Solutions / PROMS Enquiry

From broker memo to underwriting model, in minutes.

AI-native deal screening for acquisition and origination teams. From broker PDF to institutional underwriting workflow in minutes, with the auditability and modelling discipline institutional teams expect.

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Audience
Transaction Teams · CRE Lenders
Inputs
PDF · Excel · Argus
Outcome
Faster screening · Clearer decisions · Cleaner data
How it works

From broker PDF to institutional model.

A document lands, the platform reads it, and an auditable, institutional-grade model comes out the other end.

01

Broker PDF lands in the workflow.

Rent rolls, OMs and broker packs arrive as unstructured PDF, exactly as received from the market.

02

AI reads and extracts the data.

Leases, assumptions and property data are lifted out of the document and mapped to a standard schema.

03

Data is structured and validated.

Extracted fields are checked and organised into the same structure Argus and Excel inputs already use.

04

Institutional model, ready.

Cashflows, screening metrics and IC-ready outputs are generated, fully traceable back to source.

Enquiry reads broker PDFs and Argus packs, builds a full traceable model in minutes, and lets the team ask it questions in plain language before it ever reaches committee.

Workflow

A cleaner front-end to the institutional engine.

The first screen is usually where time is lost. PROMS Enquiry shortens that stage without asking teams to compromise on discipline, consistency or source traceability.

01

Ingest the live deal pack.

Load the broker PDF, supporting spreadsheets and any available Argus inputs directly into the workflow.

02

Structure the raw information.

Extract leases, assumptions and property data into a standardised model that the team can actually work from.

03

Screen, compare and decide.

Run hurdle checks, scenario views and decision-ready outputs before the opportunity moves on without you.

01

Ingest

Every source read, checked and mapped to one schema.

Deal pack
Broker PDFs and OMs
Read with OCR
Rent rolls
Leases and terms
Excel models
Seller and broker
Argus files
Imported directly
Your house view
House assumptions
Your KPIs and hurdles
Internal research
Your market view
Market subscriptions
Under your own licence
Live data
APIs and connectors
Validated, standardised, and every value traced to its page
02PROMS

Analyse on the PROMS engine

A full institutional model, then every case the committee will ask about. Same methodology on every deal.

Net operating income and Exit, $mBase case · 10 years
Y1Y2Y3Y4Y5Y6Y7Y8Y9Exit
IRR
9.2%
Equity multiple
1.74x
DSCR
1.38x
LTV
62%
Ask CredenceQuestions in plain language, answered from the model
What happens if the anchor tenant leaves at its break in year 3?
Re-run with a 12-month void and re-letting costs: IRR falls from 9.2% to 7.6%, and stress DSCR to 1.08x, below your 1.10x covenant. Added to the memo under key risks.
Source: rent roll, tenant 1Assumption: 12-month voidMemo updated
03

Investment committee memo

Drafted from the model, ready for the analyst to review and sign off.

IC memo · DraftExample deal
Multi-let industrial, 218,000 sq ft
Deal economics
9.2%IRR1.74xMultiple1.38xDSCR62%LTV
Scenarios and sensitivitiesUpside 11.0%, base 9.2%, downside 6.8%. Falls below the 8.5% hurdle at a 6.25% exit cap rate with 2% growth.
Criteria check
IRR · passMultiple · passLTV · passStress DSCR · watch
Key risk · added by CredenceAnchor tenant break in year 3 takes stress DSCR to 1.08x, below covenant.
RecommendationProceed to due diligence, subject to the anchor tenant's renewal terms.
Every figure links back to its source and assumption
Deal pack to memo in minutes.Every number traceable.Judgement stays with your team.
Illustrative example. Not a real asset or client result.
Relevant audiences

Where PROMS Enquiry fits best.

01

Acquisition and origination teams

At funds, REITs, lenders and advisory firms who need to see the whole pipeline, not a tenth of it.

02

Analysts

Who would rather spend their time on judgement than rekeying.

03

Investment committees

Who want every deal underwritten the same way.

The value

The value of Enquiry, across the whole deal cycle.

Hours saved are the part you can measure from day one. Explore the wider value of pipeline coverage, better decisions and speed, with the workings and assumptions behind every estimate.

See more of the market

When screening takes minutes rather than hours, the team reviews the whole pipeline instead of a fraction of it.

Decide faster

The first properly underwritten view of a deal arrives while competitors are still rekeying the rent roll.

Free your analysts

The repetitive work of extraction and model building disappears; analysts spend their time on the assumptions, the risks and the negotiation.

