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AI & Automation · AI agents

AI agents

Agents take over the preparatory work: they research, prepare, summarise and carry out steps in your systems. With clear boundaries and approvals wherever decisions have consequences.

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01 How you recognise it

Does this sound like your situation?

Three starting points we see regularly. One of them is enough.

  • 01

    Research eats the time before the conversation

    Companies, triggers and decision makers are gathered by hand for every contact.

  • 02

    The CRM is not updated after the conversation

    The notes stay in someone’s head, the fields stay empty, the next step is forgotten.

  • 03

    Offers are made by copy and paste

    The pieces are hunted down in old documents, gaps get overlooked, transfer errors are inherited.

02 What you get

Three results you will notice in daily work.

  • An agent with a clear assignment

    Goal, tools, rules, approval points, logging and measurement are part of the design, not of the repair.

  • Results where your team works

    In the CRM, in the calendar, in the document store. The screen does not change, only the amount of preparation.

  • A test on real, closed cases

    Only when the results convince does the agent get new ones.

03 What it looks like

A bounded assignment.

Schematic example with fictitious data

An agent is only as good as its boundaries. This one prepares CRM maintenance and may do nothing that reaches the outside.

ElementDefinition
AssignmentFor one case, add the missing company details and summarise the status
ToolsRead access to the CRM and an approved company data source, write access only to the draft area
BoundariesNo emails, no meetings, no changes to stage, amount or date
OutputA proposal per field with a source, plus a list of the points without a reliable source
LogEvery run traceable with time, input, sources used and result
ApprovalThe responsible person accepts field by field, nothing is written automatically

Before going live we test ten cases whose correct result we know. What is judged is agreement with the source, not the impression the wording makes.

How do we start?

Ioannis and Tugce Fotiou discussing a process together at the desk
This is how every collaboration starts: with a concrete process on the table, not with a specification document.

When it fits

Tasks stretch across several systems and need the same preparatory work every time.

What a first step delivers

An agent for one clearly bounded assignment, with a log and human approval before any action that reaches the outside.

What we need from you

Approved sources, test access to the systems involved and the rules for what the agent must not do.

We only need these accesses and documents once we start working together. For a first conversation, a short description of your situation is enough.

04 Definition

What an AI agent is and what it is not.

What is an AI agent?

An AI agent is software that pursues a given goal, plans and carries out several steps for it: gathering information, querying systems, producing results, triggering actions. It works within defined rules and approvals.

The difference to a chatbot: an agent does not wait for the next question but works through an assignment. The difference to classic automation: it can handle unstructured input such as emails, documents or web pages and derive intermediate steps itself.

What an agent at FIOXX is not: a system that makes commitments on its own, moves money or communicates externally. Those steps stay with humans.

05 Fields of use

Where agents reliably take work away today.

Six tasks from sales and administration that we implement with agents, with approval at the right points.

  • 01

    Account research

    Analyse companies, find triggers, identify contacts, write the result into the CRM in a structured form, before the sales person takes a first look.

  • 02

    Conversation preparation

    Before every meeting: history, open points, news about the company, relevant references as a compact briefing.

  • 03

    CRM maintenance

    Summarise conversations, derive fields, propose next steps. The human confirms, the agent writes.

  • 04

    Offer preparation

    Assemble building blocks from templates and discovery notes, mark gaps, request approval.

  • 05

    Ticket and enquiry triage

    Classify incoming enquiries, prioritise them, enrich them with context and assign them to the right team.

  • 06

    Document pre-check

    Check incoming documents for completeness and plausibility, request missing details, prepare the case.

06 Anatomy

How a FIOXX agent is built.

Six components every agent has, regardless of model and platform.

  1. 01

    Assignment and goal

    Every agent has a clearly stated task with a defined result: “prepare the customer meeting on Thursday”, not “help sales”.

  2. 02

    Tools

    Access to exactly the systems and sources needed for the task: CRM API, document search, web research, calendar. No more.

  3. 03

    Rules and boundaries

    What may the agent read, write, trigger? Which thresholds apply? Rules are part of the design, not of the repair.

  4. 04

    Approval points

    At defined points the agent stops and presents its result to a human, always before actions with an external effect.

  5. 05

    Log

    Inputs, sources used, intermediate steps, result and approval are logged. Every decision can be traced.

  6. 06

    Measurement

    Time saved, quality of results, share of corrections: the benefit is measured, not claimed.

07 Guardrails

Security is part of the design.

  • 01

    Minimal permissions

    The agent works with its own, tightly bounded access, never with a person’s full access.

  • 02

    A test on real cases

    Before going live the agent runs on real but closed cases. Only when the results convince does it get new ones.

  • 03

    A human in the loop

    Approvals are not optional. Where they get in the way of daily work, the process is cut wrongly, not the approval superfluous.

  • 04

    Stop criteria

    Unclear data, contradictory sources, unexpected answers: the agent stops in a controlled way and hands over instead of guessing.

08 Next

Agents need processes and systems.

An agent is only as good as the process it works in and the data it can reach. That is why process automation, a clean CRM and, where needed, our own interfaces are part of the project.

Process automation Article: AI agents in sales

09 FAQ

Common questions about AI agents

Can an AI agent make mistakes?

Yes, like every system and every human. That is why we build agents so that mistakes become visible early: with approvals before actions, logs and stop criteria. The difference to uncontrolled automation is not the absence of errors but traceability.

Which AI models does FIOXX use?

We decide that per use case by data protection, quality, cost and operating model. For many tasks hosted models with contractual assurances are suitable; where data must not leave the building, self-operated models are an option. The architecture is built so that models stay exchangeable.

Does an agent run inside our existing systems?

Yes. Agents access CRM, ERP, document storage or calendar through interfaces and write results back there. For your team the screen does not change, only the amount of preparatory work they have to do themselves.

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Next step

Which preparatory work costs your team time every day?

Research, preparation, summaries, maintenance: let us pick one concrete case, design an agent for it and measure the effect.

Request a first conversation info@fioxx.com