Lyron
AI agent & shared inbox

AI email assistant for shared inboxes

The assistant prioritises incoming email, identifies the request, retrieves approved information and prepares traceable reply drafts for your team.

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Review practical examples and time potential

Privacy considered Explicit approvals Documentation included
Current situation

Shared inboxes grow faster than the team

Messages sent to info@, service@ or orders@ must be read, understood, routed and often answered with information from several systems.

Static rules can recognise senders or keywords but not reliable context. An AI email assistant handles the preparation without sending uncontrolled answers.

The solution

AI prepares the work while your team stays in control

The assistant classifies intent and urgency, extracts relevant data and uses approved sources to prepare a reply. Sending and system actions follow your approval rules.

Prioritise and route

Intent, customer group, deadline and owner are inferred from the message and context.

Retrieve information

CRM, knowledge, order status and policies are queried only through approved access.

Prepare replies

The assistant drafts a response and internally references the facts and sources used.

Control approvals

Sensitive or uncertain cases stay with people; only defined routines may run automatically.

How the workflow operates

From input to a reviewed result

Every step has a clear trigger, defined data and a traceable handoff. Exceptions are surfaced and routed to people instead of being hidden.

  1. 01

    Understand email

    Sender, intent, urgency and required action become structured data.

  2. 02

    Load context

    The assistant reads only approved CRM, knowledge or operational data.

  3. 03

    Prepare draft

    A reply, summary and suggested next action are generated.

  4. 04

    Review or execute

    Depending on risk, the message is approved, automated or escalated.

Systems & interfaces

Designed for your existing tool landscape

Production automations use separate API or approved enterprise access. Personal ChatGPT and Claude subscriptions do not include API usage and are not used as unattended production accounts for sensitive business inboxes.

Additional systems can be connected through available APIs, webhooks, file exports or controlled intermediate storage.

Microsoft Outlook Gmail HubSpot Dynamics 365 SharePoint n8n
Control & governance

Automation with explicit boundaries

Approved sources

The assistant only searches systems and documents allowed for the specific use case.

Risk-based approval

Pricing, complaints and legal topics can receive stricter review rules.

Privacy by design

Data flows, providers, retention and roles are documented before launch.

Implementation

Start small, test real cases, hand over cleanly

We begin with a limited process and real examples. Production scope grows only after rules, exceptions and ownership work reliably.

  • Process workshop and target design
  • Pilot with real cases
  • Acceptance, monitoring and documentation
  • 30 days of post-launch support
Frequently asked questions

What teams want to know before starting

Can the assistant send fully automatic replies?
Yes, but only for narrow routines with reliable data. Sensitive, ambiguous or high-value requests should keep a review step.
Can we use our ChatGPT or Claude subscription?
Chat subscriptions and API platforms are separate products. A stable integration uses separate API or approved cloud access; personal chat accounts should not be a production interface for confidential inboxes.
Does the AI read the entire mailbox?
Not necessarily. Access can be restricted by folder, label, recipient, time range and specific data fields.
How do you prevent fabricated replies?
The assistant gets approved sources, explicit response boundaries and uncertainty thresholds. When evidence is missing it should ask or escalate, not guess.
Which inbox should we start with?
Good candidates contain recurring requests with clear ownership and reliable data, such as order status, scheduling, document requests or internal service questions.
Related solutions

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Practical guide

Where AI email assistant creates value in everyday work

The assistant sorts email, detects intent, researches approved knowledge and prepares traceable replies or next steps.

Three concrete operating scenarios to compare with your own process.
01

Prioritise the inbox

Intent, customer, urgency and responsible team are detected from content and context.

02

Prepare replies

Approved information is combined with sources into a reviewable draft.

03

Update business records

Tickets, CRM or tasks receive the relevant data without manual re-entry.

A strong fit when …

Recurring requests can be answered from approved knowledge while uncertain cases are handed to people with clear context.

  • You handle recurring emails using repeatable rules.
  • The intake, target system and accountable business role can be named clearly.
  • Exceptions are allowed to remain visible and move to people deliberately.
Transparent potential estimate

Estimate time savings with your own volume

The calculator uses 5 minutes today and 2 minutes after automation as fixed example assumptions. It does not replace process analysis.

Illustrative estimate based on the visible assumptions — not a guarantee.

55Hours per month
660Hours per year
Additional measures after launch Handling time Escalation rate Source coverage
Content reviewed on 26 July 2026 About Lyron AI

Which emails consume the most time every day?

We analyse categories, sources and risk and define a first assistant that creates measurable relief while staying controllable.

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