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DozAI mission design · Evidence-led

90-day and 180-day retention follow-up.
Keep following the cohort after the placement report is filed.

A retention follow-up mission schedules consented contact at defined intervals, gathers current employment evidence and prepares exceptions for human review. Denominators must retain unreachable and unresolved graduates so retention is not overstated.

Graduate Follow-Up EpisodeReference model
One connected recordSOURCE · STATUS · OWNER · EVIDENCE
traceable
01
Graduate and consent state

Linked to the same operating record.

Defined
02
Placement baseline

Linked to the same operating record.

Defined
03
Follow-up window and attempt

Linked to the same operating record.

Defined
✦
Decision boundary

A system prepares the record and evidence. A named person owns consequential judgement.

Illustrative operating model, not a client record or product screenshot.

The direct answer

A retention follow-up mission schedules consented contact at defined intervals, gathers current employment evidence and prepares exceptions for human review. Denominators must retain unreachable and unresolved graduates so retention is not overstated.

01 · What breaks

Design for the failure modes, not only the happy path.

The value of 90-day and 180-day retention follow-up depends on what happens when records are incomplete, evidence conflicts or the next action carries consequence.

RISK 01

Different questions at each interval

Make this visible in testing, ownership and review rather than leaving it as an implementation surprise.

RISK 02

Unreachable graduates removed

Make this visible in testing, ownership and review rather than leaving it as an implementation surprise.

RISK 03

Job change counted as failure

Make this visible in testing, ownership and review rather than leaving it as an implementation surprise.

RISK 04

Sensitive reasons shared with employers

Make this visible in testing, ownership and review rather than leaving it as an implementation surprise.

02 · Minimum viable model

Start with graduate follow-up episode and the decisions around it.

The smallest useful model for this page connects the following records. Each field should have a purpose, owner and retention rule.

Central recordGraduate Follow-Up Episode
01Graduate and consent state
02Placement baseline
03Follow-up window and attempt
04Current role, employer and wage evidence
05Change, exit or support need
06Nonresponse, conflict and reviewer decision

03 · Implementation sequence

Move through reviewable gates.

A complete small workflow is safer and more useful than a large collection of unfinished modules.

Define follow-up windows and states

Agree the owner, evidence and exit condition before moving forward.

Human gate

Verify safe contact channels

Agree the owner, evidence and exit condition before moving forward.

System-supported

Schedule multilingual outreach

Agree the owner, evidence and exit condition before moving forward.

System-supported

Collect comparable evidence

Agree the owner, evidence and exit condition before moving forward.

System-supported

Route support needs and conflicts

Agree the owner, evidence and exit condition before moving forward.

System-supported

Report retention with nonresponse

Agree the owner, evidence and exit condition before moving forward.

Human gate

04 · Evidence

Measure whether the work became clearer.

Usage alone is not success. Review the quality, timeliness and decisions the system is meant to improve.

01Contact and completion rate
02Verified retention by window
03Job change and exit reasons
04Unresolved and support cases

05 · Responsible automation

Let systems prepare. Keep consequence with people.

Systems can support

  • Verify safe contact channels
  • Schedule multilingual outreach
  • Collect comparable evidence
  • Route support needs and conflicts

People should decide

  • Responding to distress or exploitation
  • Resolving employment conflict
  • Offering programme support
  • Approving the reported status

06 · Common questions

Practical questions teams ask.

Use these answers to clarify scope, compare approaches and identify the decisions your team needs to make before implementation.

Can AI safely help a nonprofit with 90-day and 180-day retention follow-up?

A retention follow-up mission schedules consented contact at defined intervals, gathers current employment evidence and prepares exceptions for human review. Denominators must retain unreachable and unresolved graduates so retention is not overstated.

What information does an AI mission for 90-day and 180-day retention follow-up need?

Start with graduate follow-up episode. The minimum useful record set covers graduate and consent state, placement baseline, follow-up window and attempt, current role, employer and wage evidence, change, exit or support need and nonresponse, conflict and reviewer decision. Remove any field that does not support a service, safeguard, decision or reporting obligation.

What can AI execute and what must a person decide in 90-day and 180-day retention follow-up?

People should retain responsibility for responding to distress or exploitation, resolving employment conflict, offering programme support and approving the reported status. Software or AI may prepare evidence and queues, but it should not silently make those decisions.

What evidence and audit trail should 90-day and 180-day retention follow-up produce?

Keep the source, definition, time, owner, status and review decision together. Monitor contact and completion rate, verified retention by window, job change and exit reasons and unresolved and support cases, and preserve limitations instead of cleaning them out of the report.

Where can an AI mission for 90-day and 180-day retention follow-up fail or require escalation?

The main risks are different questions at each interval, unreachable graduates removed, job change counted as failure and sensitive reasons shared with employers. Test these with representative cases and keep the consequential judgement with a named person.

Tell us about the workflow you want to improve.

Share what happens today, where it breaks and what a useful decision or outcome would look like. We’ll help identify a practical first step.

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