AI assistants

Technological solution
AI assistants – are relatively small software assistants that help employees perform everyday tasks. They function based on a large volume of unstructured knowledge – general, corporate-owned or domain-specific. Ai assistants can perform a wide range of functions, including natural language processing, data analysis, task automation, and more.
What tasks can AI assistants perform
  • Smart search & data summarization of unstructured complex data (documents, templates, etc.)
  • Data retrieval from unstructured documents and
    third-party sources (Internet).
  • Natural language communication (text & voice).
  • Texts & documents generation.
  • Creative content creation (images, video, audio, etc.)
  • Deep analysis & insights mining.
  • Smart automation of repetitive tasks.

Reasons to use AI assistants

  • Improve productivity
    AI assistants implementation can raise productivity up to 130% depending on activity type.
  • Improve quality
    AI can improve output quality and efficiency by using vast amount of pre-collected knowledge.
  • Less time on education
    "Experience" is already available. AI assistants implementation enables business to spend less time on employee education and get them to work faster.
  • Improve corporate knowledge
    AI accumulates experience while performing tasks. That leads to significant volume of new knowledge for business which did not exist before.

What might AI assistants look like

Today, there are various types of AI assistants, including corporate chatbots, integrates, and autonomous AI assistants, each serving specific range of tasks and functions, helping companies increase efficiency and automate routine processes. These assistants leverage artificial intelligence technologies to enhance productivity, streamline workflows, and improve user experiences.
Corporate chatbots are AI-powered virtual assistants designed to enhance communication and efficiency within businesses (well-known GPT-like user interface with web-based chat window to interact with AI assistant). These intelligent bots are programmed to engage with employees, customers, or stakeholders through chat interfaces, providing instant support, answering inquiries, and automating routine tasks.
  • 24/7 Availability
  • Multichannel support & scalability
  • Cost savings by reducing human work
  • Personalize interactions based on user preferences
  • Data Collection and Analysis
  • Consistent responses, ensuring unified communication
Integrated AI assistants are multifunctional artificial intelligence tools that can be easily integrated into existing corporate software to enhance the user experience for employees. These assistants utilize advanced algorithms and natural language processing (NLP) to perform tasks such as scheduling meetings, managing calendars, analytics, and generating personalized recommendations.
  • Seamless integration with corporate systems
  • Personalized recommendations and responses
  • Automation of repetitive tasks
  • Enhanced User Experience
  • Scalability to accommodate evolving business requirements
  • Enhancing decision-making with data analysis
Autonomous AI assistants are advanced artificial intelligence systems capable of operating independently to perform tasks and make decisions without constant human oversight. They utilize machine learning algorithms, natural language processing, and other advanced technologies to understand and solve complex problems. Some tasks can be accomplished without human involvement — in such cases AI assistant may be seamlessly integrated into corporate platforms.
  • No human employees involved
  • Integrated into existing corporate software
  • Automated quality & performance control
  • No changes in existing business workflows
  • Based on corporate and domain knowledge
  • Wide range of integration scenarios
Possible areas of implementation
  • Automated data quality assurance
  • Customer documents processing
  • Automated up- and cross-sales
  • Recommendations & customer self-service
  • Automated order processing
  • Transactions analysis & fraud prevention
  • No-human customer support messaging
Possible areas of implementation
Autonomous AI assistants optimize document processing and customer interactions, providing recommendations and support without the need for manual intervention. AI conducts transaction analysis and effectively strengthens company security measures by preventing fraud.
Basic process of typical AI implementation
Average AI assistant implementation from early idea to production stage within 3-5 months.
  • 1
    Preliminary business needs discussion
    Understanding the goals and state of the client's business. We provide insights and examples of how AI can solve these issues. Usually held in form of 1-2 conf-calls or offline meetings.
    Outcome: analytical paper/detailed proposal.
    Terms: 1 week.
  • 2
    Exploring existing corporate knowledge
    Analysis of existing corporate documents templates, formats & general data workflow. Preparing data retrieval framework, experiments & quality evaluation.
    Outcome: ready-to-use data retrieval framework (libraries, tools, etc.)
    Terms: 2 weeks.
  • 3
    Model selection & training
    Set of experiments to choose appropriate AI models depending on business task & corporate requirements. Making decision on most-effective training model. Preparation of training datasets. Models deploy & training.
    Outcome: deployed & trained ai models.
    Terms: up to 1 month.
  • 4
    Building a pilot AI assistant
    Launch of a pilot AI assistant based on trained and prepared models to test with business end users, probably – within existing business processes.
    Outcome: pilot corporate ai assistant (web chatbot).
    Terms: 1 week.
  • 5
    Ai assistant tests
    Testing of pilot AI assistant, obtain feedback from beta end-users, revise quality & speed (may require to re-train models).
    Outcome: QA report, proven ai models.
    Terms: 2 weeks.
  • 6
    Production launch
    & integrations
    Development & integration of production AI assistants into corporate workflow, deployment & QA.
    Outcome: set of ai assistants fully integrated into real corporate workflow.
    Terms: up to 1 month.
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AI assistant for your business

