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ENUA
  1. Services
  2. /AI & Intelligent Automation
  3. /AI agents and assistants

AI AGENTS & ASSISTANTS

AI agents and assistants for your workflows.

We build assistants that understand a request, find the relevant information and carry out agreed actions in your systems. Each workflow defines what the agent can handle and when your team takes over.

Discuss your AI agent→Explore a workflow→

Start with one workflow and a clearly defined outcome.

Illustration of an AI agent connecting a request, workflow steps and operator review.

Where an assistant can take on work

A useful scenario has a specific task, accessible information and a clear completion point.

  • Support with context

    The assistant clarifies a request, reads the permitted support history and prepares a reply. When the case needs judgment, it hands over the facts it has gathered.

  • First-contact sales assistance

    It gathers a prospect’s needs, explains your offer using current materials and prepares a record for the salesperson. Prices, discounts and commitments stay within agreed rules.

  • Internal team requests

    It gathers information, prepares a task or starts an approved workflow. Employees can see what has been completed and which decisions still need their input.

A WORKFLOW IN PRACTICE

From a request to an approved action

This example shows an assistant preparing an internal task. Action and approval boundaries are tailored to your process.

Illustrative scenario. No AI calls or real actions are performed.

Request received

Prepare a task for the account manager

“The customer needs two more users. Gather the context and prepare a task for the account manager.”

Request received

“The customer needs two more users. Gather the context and prepare a task for the account manager.”

Draft ready

The assistant finds the customer record and account owner. In this example, its permission covers reading that information and preparing a task draft.

Awaiting human approval

The draft includes the customer’s request, owner and record reference. Creating the task requires confirmation. The assistant does not add users or change billing.

Illustrative completion path

In the implemented workflow, approval permits task creation. The result and any integration error are recorded. This demonstration does not create a task.

  1. 01 · Request

    Prepare a task for the account manager

    Request received

    “The customer needs two more users. Gather the context and prepare a task for the account manager.”

  2. 02 · Context

    Relevant information gathered

    Draft ready

    The assistant finds the customer record and account owner. In this example, its permission covers reading that information and preparing a task draft.

  3. 03 · Approval

    The team reviews the draft

    Awaiting human approval

    The draft includes the customer’s request, owner and record reference. Creating the task requires confirmation. The assistant does not add users or change billing.

  4. 04 · Outcome

    After approval, a traceable action

    Illustrative completion path

    In the implemented workflow, approval permits task creation. The result and any integration error are recorded. This demonstration does not create a task.

The assistant proposes an action; the application checks permissions and execution rules.

What goes into your AI agent

We choose the components around your workflow, channels and available systems.

  • Context and sources

    Connect approved materials and data, with clear rules for freshness and how they can inform a response.

  • Actions in your systems

    Design API access for specific operations: retrieve a status, prepare a record or create a task after approval.

  • Conversation continuity

    Retain useful conversation context within agreed boundaries so users do not have to repeat the same explanation.

  • Human handoff

    Pass the request on with its context, completed steps and the reason a person needs to take over.

  • Scenario evaluation

    Evaluate common requests, ambiguous instructions, missing information and tool failures against an agreed set of examples.

  • Activity and usage visibility

    Record action outcomes, errors and model usage, giving the team a practical basis for oversight and improvement.

The task determines the level of autonomy

Some workflows need a prepared answer. Others need tools, multiple steps and approval before changes are made.

  • Answer

    The assistant explains information from permitted sources and asks clarifying questions.

  • Prepare

    It prepares a message or record that an employee can edit before using.

  • Carry out an approved action

    It acts within permitted operations; changes above an agreed risk threshold require confirmation.

Three assistant modes: an answer, a draft and an approved action.

Experience in workflow automation

AI automation platform for workflows — frame from the Draxon case study

AI automation platform and workflow system

Draxon’s portfolio includes a platform with intelligent intake, workflow orchestration, integrations and an operator workspace. It demonstrates experience connecting AI to operational processes.

View the case study→

How we launch a working assistant

Each stage produces something the team can review and agree on.

StageWhat we doWhat you receive
  1. 01

    01. Choose the first workflow

    Define the requests, accountable owner and completion criteria. Identify steps that can be handled by ordinary automation rules.

    An agreed workflow and completion criteria.
    An agreed workflow and completion criteria.
  2. 02

    02. Design the workflow

    Specify tools, information, permissions, approvals and handoff. The result is a clear description of the assistant’s behavior.

    A workflow map with approvals and human handoff.
    A workflow map with approvals and human handoff.
  3. 03

    03. Evaluate a prototype

    Run examples in a test environment, investigate failed responses and estimate usage costs per workflow.

    An evaluated prototype and test findings.
    An evaluated prototype and test findings.
  4. 04

    04. Connect operational systems

    Add agreed integrations, error handling and activity logs. Check that retries do not trigger unintended duplicate actions.

    Working integrations and activity logs.
    Working integrations and activity logs.
  5. 05

    05. Launch and observe

    Start with an agreed user group, collect feedback and extend the workflows based on observed behavior.

    A pilot release and an improvement plan.
    A pilot release and an improvement plan.

ESTIMATE

What we need to scope the work

Show us one typical workflow and a few representative requests with unnecessary personal information removed. We will use the discussion to define the pilot scope, dependencies and estimation approach.

Discuss your AI agent→
  • Task and boundaries

    What should be complete at the end, and which decisions require human input?

  • Systems and access

    Where is the information, which APIs are available and who can approve access?

  • Volume and channels

    Where do requests arrive, how many are there and what response times matter?

  • Quality criteria

    Which outcomes count as success, and when should a person take over?

QUESTIONS & ANSWERS

Questions about AI agents and assistants

Multi-step tasks, tools, approvals and human handoff. This page does not replace the separate services for knowledge search, document processing or in-app CRM assistance.

Questions and answers

A chatbot mainly supports a conversation. An agent can select and carry out steps using permitted tools. A stable process may only need an assistant with a predefined workflow; we choose the approach after examining the task.

Yes, when the system provides a suitable API or another agreed integration method. We first check available operations, permissions and constraints. Reading data and changing records need separate rules.

Not necessarily. An existing model combined with relevant sources, tools and evaluation is often sufficient. Model and deployment choices depend on the information, response quality, latency and budget.

We design checks before changes, limits on available actions and human handoff. Missing information and integration failures are tested separately. No model guarantees error-free answers, so quality is evaluated on your scenarios.

Yes. You can begin with an internal workspace or one inquiry channel. The first release helps validate the workflow and handoff rules before broader rollout.

Development cost depends on workflow complexity, integrations, the operator interface and evaluation. Ongoing cost depends on model usage, data volume and workload. We separate these elements in the estimate.

We agree which materials, workflows or settings your team can update. Behavioral changes are checked against a reference set before release to protect existing workflows.

Describe one workflow, the people involved and its difficult manual steps. Together we identify where AI is useful, which information is missing and which initial outcome to test.

Related work

  • AI features inside your CRM→

    Summaries and drafts within the interface your team already uses.

  • Document and inquiry processing→

    Structured inputs for the next workflow step.

  • Intelligent search→

    Find answers across approved company sources.

LET’S DISCUSS YOUR WORKFLOW

Which task would you likean AI assistant to handle?

We will explore the workflow, required information and action boundaries, then identify a useful first scenario to test.

Discuss your AI agent→All AI services→