Service / 05
AI assistants and automation
We integrate AI into business processes, building assistants and automation systems for customer service, content, data and internal tasks.
Discuss your task ↗Capabilities
What the solution includes
- 01AI assistants and chatbots
- 02Documents and knowledge bases
- 03Content generation and processing
- 04Automation of repetitive processes
- 05Data analysis and processing
- 06AI model integration into existing products
- 07Automated workflows and action chains
01
Where AI can support business operations
AI is useful where teams repeatedly process text, enquiries, documents or structured and unstructured data.
- 01Handles common customer questions
- 02Finds information in documents and knowledge bases
- 03Drafts and edits content
- 04Structures conversations, tasks and decisions
- 05Analyses and transforms data
- 06Triggers agreed sequences of actions
02
AI solution development scope
We begin with a testable process and place AI inside a clear operating workflow.
- 01Task and data-source analysis
- 02Conversation or workflow design
- 03AI model integration approach
- 04Backend and user interface
- 05Integration into an existing product when required
- 06Response and edge-case testing
03
Data sources and integrations
The AI layer can work with existing channels and systems when they provide suitable technical access.
- 01Telegram bots and web interfaces
- 02Documents and knowledge bases
- 03CRM and internal services
- 04External AI models and APIs
- 05Automated workflows
- 06History storage and administration tools
04
AI implementation process
- 01
Discovery
We clarify the business objective, audience and requirements for the AI solution.
- 02
Design
We map the structure, user journeys and required connections.
- 03
Implementation
We build the product and connect the agreed functionality.
- 04
Quality assurance
We test core journeys, responsive behaviour and data handling.
- 05
Launch
We deploy the solution to its working environment and verify availability.
05
What affects AI solution cost
The estimate covers data and output quality as well as interfaces and connected systems.
- 01Number of AI journeys
- 02Source-data format and volume
- 03Knowledge-base retrieval requirements
- 04Integrations and automated actions
- 05Interfaces, roles and operation history
- 06Quality checks and exception handling
06
AI and automation projects
Real studio tools for speech, conversation analysis and focused monitoring.
TELEGRAM BOT / AI
VoiceText AI
A Telegram bot for transcribing voice messages and AI-powered text processing. It converts voice to text, lets users edit and improve results with AI, translate text and retain message history.
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AI / Automation
KarmaCraft
A Reddit and Hacker News monitoring tool that prepares relevant AI-generated comments.
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AI / Productivity
AI Chief of Staff
A Telegram assistant that analyzes conversations and identifies tasks, decisions and agreements.
View case ↗FAQ
AI automation FAQ
Which processes are suitable for AI automation?+
Start with repeatable tasks that have clear inputs and outcomes, such as handling enquiries, documents, content or data.
Can the solution use company documents?+
Yes, when their format and access rules allow secure processing and retrieval.
Does AI replace our CRM or other systems?+
Usually not. AI complements the workflow and exchanges data with existing systems through available integrations.
Can AI be added to an existing product?+
Yes, when the product architecture and connected services provide the required access.
How do you verify response quality?+
Before launch we define target journeys and test outputs, constraints and cases where the available information is insufficient.
What determines the estimate?+
Journeys, data sources, models, interfaces, integrations and output-control requirements.
Let’s find a practical AI use case
Describe the repeatable process, available data and expected outcome, and we will assess where automation adds value.
Send an enquiry ↗