and automate processes that previously required manual switching between systems.
CRM, ERP, HRM, CMS, BI platforms, and other corporate solutions. AI can retrieve data from them, analyze the information, and perform authorized operations.
PostgreSQL, MySQL, MongoDB, and other sources of structured and unstructured data. We implement connections to internal knowledge bases and information retrieval using the RAG architecture.
Telegram, WhatsApp, email, telephony, and other communication channels. We integrate AI assistants into familiar communication channels with clients and employees.
REST API, webhooks, and third-party software platforms. We facilitate data exchange, operation initiation, and interaction between various system components.
We integrate LLM, multimodal models, recognition services, and specialized ML algorithms in accordance with project objectives.
We create user interfaces for interacting with AI: from built-in assistants and intelligent search to full-fledged control panels and standalone applications.
A separate area is the development of MCP servers , which allow AI assistants to securely interact with corporate data and tools through a standardized interface.
You don't have to change your existing IT infrastructure to start using artificial intelligence. We can integrate new capabilities into existing business systems.
Personalized product recommendations, AI consultants, automated order processing, description generation, and customer behavior analysis.
Computer vision for product quality control, defect detection, production data analysis, demand forecasting, and automation of technical documentation.
Automatic processing of transport documents, route analysis, delivery time forecasting, transaction monitoring, and intelligent request processing.
Document recognition and verification, transaction analysis, anomaly detection, automated reporting, and customer inquiries processing.
Intelligent property search, real estate database processing, property and document analysis, and automated communications with potential buyers and tenants.
Processing medical records, structuring information, automating administrative processes, and intelligently routing requests in compliance with data protection requirements.
Development of AI functions within software products, intelligent interfaces, support automation, processing of user requests, and creation of new AI services.
Internal AI assistants, corporate knowledge base search, document automation, analytics, and interdepartmental collaboration optimization.
Developing an AI system begins with understanding the problem to be solved and the desired results the future product should deliver. We consistently refine the concept, architecture, functionality, and integrations to create a solution ready for use in real-world business processes.
We study the specifics of your business, existing processes, and available data sources. We determine which operations can be automated using AI and evaluate the technical feasibility and potential effectiveness of the solution.
We define the structure of the future system, select suitable models and technologies, design component interactions, integrations, and user scenarios. We also develop technical requirements and an implementation plan.
We create the first working version of the solution, implement key features, and test key hypotheses. This allows us to evaluate the quality of the AI, identify limitations, and determine necessary improvements before full-scale development begins.
We implement agreed-upon functionality, develop server components and interfaces, and connect databases, external services, and corporate systems.
We verify the correct operation of scripts, the quality of data processing, system stability, and security. We fix errors, optimize performance, and prepare the solution for production.
We support the system after launch, analyze its operation, optimize processes, and expand functionality as new business challenges arise.
To create a useful AI product, it's not enough to simply select the right model. It's essential to understand how the company's processes are structured, where the data comes from, what actions the system should perform, and how its output will be used by employees or clients.
Cortex Intellect combines expertise in software development, digital product design, systems integration, and AI technology implementation.
Tell us about your project, business processes, or idea for a new digital product. We'll help you identify opportunities for using artificial intelligence, evaluate the technical implementation, and suggest the optimal development approach.
The cost depends on the project's complexity, the number of features, the selected AI models, the volume of data, the required integrations, and the infrastructure requirements. Developing a standalone AI assistant and creating a comprehensive platform require completely different resources. After analyzing the task, we determine the scope of work and propose the optimal implementation option.
Timelines depend on the functionality and scale of the project. A prototype or MVP can be implemented significantly faster than a full-fledged enterprise platform with multiple integrations and complex business logic. Specific timelines are determined after the requirements and architecture are agreed upon.
Yes. We can add AI functionality to your existing system via APIs, webhooks, and other available integration mechanisms. For example, we can implement an intelligent assistant, automated request processing, data analysis, or user-requested operations.
Yes. To do this, you can connect corporate documents, databases, and other information sources, implement RAG and search mechanisms within the internal knowledge base. The assistant will be able to use up-to-date company information when generating responses, taking into account configured access rights.
Not always. In many projects, it's sufficient to use ready-made models, customize them for specific tasks, and connect the necessary data and tools. A custom model or additional training may be required if the project has specific requirements for accuracy, subject area, or data processing.
Security is designed taking into account the solution architecture, the services used, and the company's requirements. This may include access control, encryption, data isolation, transaction monitoring, and component placement within the selected infrastructure. Specific mechanisms are determined at the design stage.
Yes. This is one of the practical approaches to developing AI products. Key features are implemented first and tested in real-world conditions. Then the system is expanded: new scenarios, integrations, data sources, and additional capabilities are added.
Yes. After implementation, you can organize technical support, monitoring, bug fixing, performance optimization, and further functionality development. This is especially important for systems that work with changing data, models, and business processes.
