Skip to content

Draaftly for investors and lenders

Appraise proposals on the evidence, not the formatting

Investment and credit teams read a lot of optimistic documents. Draaftly makes the working visible: where each number came from, what it assumes, and what has to be true for the case to hold.

Get early accessBook a demo

What slows down an appraisal

The analysis is rarely the slow part. Reconstructing somebody else’s numbers is.

  • Every submission arrives in a different shape

    Comparing two proposals means rebuilding both models before you can look at either.

  • Projections come without their assumptions

    A ten-year forecast lands with no record of the growth rates, prices or utilisation behind it.

  • Sources cannot be checked

    Market claims cite a link that has moved, or a figure with no date, page or publisher.

  • The downside case is missing

    The pack shows one scenario, and the first question in committee is what happens if it slips.

Which parts of Draaftly help

Modules share the same evidence, assumptions and house style, so work done in one carries into the next.

The question a credit committee asks first

A fictional project summary where every figure is marked sourced or computed, and the simulator surfaces the debt-cover question before the meeting does.

Every sample on this site uses fictional projects, markets and figures.

Riverside cold-chain hub — financial summarySample
Capital cost
$4.20m
Source
Project IRR
21.4%
Computed
NPV at 12%
$2.11m
Computed
Payback
4.4 years
Computed
Minimum DSCR
1.09× (year 1)
Computed
Average DSCR
2.50×
Computed

Banker and Investor Simulator

“Debt cover is 1.09× in year 1, below the 1.20× most lenders expect. What supports first-year revenue of $1.10m, and would you accept a six-month grace period on repayments?”

Fictional project. Every figure is calculated from the assumptions register; the simulator flags what a lender would ask first.

What changes in appraisal

  • A consistent assumptions register for every proposal you review, so two cases can be compared directly.
  • Sensitivities and downside scenarios produced from the same model, not re-keyed by hand.
  • Source snapshots with date, page and excerpt, so a market claim can be verified later.
  • The likely committee questions listed before the meeting, generated from the numbers in the pack.
  • A defensible record of how a decision was reached, held with the project.

Or have our team do the work

Our team also takes on independent appraisal and commercial due diligence as fixed-fee work.

Questions people ask

Can we standardise what applicants submit?

Yes. You can set the structure, assumptions template and house style for a project type, so submissions and internal papers arrive in a comparable shape.

Does the AI decide anything?

No. The AI organises evidence and drafts narrative. Calculations run in a tested calculation engine, and every decision stays with your team.

Does Draaftly score credit risk or predict approval?

No. It does not score borrowers, rate credit risk or predict any lender’s decision. It makes the evidence, assumptions and sensitivities behind a case visible so your own process can do its job.

Can we see what changed between versions of a case?

Each project keeps its evidence, assumptions and approval history, so you can see which inputs moved and who approved the version you are reading.

Is submitted or borrower data used to train AI models?

No. Draaftly never uses your data to train AI models. Our AI providers, Anthropic and Google Cloud, do not use customer data from their commercial services to train their models by default. We explain this in full on our Trust page.

Run one live proposal through Draaftly

Bring a real submission to a guided session and see the assumptions, sensitivities and committee questions it produces.

Get early accessBook a demo