More time for your team.
Repetitive work handled by AI.
AI agents and automation
A team of AI agents built around your business
We build solutions around specific processes: customer enquiries, quotations, documents, company knowledge and operations. An agent can organise information, draft responses and carry out approved actions in connected systems. We define its tasks, data access and level of autonomy.
We design the interface, logic and integrations in custom code. We can connect several specialised agents within one process or start with a single use case. Your CRM, ERP, store, email and document repository can stay where they are if suitable integration methods are available.
Use cases
Choose the process you want to improve
AI agent for B2B sales
The agent supports finding and organising companies that match an agreed customer profile. It combines information from permitted sources, removes duplicates and prepares context for a salesperson. We design it to support your sales process with clear rules for data use.
Explore this use caseAI agent for quotations
The agent reads an enquiry, compares it with a price list or catalogue and prepares a draft quotation. It can identify missing information, compare options and create a document in an agreed format. Calculation rules are kept separate from text interpretation.
Explore this use caseAI agent for documents and contracts
The agent helps read documents, compare versions and find specified information. It can prepare a table of deadlines, obligations and missing attachments or compare a contract with an agreed checklist. Each finding should link to a specific source.
Explore this use caseAI agent for company knowledge
The agent combines document search with answers to team questions. It helps find a procedure, decision or project detail and identifies the sources used. Knowledge stays linked to its version and the recipient’s permissions.
Explore this use caseAI agent for marketing
The agent supports topic planning and content drafts based on brand materials. It can create message variants, adapt formats and organise a schedule. Creative direction, factual accuracy and approval remain part of the editorial process.
Explore this use caseAI agent for warehouse operations
The agent helps monitor stock, turnover and discrepancies between systems. It can prepare shortage alerts, summaries of unusual changes and proposed next actions. Calculations use current data and agreed business rules.
Explore this use caseAI agent for customer support
The agent answers questions about your offer and procedures using approved knowledge. It can collect enquiry context, help identify the next step and prepare a case for a consultant. We also define when it should stop answering independently.
Explore this use caseAI agent for company checks
The agent supports collecting company information from agreed registers and sources. It organises identifiers, statuses and discrepancies, recording when each check was made and where the data came from. The report helps your team conduct its own assessment.
Explore this use caseDeployment and development
We review the current workflow, information sources and repetitive tasks. We select a use case, define the expected outcome and agree how to measure quality.
We build an initial version and test representative examples, including missing data, incorrect responses and situations that require a handover to a person.
We connect the agreed systems, configure roles and permissions, and build error handling. We roll out in stages with a way to stop automated actions.
We monitor errors and usage costs, update knowledge sources and improve behaviour based on results. Support and further changes are scoped in the proposal.
From audit to everyday use
Data and integrations
APIs, CRM and ERP in one workflow
An agent can read data from one system and prepare work for another, from an enquiry through a quotation to a record update. We design integrations after reviewing available APIs, permissions and provider limitations. Actions such as sending a proposal or changing records can require approval from a designated person.
AI agents and automation
Private AI and controlled access to knowledge
We choose the deployment model around your requirements: your own infrastructure, an agreed cloud environment or a hybrid setup. Before launch, we establish what data reaches the model, where it is processed and stored, and who can access it. Local and external models have different hardware requirements, costs and capabilities.
Output and oversight
Know what the agent did and why
The design includes access rules, an activity log and handling for uncertainty and errors. When an answer relies on documents, the agent should identify its sources. If information is missing, it should report the gap instead of guessing. Decisions with significant consequences remain within the agreed approval process.
Questions and answers
Before you introduce AI into your business
A chat primarily supports conversation. An agent receives a defined task, context and tools. It can handle several steps in a process, but its access and autonomy are designed individually.
Not necessarily. We first assess integration with your existing systems. Replacement may only be needed if their limitations prevent the agreed workflow.
We can design for that requirement. It involves selecting a suitable model and infrastructure and checking every connection. Not every deployment option processes data locally.
The price depends on the process, data, integrations and requirements. We separate implementation costs from estimated infrastructure, model and maintenance costs. Usage limits are agreed before launch.
We test difficult cases, limit permissions and design handovers to people. Approval thresholds, retries and process stops are possible. The model itself does not guarantee error-free results.
Only within the agreed scope. We can begin with drafts and recommendations, then enable selected automated actions after testing and approval of the rules.
A process description, sample data and information about your systems. Anonymised examples are sufficient for initial discussions. Access to production data is arranged separately.
Yes, where the architecture and available integrations support it. We plan further development around additional workflows, reuse proven components and test new permissions separately.
Which process would you like an AI agent to handle?
Thank you for sending the brief!
Your project manager will carefully review the submitted information and contact you as soon as possible. We value your time and commitment, and providing the highest quality service is our priority.
Your project contact
Adrian Koziński
+48 791 141 047