Underwrite consistently

Every deal passes through the same engine and the same methodology, so committees compare like with like.

Trust the numbers

The engine is deterministic and certified, and every value traces to its source, so the output stands up to audit in a way that pure AI tools cannot.

Build a data asset

Rents, lease terms, costs and pricing from every document are retained, including deals you pass on, and compound with use.

Start from a profile
Illustrative estimates · USD
40

480 a year. Count only your sectors, markets and size range; off-mandate opportunities are excluded.

3

The people who screen and underwrite. Their available hours set how much of the pipeline gets a proper look today.

$35m

Drives the modelled value of finding, winning or avoiding a deal.

$150

Salary, bonus, benefits and overhead per working hour. This values capacity, rather than an assumed reduction in payroll.

Your pipeline, today and with Enquiry
TodayWith Enquiry
Screened and ranked45% → 100%
Reviewed by your analysts45% → 100%

Enquiry screens and ranks all 480 deals a year. Your analysts can review 480, up from 214, starting with the best matches.

Estimated value from one year's pipeline
$678k

$392k of annual analyst capacity, plus modelled opportunity and avoided-risk value. These amounts are estimates, rather than cash savings or a forecast of returns.

Analyst capacityAnnual hours freed × loaded cost$392k
Better decisionsModelled hidden gems and avoided risk$135k
Opportunity upsideAdditional reach, net of hours, and speed$152k
Analyst hours freed2,610

From data handling to analysis, each year

Pipeline screened and ranked45% → 100%

Analysts review 100%, highest ranked first

Strong deals identified2.1 → 6.7

Available capital decides how many close

Analyst days per deal10.6 → 5.3

For a deal that reaches committee

The AI reads the documents. The PROMS engine supplies the model, with traceable inputs and analyst review throughout.

Explore the assumptions for you
Across the deal cycle

Same team. Every deal screened and ranked.

Enquiry builds a model for the whole pipeline, so the team chooses from the opportunities in its mandate, rather than just the ones it had time to read.

Your pipeline, each year

TodayWith Enquiry
Deals in your mandate
480 → 480

Off-mandate opportunities are excluded from every figure.

Screened and ranked against your criteria
214 → 480

Enquiry reads each pack and scores it; analyst review is accounted for separately below.

Full institutional model
43 → 480

Today 20% of screened deals get a full model. With Enquiry, each opportunity has one.

Reviewed by an analyst
214 → 480

The same team's available hours, with the highest-ranked opportunities reviewed first.

Underwritten by an analyst
43 → 96

Analysts still review and judge each deal that goes forward: 41.6 hours rather than 80.

Strong deals identified
2.1 → 6.7

Uses a 1% make-the-cut rate and 0.5% hidden gems among quick-screen rejections. Identification is not a closing forecast.

Capital decides how many deals you close. Enquiry helps expand the choice.

Analyst time for a deal that reaches committee

The model can be built in minutes. What remains is the analyst's review and judgement.

Today
85.0 hours · 10.6 days
ReviewExtractFormat to ExcelMarket assumptionsSanitiseStress test
With Enquiry
42.1 hours · 5.3 days
Model built in minutesScored against your criteriaAnalyst checks inputsAnalyst judges and stress tests
ScreeningData handlingAnalysis and judgement

Less data handling. More time for the assumptions, risks and decisions that need your analysts.

Six channels of value

The hours are the start, not the whole story.

See what sits behind each estimate. Capacity can be checked against your timesheets; the other monetary channels depend on the assumptions and on what your team can execute.

Move hours from data to analysis

Analyst capacityYour hours × your cost
$392ka year · 2,610 hours

Enquiry screens and models each deal, and takes on much of the data work in underwriting. Analysts keep the checking, judgement and decision.

Show the working

Today: 5 screening hours + 20% × 80 underwriting hours = 21.00 hours per deal screened.

With Enquiry: 0.5 hours to review the screen + 20% × 41.6 underwriting hours = 8.82 hours.

214 deals × 12.18 hours freed × $150/hour = $392k of analyst capacity.

Capacity value is an opportunity cost, not a guaranteed cash saving. Some freed hours may be reinvested in additional reach; that cost is deducted in the reach channel.

Find the hidden gems

Better decisionsModelled
$90kfor one year's pipeline

A quick screen can reject deals that meet your criteria. Modelling each opportunity helps surface the ones headline numbers miss.

Show the working

171 quick-screen rejections × 0.5% hidden gems = 0.9 strong deals.

