eltyoAI agents connected to your business context
Finding the right procedure, piecing together a conversation and preparing a reply all take attention before the substantive work begins. A custom assistant gathers the useful information and prepares a next step your team can check.
We start with a specific task and the sources you choose. An assistant does not need access to everything to be useful. Its information access, responsibilities and human owner are defined from the outset, with the people doing the work and the relevant technical teams. This gives everyone a shared understanding of what the assistant is there to do.
Plug-and-play agents or custom development: where should you start?
Eltyo is both an AI software publisher and a development agency. Our plug-and-play agents provide a starting point when their features and connections match your use case. We review access, configuration and operating limits with you before they enter use.
When the task calls for a specific integration, business rules or a new workflow, we build a custom solution. The two approaches can work together: start with an existing agent and adapt the parts your work requires. Explore our two offers to place your project.
Choose a configurable product, custom development or a hybrid approach
Plug and play still requires preparation. An existing agent needs suitable sources, scoped permissions, configured rules and checks on its output. The useful question is how much of your work the product already supports, and what needs to change.
Scroll across the table to compare all three approaches.
| What to assess | Plug-and-play agent | Custom development | Hybrid approach |
|---|---|---|---|
| The task | A use case covered by the product | A specific workflow or business rules | A covered use case with a step to adapt |
| Connections | Available connections checked for your tools | An integration to design where interfaces allow it | Existing connections extended where needed |
| Data | Compatible sources to prepare | Formats and processing to define | An existing foundation with additional sources to check |
| Review | Configurable controls to test | Approval steps to design | Existing controls with additional rules |
| Ongoing support | Configuration and product update monitoring | Maintenance of custom components and integrations | Clear responsibility for the product and its extensions |
These pointers do not replace checking the actual product and tools. A missing connection, difficult source material or unsuitable controls can change the decision. An AI opportunity review helps clarify those points before selecting an approach.
What helps scope your first AI agent
A useful first brief can begin with four answers:
- The task: what triggers it, the current steps and the expected result.
- The context: the tools involved, available sources and permissions to check.
- The limits: permitted actions, approval steps and who handles exceptions.
- The measure: current end-to-end time, expected quality and costs to compare during a trial.
We then clarify the scope, the work that stays manual, the test cases and the support required. Missing information becomes an issue to resolve, rather than an assumed capability. Our guide to scope, deliverables and budget for a first AI project helps prepare that conversation.
Prepare, connect and move work forward
Depending on the available connections, the assistant can retrieve information, create a draft or prepare an action in your software. Its level of involvement follows the task and the checks you agree.
- Find a procedure and show which document it used.
- Summarise a file and highlight points that need checking.
- Draft a reply using the context of a customer request.
- Propose an update to a record in your sales software.
- Identify missing information before passing a file to the next person.
These examples help define your scope. The selected capabilities are tested with your information and tools before they become part of everyday work.
Build with the people who will use it
We gather representative cases, including situations where information is missing or contradictory. Your team defines a useful answer, the mistakes to look for and when a person needs to take over. Trials help improve the assistant, its sources and its review steps.
Onboarding explains where the assistant fits: when to use it, how to check its suggestions and how to report a problem. Feedback becomes a practical starting point for further improvements, rather than a list of issues left for users to work around.
Grow what works
We track quality, preparation and review time, along with the exceptions encountered. This helps identify where the assistant adds value and where its role should change. Each new use case gets its own rules and tests.
An AI opportunity review can help choose the first task, while agent oversight establishes how the work will be checked as usage grows.
To prepare for everyday use, explore the steps from prototype to production and the AI agent oversight checklist.