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AI-drafted time-entry narratives

01 — The scenario

A legal business where this lands in Finance.

The friction
billingtime-capturewrite-offstimesheetsrealisation

02 — What is actually going wrong

Time gets written up on Friday afternoon from memory. Memory is generous to the client and unkind to the firm: work genuinely done goes unbilled, and the narratives that do get written are thin enough to invite write-downs from the client's billing team.

How it works

The system watches the systems your fee earners already use — calendar, email, document management — and drafts time entries with a narrative describing what was actually done. The fee earner reviews, edits and approves; nothing posts unreviewed.

What good looks like

Write-up time on Friday collapses, recorded hours rise a few percent because the small entries stop falling through, and client write-downs fall because the narratives describe real work in specific terms.

03 — The problem, in money

$128,700$15,854,475/ yr at stake
Modeled
  • Timekeepers10 people101 peoplePlaceholder — not a validated benchmarkStarting point
  • Admin hours per timekeeper per week3 hours10 hoursPlaceholder — not a validated benchmarkStarting point
  • Recovered billable ratio0.05 ratio0.25 ratioPlaceholder — not a validated benchmarkStarting point
  • Billable billable_hourly_rate300 USD780 USDPlaceholder — not a validated benchmarkStarting point
  • Share automated0.4 ratio0.5 ratioPlaceholder — not a validated benchmarkStarting point
  • Share of freed time redeployed0.5 ratio0.5 ratioPlaceholder — not a validated benchmarkStarting point

04 — The options

Buy$100–$300 / moOff-the-shelf tooling, live sooner.
Bin$0Do nothing — and accept the leak.

05 — The call

Buy it

Buy it. An off-the-shelf tool wins this one — it gets you live faster, and the math does not justify building from scratch.

06 — How this goes wrong

  • Auto-posting without review. A fabricated or duplicated entry on a client bill is a professional conduct issue, not a billing error.
  • Narratives that are verbose rather than specific. Billing teams reject padding faster than they reject brevity.
  • Counting recovered billables and freed admin hours as separate wins on the same hour — the model splits them deliberately, and you should not add them back together.
  • Monitoring email content without telling your people. Get consent and scope it explicitly.

07 — How you would actually do it

  1. 01Confirm what your practice management system will accept via API before choosing anything.
  2. 02Scope the activity sources, and be explicit with staff about what is being read.
  3. 03Pilot with two willing fee earners for a full billing cycle.
  4. 04Compare their recorded hours against their own prior three months, not against the firm average.
  5. 05Tune narrative style against what your biggest client's billing team actually approves.
  6. 06Keep review-before-post permanently. This is not a maturity stage to graduate out of.

08 — Tools worth looking at

Ajilon / LaurelPassive time capture with AI narrative drafting.
SmokeballAutomatic time capture built into the practice management system.
Clio DuoNative option if the firm already runs Clio.

Named for orientation, not endorsement. No affiliate arrangements, and nothing here has been paid for.

09 — Run it on your numbers

Start from industry averages, then drag the inputs to match your business. The number moves live.Drag each input to your number — the starting points are neutral midpoints, not industry data. The number moves live.

Worth to your business
$128,700per year
Modeled — industry averages
Revenue$312,000Modeled
Cost savings$0Modeled
Hours / week12Modeled
Industry averages
10 people
Industry avg: 10 peoplePlaceholder — not a validated benchmark
3 hours
Industry avg: 3 hoursPlaceholder — not a validated benchmark
0.05 ratio
Industry avg: 0.05 ratioPlaceholder — not a validated benchmark
300 USD
Industry avg: 300 USDPlaceholder — not a validated benchmark
0.4 ratio
Industry avg: 0.4 ratioPlaceholder — not a validated benchmark
0.5 ratio
Industry avg: 0.5 ratioPlaceholder — not a validated benchmark

10 — The evidence · what others report

No hard numbers reported.

Reported numbers are third-party claims, source-attributed — not verified by me, and never blended into the model above.

11 — Questions owners ask

Every figure is Modeled — computed from industry-average benchmarks against the scenario’s formula. Move the sliders to your own inputs and the numbers recalculate live. Nothing here is a promise; it is a starting estimate you can pressure-test.
The library is organized by department, outcome, effort and readiness so you can find what fits. Add scenarios to your plan, tune the inputs, and see the combined picture on your plan dashboard.
Want this to be a Projected number? That's what the Audit produces — my forecast on your real data, with my name on it.
Build means a custom system is the right move; Buy means an off-the-shelf tool wins; Bin means the math does not justify doing it at all. Binned scenarios can be favorited for reference but never enter a plan.

Is this your business?

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