Datalytica team will help identify specific applications of AI assistants tailored to address the key tasks of your business. Our AI assistants help in automating customer interactions, improving internal workflows, and enhancing decision-making efficiency.
Diagnosis & pathologies detection
AI can analyze images (x-ray, CT, MRI, etc.) And recognize pathologies, speeding up the work of doctors and making their lives easier.
Disease forecasting
AI assistants can compare large amounts of patient data and predict the likelihood of diseases occurring. This allows for timely intervention and resource allocation.
Automation of laboratory processes
AI can speed up the process of sample analysis and testing in medical laboratories. Ai-controlled robotic systems can handle tasks such as sample sorting, pipetting, and sample preparation.
Patient monitoring
AI health tracker monitoring the patient's condition (data collected from devices on the person's body), issuing warnings about critical conditions, and triggering emergency assistance.
Telemedicine service
AI-powered chatbots can be used to provide instant responses to common questions from patients and streamline communication, make appointments.
Psychological scoring
The main task of ai scoring in the field of healthcare is segmentation of the client base in order to optimize marketing activities and increase their effectiveness.
Adaptive learning
AI analyzes students' progress and difficulties, providing additional materials and exercises for better understanding.
AI-generated learning materials
AI generates summaries and creates new outlines on various topics. For teachers, this aids in lesson planning, schedule management, and handling inquiries.
Tutoring chatbots
AI-based chatbots provide instant support and explanations to students on specific topics, acting as virtual mentors.
Assessment and testing trends
AI algorithms can automatically grade objective questions (multiple-choice, true/false), as well as analyze written responses against predefined rubrics (essays and open-ended questions).
Curriculum alignment
AI analyzes global education trends and curriculum changes, helping educational institutions stay updated and align their offerings with evolving standards.
Sentiment analysis
Early intervention for mental health: AI analyzes written content, such as essays or forum posts, to identify signs of emotional distress, enabling early intervention and support for students' mental health.
Demand forecasting
AI analyzes historical sales data, market trends and other factors to generate a forecast. This helps service providers optimize inventory levels, reduce stockouts and improve overall supply chain efficiency.
Paperwork automation
AI is used for text and image recognition to automate paperwork - automatic recognition of checks, receipts, invoices, contracts, etc.
Chatbots and virtual assistants
AI-powered chatbots can be used to provide instant responses to citizen queries and streamline communication, collect opinions and influence citizens' sentiments.
Price optimization
AI algorithms analyze market conditions, competitor pricing, and consumer behavior in real-time. It helps retailers to optimize pricing dynamically to match changing market conditions.
Personalized product offers
AI may help in generating personalized recommendations for clients by analyzing data about past purchases and preferences. Cross and up-sale to existing clients via CRM.
AI fraud management
AI systems integrate with payment gateways to assess transaction risk factors and detect potentially fraudulent payments. It also may use facial recognition technology.
Internal chat-bot for employees
Internal chat assistant integrated into corporate messaging platforms providing employee access to business data, regulations, reports and forecasting capabilities.
Product definition & pricing
Insurance product invention & specification by means of market, competitors and customer feedback analysis.
Improved risk inspection, analysis & forecasting
Company-wide risk management based on previous knowledge, current portfolio, market regulation and domain knowledge. Recommendations & automated deal parameters change.
Automated claims management
AI assistant to process claims in autonomous mode, including claims data retrieval, pre-decision making, request for additional data and final set of document preparation.
Automated sales execution & underwriting
AI assistant to execute full process of insurance product sales & client underwriting, including price definition, risk measurement & documents processing.
Account & contract management
Automated management of account relations, contract extensions & changes depending on past experience, generation of documents, ai-based cross and up-selling.
Route optimization
Optimization of logistics routes based on cost, timing and available transportation options. AI assistants continuously monitor real-time data and can dynamically adjust routes in response to unexpected events.
Warehouse optimization
