AI shared inbox for support agencies
Keep client work separated while AI handles the routing and reply prep.
Key takeaways
- Separate client queues, labels, and knowledge sources so context does not blur.
- Standardize intake and reporting without forcing every client into the same process.
- Use AI drafts to speed up repeat replies while senior agents handle tone, exceptions, and escalations.
Built for agency workflows
Agency support is a context-switching problem. One team may handle several brands, each with its own policies, tone, SLA expectations, and escalation contacts. Protodesk keeps the work organized so agents can move quickly without mixing client context.
What to standardize for each client
- Channel setup: which email addresses, WhatsApp numbers, and chat widgets belong to the client.
- Ownership rules: who handles billing, product, VIP, refund, and escalation tickets.
- Knowledge base scope: approved policies, product details, macros, and escalation language.
- SLA targets: first response, follow-up, and resolution expectations by priority.
- Reporting cadence: weekly operational review and monthly client summary.
How AI helps without weakening quality control
Agencies cannot let automation improvise on behalf of a client. Use AI for preparation first: triage, summaries, suggested replies, and safe auto-resolve where the answer is documented and low-risk.
- Keep brand tone in saved examples and approved knowledge base articles.
- Review sidekick drafts before sending, especially early in a client relationship.
- Limit auto-resolve to routine questions with clear policy sources.
- Escalate legal, refund, VIP, and angry-customer threads to senior agents.
Client reporting that does not need a spreadsheet
The agency problem is context switching
An in-house support team can gradually absorb one company’s policies, tone, and product details. An agency does not have that luxury. Agents may answer for several brands in the same day, and each client expects the reply to sound like it came from their own team.
That is why the operating system matters. Client separation, approved knowledge sources, SLA rules, and escalation paths need to be visible before AI starts drafting. Otherwise automation can speed up the wrong kind of work: replies that are fast but not aligned with the client.
Protodesk works best when each client has a small support playbook: channels, labels, policy sources, tone examples, escalation contacts, and reporting expectations.
A client onboarding playbook
Use the first week of a new client relationship to build the system that keeps the next months calm.
- Collect the client’s top articles, policy pages, macros, and escalation rules.
- Define labels for the most common topics before importing every historical edge case.
- Create a short list of topics AI may draft, topics AI may auto-resolve, and topics humans must own.
- Agree on SLA targets and what counts as an escalation-worthy message.
- Review the first week of drafts with the client so tone and policy boundaries are corrected early.
Quality control for AI-assisted agency support
Agency support has a higher bar for review because a weak reply affects both the customer and the client relationship. AI should reduce the blank-page work while leaving accountability with the agency.
The practical QA loop is simple: sample drafts, inspect auto-resolved conversations, track reopened tickets, and review messages where agents heavily edited AI output. Each review should produce an operational change: improve an article, adjust a label, change an escalation rule, or clarify client tone.
Over time, the agency builds reusable support operations muscle without making every client workflow identical.
Frequently asked questions
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