We design AI assistants and agents connected to data, documents, CRM, ERP, portals and internal procedures. The goal is to increase productivity, reduce manual work and turn artificial intelligence into an everyday operational tool.
It means designing intelligent systems that do not remain isolated in a chat, but work inside real flows: they read documents, query data sources, support operators, prepare responses, classify requests and trigger controlled actions.
Emails, tickets, checks, summaries, searches and form-filling consume hours that can be reduced with well-designed agents.
Company knowledge is often distributed across folders, CRM, ERP, databases, files and portals: AI can make it easier to access.
Without rules, permissions, logic and integrations, AI remains only partially useful and does not create stable business advantages.
Not a tech gimmick, but an operational layer designed to increase productivity and continuity.
At I.T.S. Planet we develop custom AI solutions that assist operators, automate tasks, read documents, classify requests, generate controlled content, support decisions and connect with existing business systems.
We define goals, instructions, sources, roles and logic to build agents aligned with business language and procedures.
We create AI flows that help teams complete recurring activities, reduce manual steps and handle exceptions.
We connect AI to CRM, ERP, databases, documents, knowledge bases, APIs and portals already present in the digital ecosystem.
We design limits, permissions, supervision, tracking and usage criteria to keep AI reliable over time.
Every agent starts from a concrete process: a request to handle, a document to read, data to retrieve, a procedure to follow or a decision to prepare.
More productivity, less operational friction. AI becomes a controlled digital teammate: it helps, prepares, suggests, automates and leaves important choices to people.
They answer frequent requests, retrieve information from knowledge bases and prepare responses aligned with company procedures and tone of voice.
They read attachments, extract data, classify cases, generate summaries and help complete repetitive steps.
They support analysis, briefings, follow-ups, reporting, lead qualification and fast data retrieval from CRM or internal systems.
They help produce controlled drafts, adapt text, summarize materials and keep consistency across channels and audiences.
We are talking about intelligent tools designed to understand input, retrieve information, propose responses, trigger actions and support processes in a faster, more contextual and manageable way.
These are components that process language, content, documents or data to classify, generate, summarize or support specific activities.
Useful when you need analysis, interpretation, drafting support or intelligent reading of information.
These are more operational systems that use models, rules and integrations to follow flows, execute steps, query sources and help users complete tasks.
Useful when you need contextual assistance, guided automation or orchestration of recurring activities.
These are the links between the AI layer and business systems, necessary to make the model work on the real data and workflows of the organization.
Useful for making AI concrete, current and genuinely valuable to the business.
We do not start from technology, but from flows where the company loses time: repetitive requests, hard-to-find information, manual steps, redundant checks and low-value activities.
Automatic classification, priorities, response drafts, information retrieval and routing to the right department.
Agents that guide operators through standard steps, check conditions and reduce operational errors.
Reading, summarizing, data extraction, version comparison and preparation of operational sheets.
Customer data search, summaries, follow-ups, qualification support and guided information updates.
Support for event secretariat, guest requests, event FAQs, reminders, reports and check-in workflows.
Preparation of summaries, indicators, anomalies and insights from internal data and authorized sources.
An agent becomes truly useful when it can use up-to-date information and follow the company’s operating rules. That is why we design integrations with existing systems, roles, permissions and tracking.
Explore AI integrationsEach solution is designed starting from users, processes, data sources and real use cases to avoid abstract AI disconnected from context.
The goal is to reduce repetitive work, shorten response times, increase information accessibility and make certain processes more scalable.
We follow a path that starts from the use case and leads to the deployment of a useful, integrated and manageable solution.
We study where AI can generate real value: activities, users, available data, constraints and expected outcomes.
We design prompts, rules, context, information sources and the necessary supervision levels.
We build an initial testable solution to verify output quality, usefulness and process impact.
We connect the solution to company systems and the interfaces needed to make it operational.
We define roles, limits, monitoring and usage criteria to keep the solution reliable over time.
We optimize system behavior based on real use, new data and emerging needs.
The value grows when the solution fits the process, integrates well and is designed to help teams in real daily work.
AI acts on repetitive activities to reduce team workload and speed up operational steps.
Documents, archives and data become easier to query and turn into concrete support.
Integration with existing tools makes the solution more coherent, current and easier to adopt.
A well-designed solution can be monitored, improved and adapted to business change.
A concise view of use cases, data management and validation steps.
Tell us about workflows, data and goals: we can help design a custom AI solution that is useful, controlled and integrated into the systems you already use.
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