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

01

Read scattered context

02

Apply rules and reconcile

03

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

BigQuery
Slack
Adoption risk
Error patterns

Explore Customer Success

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

Avoma
Google Calendar
Salesforce
Meeting summary

Explore Revenue & Sales

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

Avoma
Google Drive
Keyword research
Conversational

Explore Product Intelligence

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

BigQuery
Server telemetry
Adoption
Fleet ranking

Explore Platform Analytics

True of every blueprint, whatever the use case

Zero prompt drift

Every Blueprint is a versioned contract. Run 1 and run 10,000 behave identically.

Scoped sessions

Each LLM call sees only the context it needs — no one giant prompt, no context rot.

Typed output

Blueprints return validated objects pinned to a schema, not text you have to parse.

Reusable like an API

Parameterise once and call it from anywhere — versioned, auditable, shareable.