AI analyzes historical sales data, market trends and other factors to generate an accurate forecast. This helps service providers optimize inventory levels, reduce stockouts and improve overall supply chain efficiency.
Defect detection
AI may help in product inspection and defect detection processes. It analyzes product images and can identify defects (cracks, dents, changes in color, size), even those that may not be visible to the human eye.
Chat-bot for customers & employees
AI-powered chatbots improve customer experience by providing real-time updates on shipments, answering queries, and facilitating communication between logistics providers and customers.
Documents & reports generation
Automated preparation of the necessary reports for regulatory organizations in accordance with the law. Formation of accompanying documents for cargo and customs clearance documents.
Cross-border compliance
Global trade regulations: ai assists in navigating complex international trade regulations and customs requirements, ensuring compliance and reducing the risk of delays and penalties.
Chatbots and virtual assistants
AI-powered chatbots can be used to engage with users on websites or mobile apps, answering questions, guiding users through processes, and facilitating routine interactions.
Client finance management
AI assistants can analyze users' financial data to offer personalized financial planning advice, including budgeting, saving, and investment recommendations.
Smart onboarding
Automatic analysis of the documents provided, verification and validation, assessment of solvency, drawing up a risk profile, generating a service agreement with the appropriate parameters.
Demand forecasting
AI analyzes historical sales data, market trends and other factors to generate a forecast for banking products and services. This helps finance organizations to plan the workload and marketing activities.
Documents & reports generation
Automated preparation of the required reporting for higher authorities and regulatory organizations in accordance with legislation, recommendations, and other requirements.
Product definition & pricing
Creating new financial products based on an analysis of the organization's audience and its characteristics, analysis of competitors and regulatory requirements.
Documents & reports generation
Preparation of analytical and reference documents based on discussion materials, technical specifications, tasks in task trackers, and source code.
Network design and planning
AI assistants analyze network requirements, traffic patterns, and performance metrics to automatically generate optimized network topologies that minimize latency and enhance efficiency of work.
Performance analysis
Automated analysis of performance metrics (code commit frequency, issue resolution time), comparing team performance to industry benchmarks to provide insight into areas that may need attention.
Resource planning
AI assistants help in streamlining processes, optimizing resource allocation, and improving overall project efficiency. AI algorithms can distribute tasks among team members, considering their current workload.
Code lint & generation
Automatic analysis and checking software code for errors and inconsistencies. Automatic code generation based on technical specifications and analytical materials.
Automated project estimation
AI-powered projects estimation in terms of cost and implementation time, depending on the goals and objectives, tools used and available resources.
Documents examination
Examination of documentation for government contracts to ensure compliance with regulatory documents, recommendations, and legislation.
Anomaly detection
AI algorithms can analyze large data sets to identify irregular patterns or anomalies that may indicate potential cases of corruption.
Predictive police service
AI algorithms analyze historical data to predict crime hot spots, allowing law enforcement to allocate resources more effectively.
Performance analysis
Analysis of the government performance depending on target indicators and citizen satisfaction. Natural language processing (NLP) algorithms analyze public feedback and identify areas that require attention.
Documents & reports generation
Automatic preparation of procurement and tender documentation for projects. Automated preparation of the required reporting for higher authorities and regulatory organizations.
AI fraud management
AIenhances the analysis of cybersecurity threats and vulnerabilities, improving the public sector's ability to safeguard sensitive information and systems.
Big Data Analytics

© 2017 Datalytica
  • Mathematical modeling
  • Analytics
  • Custom software development
  • Data management
  • Recommender system
  • Fraud detection
  • Phycological scoring
  • Fault prediction
  • Preventive Maintenance
  • Churn prediction and customer retention
  • Warehouse optimization
  • HR analytics
  • Chat bot and text analysis
  • Fuzzy search and knowledge base
  • Lead generation
  • Image recognition