0.9 strong deals × 20% acted on × $525k value per deal (1.50% of $35m) = $90k.

An illustrative opportunity estimate, dependent on criteria, available capital and execution.

Invest and reject with confidence

Better decisionsModelled
$45kfor one year's pipeline

A consistent model and stress tests help the team examine the risks in every deal. Traceable inputs support checks before a decision is made.

Show the working

2.1 deals closed × 2% with a material error or unexamined risk × 3% impact on a $35m deal = $45k.

This scenario assumes all the material events in the selected error rate are caught and avoided. There is no separate prevention-effectiveness adjustment; it is not a prediction of losses prevented.

Reach the rest of your pipeline

Opportunity upsideNet of hours used
$39kfor one year's pipeline

The same team can review 100% of its pipeline instead of 45%, starting with the best matches. The estimate deducts the analyst hours reinvested in reaching them.

Show the working

3 analysts can review 480 of 480 deals, up from 214.

266 extra deals × 1% that make the cut, plus 0.5% hidden gems among rejections = 3.7 strong deals.

3.7 strong deals × 20% acted on × $525k value per deal (1.50% of $35m) = $391k gross opportunity value.

Less 2,344 reinvested hours × $150/hour = $352k.

Positive net reach value = $39k.

Win on speed

Opportunity upsideModelled
$113kfor one year's pipeline

A properly underwritten view can be ready earlier in the process. The estimate counts only 25% of deals assumed lost because analysis was not ready.

Show the working

43 deals underwritten × 2% lost on timing = 0.9.

× 25% won back × $525k value per deal = $113k.

Uses the win-back rate, without a second capital-capture adjustment. Price, competition, relationships and available capital can still determine the outcome.

Build your own data asset

Compounding assetNot priced
480deals structured a year

Rents, lease terms, costs and pricing are retained, including deals you pass on. Your own comparables grow with every opportunity. This asset is excluded from the monetary total.

Show the working

40 in-mandate opportunities per month × 12 = 480 structured opportunities a year.

Includes opportunities you do not buy or fund. No monetary value is assigned to this data asset.

The assumptions

These are illustrative starting points, rather than verified benchmarks. Replace them with your own figures and the whole calculation updates.

See and change the assumptions
1,500 hrs/year

Illustrative defaultAnnual screening and underwriting hours, after meetings, travel and admin.

5.0 hrs

Illustrative rangeReplace the example with your team's tracked screening time.

80 hrs

Use your ownAnalyst hours to take a deal from raw data to a committee pack.

80%

Illustrative rangeGathering, entering, formatting and checking data, as a share of full underwriting time.

60%

Illustrative defaultBelow full automation: analysts still check the extracted inputs.

20%

Illustrative rangeThe example assumes one in five. Use your pipeline's observed rate.

1.0%

Use your ownThe share of reviewed deals that meet your criteria; cannot exceed the underwriting rate.

0.50%

Illustrative defaultRejected on headline numbers, but shown by a full model to meet your criteria.

1.50% of deal

Use your ownValue added over the next-best use of the same capital, as a share of deal value.

20%

Illustrative defaultCapital is finite. Applied to hidden gems and additional reach, rather than assuming every opportunity closes.

2.0%

Use your ownProcesses where the analysis was not ready in time.

25%

Illustrative defaultSpeed helps; price and relationships still matter. This channel uses its own win-back rate.

2.0%

Illustrative defaultThe risk estimate assumes every event included in this rate is avoided through better checks and stress tests.

3.0% of deal

Illustrative defaultValue lost on a mispriced deal, as a share of deal value.

How to read these estimates
  • Monthly volume is multiplied by 12. Analyst budgets, pipeline counts and capacity value use an annual basis. All amounts are in US dollars.
  • Hours freed are valued at loaded cost. Additional reach deducts the value of hours reinvested; a negative reach estimate is counted as zero.
  • The model treats hidden gems, additional reach and timing wins as separate opportunities. Check that they do not overlap in your pipeline and that you have capital to act on them. Timing wins use their own win-back rate.
  • Avoided-risk value assumes every material event in the selected error rate is prevented. Actual effectiveness can be lower.
  • Deal opportunity values are estimates of added value; they are not cash savings or guaranteed investment returns. Subscription and implementation costs are not deducted, so this is not a net ROI calculation.

Illustrative only. Estimates depend on the assumptions shown and are not a forecast of returns. In an early access session, we replace the defaults with your figures and run the calculation on your own pipeline.

Run it on your pipeline →

Now onboarding early access clients

Book a PROMS Enquiry demo →