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Workflow automation

Internal request intake & prioritisation system

Internal requests pile up as scattered DMs and tickets, prioritised by who follows up most. We write the intake rule and the prioritisation rubric — and AI classifies, routes, and proposes a priority, so a person decides instead of guessing.

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Who this is for

B2B

Operations and RevOps teams that field requests from every other function with no single intake.

IT, data, and analytics teams whose queue is a pile of Slack DMs and "quick favours".

People/HR, finance, and legal teams pulled into ad-hoc asks with no way to rank them.

Delivery leads and PMOs juggling internal requests against planned work.

Founders and leadership whose team is flooded with asks and prioritises by who follows up most.

Common pain points

Why internal requests get prioritised by insistence, not by criteria

Requests arrive as DMs, emails, and hallway asks, with no single place to see what has actually been asked.

Nothing defines what counts as a real request versus a question or an FYI, so everything becomes a ticket.

There is no owner per request type, so each ask gets routed by guesswork or lands on whoever answered last.

Priority is set by who follows up most, not by impact — so the most insistent request wins, not the most important one.

Near-identical requests get worked twice because nobody dedupes them first.

The team has no written rubric to say no, or later, so every ask feels equally urgent.

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A rule for what counts as a request — and AI to classify, route, and propose priority

An internal request intake and prioritisation system makes explicit what counts as a request, the fields it must carry, who owns each type, and how it is prioritised. AI classifies each incoming request by type, routes it to the named owner, dedupes near-identical ones, drafts the missing context, and proposes a priority from a written rubric. A person prioritises and owns the exceptions — AI never sets the final priority on a contested item.

How we work

  1. 1

    We define what counts as a request, the intake surface, and the fields each request must carry before it enters the queue.

  2. 2

    We connect AI to classify each request by type, route it to the named owner, dedupe near-identical ones, and propose a priority from the rubric.

  3. 3

    We set the prioritisation rubric and the owner for exceptions, and hand over a runbook the team operates and edits.

Next step

Talk through where internal requests pile up

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What we build

What this work includes

Area 1

An intake rule: what counts as a request, and the fields it must carry

We write what counts as a real request versus a question or an FYI, the surface requests come in through, and the fields each one must carry — requester, context, impact — before it enters the queue. The rule is agreed with the people who field the requests, so it reflects how the work really arrives.

Deliverable

A request definition + intake template: request type, requester, context, impact, and the owner it routes to.

Area 2

AI classification and routing to the named owner

We connect AI to read each incoming request, classify it by type, and route it to the owner who handles it — and where it is unsure, it asks rather than guesses. Routing follows the written map, not whoever answered last.

Deliverable

A routing map: request type → named owner, with the AI classification rules behind it.

Area 3

A prioritisation rubric: impact, effort, and urgency

We agree how to rank a request — impact, effort, and urgency — and turn it into a written rubric, so priority stops being set by who follows up most. The rubric is what lets the team say "later" with a reason, not a shrug.

Deliverable

A prioritisation rubric: how impact, effort, and urgency are scored, and the thresholds that rank a request.

Area 4

AI that classifies, routes, dedupes, and proposes priority — within written limits

We connect AI to classify each request, route it, dedupe near-identical ones, draft the missing context, and propose a priority from the rubric. What AI may never do — set the final priority on a contested item — is written down. AI prepares and proposes; a person decides.

Deliverable

An AI capability map with the limits written: what AI classifies/routes/dedupes/proposes, and what only a person decides.

Area 5

A dedupe and merge step for near-identical requests

Most queues carry the same ask three times from three people. We define how near-identical requests are detected and merged before anyone works them twice, so the queue reflects real demand, not duplicated noise.

Deliverable

A dedupe rule: how near-identical requests are detected and merged before the team works them twice.

Area 6

A runbook the team operates and edits

We hand the system over as a runbook: the intake rule, the routing map, the prioritisation rubric, and the AI limits. The goal is for the system to live without us — the team can add a new request type, adjust a threshold, and bring a new owner up to speed without rebuilding it.

Deliverable

A runbook with the intake rule, routing map, rubric, and AI limits the team owns.

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Every request lands in one intake with the fields it needs, so the team stops reconstructing context from a thread.

What counts as a request is written down, so questions and FYIs stop turning into tickets.

Each request type has a named owner, so nothing routes by guesswork or lands on whoever answered last.

Priority follows a written rubric — impact, effort, urgency — so the most important request wins, not the most insistent one.

AI classifies, routes, dedupes, and proposes a priority — and a person decides, with the limit that AI never sets final priority on a contested item.

The intake rule, routing, and rubric live in a runbook the team operates and edits, not in one overloaded person's head.

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Answers before we start

How is this different from customer-support ticketing?

Customer-support ticketing handles external customer tickets; this handles internal requests between your own teams. The two look similar but the buyer, the rules, and the owners are different. If what you need is external support triage, that is our ticket-triage and routing work, not this.

How do you prioritise an internal request?

With a written rubric — impact, effort, and urgency — agreed with the team, not by who follows up most. AI proposes a priority from that rubric and routes the request to its named owner; a person makes the call and owns the exceptions. The rule that AI never sets the final priority on a contested item is written into the system.

Does AI decide what gets done first?

No. AI classifies each request, routes it, dedupes near-identical ones, drafts the missing context, and proposes a priority — but a person decides. On a contested or high-impact request, AI prepares the case and a named owner sets the order. The line between what AI proposes and what a person decides is written down.

Is this an approval workflow?

No, though they sit next to each other. Approvals are about who signs off on a request once it is in flight; this is about taking the request in, owning it, and ranking it in the first place. If the bottleneck is sign-off rather than intake, we will point you to our approval workflow work instead.

Does this integrate with Slack, Jira, Linear, or Asana?

We design the intake and routing to fit the tools your team already uses, and name current tools as examples — but we do not make integration promises on this page, because tools change. In the diagnostic we confirm what is actually possible with your specific stack, and we will tell you honestly where a clean connection exists and where it does not.

What does this work NOT include?

It does not include building or selling a helpdesk or ticketing product, a project-management tool, an approval workflow (that is a separate page), or an AI that sets contested priority on its own. If what you need is one of those, we will tell you and point you to the right work.

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Ready to stop prioritising internal requests by insistence?

Book a 30-minute call to look at how internal requests reach your team today. We will talk through what should count as a request, who should own each type, and how a written rubric plus AI routing can rank them — and what the team can realistically run. If the real issue is sign-off or too much rework downstream, we will tell you and point you to the work that fits.

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