Use Cases — AI Workflow Automation by Team | Diaphora

Operational patterns by team

Find the work that should run itself.

Start with the manual bottleneck: reading context, reconciling systems, or reshaping the same report. Diaphora turns that repeated work into a governed blueprint.

The recurring pattern

  1. Read scattered context
  2. Apply rules and reconcile
  3. Return a typed outcome

Same inputs · same controls · repeatable result

Create

— Plain language in

Distribute

— API, MCP, or scheduled

Govern

— RBAC, ABAC, and DLP

Choose your operating problem

Each pattern below starts with work a person repeats and ends with an inspectable, versioned outcome. Open a team to see the blueprints behind it.

UC-01

Customer Success · 3 blueprints
Account health without the gut feel
Nobody needs to read every Slack thread to know if an account is healthy — that's an inference problem, not a willpower problem. These blueprints read the scatter, Slack, usage, audit, and return the same structured health read every time.

Manual bottleneck

Account health lives in someone's head, read fresh out of Slack threads every time.

Blueprint returns

One structured health read — usage, audit, and error data, reconciled automatically

Adoption risk

UC-02

Revenue & Sales · 2 blueprints
Reps stop walking in cold
The prep a rep needs already exists — in the CRM, the calendar, the transcript. Reconciling it by hand is the unnecessary step. These blueprints do the reconciling and hand back one document.

Manual bottleneck

Call history, open items, and CRM gaps live in three systems — reconciled by hand, every time, if at all.

Blueprint returns

One prep doc, assembled from CRM, calendar, and past calls — before every call

UC-03

Product Intelligence · 2 blueprints
Every call read. Not the three you had time for.
Reading transcripts one at a time doesn't scale — and it's the wrong job for a person anyway. These blueprints read all of them, by topic, and hand back a structured answer.

Manual bottleneck

The real answer is buried across dozens of transcripts — reading them one by one doesn't scale.

Blueprint returns

Topic-level answers across the entire call corpus

UC-04

Platform Analytics · 2 blueprints
Know which MCP servers earn their keep. Without the joins.
Every question about fleet health is a manual join across telemetry tables. That's not judgment — it's plumbing. These blueprints make the join, and hand back the same snapshot on a schedule.

Manual bottleneck

Understanding one server's real performance means joining tables by hand. Every time.

Blueprint returns

One fleet-wide view — usage, errors, dormant connections

True of every blueprint, whatever the use case