Your data is the bottleneck.
We fix that.
Scaylor turns the disparate systems inside PE-backed companies into exit-ready intelligence — a clean data room in weeks, not months.
PE-backed companies in the exit backlog, valued at $3.7T
of PE firms say weak data / KPI reporting is their biggest finance issue at exit
average holding period — a historic high
of mid-market organizations report full data readiness
a CFO spends on manual data gathering during a typical deal
Buyers ask baseline questions.
Your systems can't answer them.
Revenue by end market. Margins by product line. Customer concentration going back five years. A full HR roster with comp history. Not exotic analysis — the absolute baseline of a CIM and a well-organized data room. Yet in the typical mid-market company running an ERP that doesn't talk to the CRM, spreadsheets as the de facto inventory tracker, and a legacy system from an add-on that was never migrated, pulling it together is where months and hundreds of thousands of dollars go.
200–300+ hours over 8 weeks pulling reports from five systems and reconciling them in Excel — during the exact period the business needs its financial leader most.
When data rooms are populated late, incomplete, or inconsistent, every new file that surfaces forces advisors to revisit prior conclusions. The re-work shadow equals 20–40% of the visible adviser bill.
Sellers who can't substantiate claims with clean, consistent data face price adjustments in diligence. Disorganized deals drag from 4–6 weeks to 4–6 months — and every month costs.
Connect. Unify. Analyze. Deliver.
Your existing systems don't need to change. Scaylor sits on top of them and produces the outputs buyers expect.
Connects to every data source in the business — ERP, CRM, HRIS, inventory systems, spreadsheets, legacy databases. No rip-and-replace. Your systems don't change; they start speaking the same language.
Captures how your business actually defines its metrics — what counts as recurring revenue, how product lines map across systems. Entity resolution, deduplication, and schema mapping happen automatically.
Generates the exact outputs buyers and advisors need: revenue by end market, geography, and segment. Margins by product line. Customer concentration. HR roster with comp history. Live, not static.
Clean, verified, exportable data ready to populate a CIM, feed a virtual data room, support a QoE analysis, and answer buyer diligence questions. A single source of truth advisors can query directly.
The exact answers buyers ask for.
Every figure below traces back to source systems — reconciled, governed, and exportable straight into your CIM and data room.
| End market ($M) | FY21 | FY22 | FY23 | FY24 | FY25 | Mix |
|---|---|---|---|---|---|---|
| Industrial OEM | 18.4 | 21.2 | 24.8 | 28.1 | 31.6 | 38.2% |
| Aerospace & Defense | 9.1 | 10.4 | 12.2 | 14.0 | 16.3 | 19.7% |
| Medical Devices | 6.2 | 7.8 | 9.5 | 11.4 | 13.8 | 16.7% |
| Energy & Utilities | 5.8 | 6.1 | 6.9 | 7.6 | 8.4 | 10.2% |
| Transportation | 4.4 | 4.9 | 5.6 | 6.2 | 7.1 | 8.6% |
| Other | 3.9 | 4.2 | 4.6 | 5.0 | 5.5 | 6.6% |
| Total | 47.8 | 54.6 | 63.6 | 72.3 | 82.7 | 100.0% |
Every seat in the process gets time back.
Fund life is ticking and LPs want DPI. Scaylor gets portcos to data-room readiness in weeks — with a value creation story backed by data, not narrative.
Scaylor automates the extraction, reconciliation, and analysis you'd otherwise do by hand — freeing 150–250 hours to keep performance on plan while the process runs.
One governed source of truth means fewer broken analyses, fewer re-cuts, and a diligence process that doesn't stall every time a new file surfaces.
For a representative $50M-EV company.
Mid-market, 5+ disparate systems, ten-year operating history.
| Cost category | Manual approach | With Scaylor | Savings |
|---|---|---|---|
| CFO / Controller time (exit prep) | 200–300+ hours | 40–60 hours | 150–250 hours freed |
| Advisory premium from data chaos | $30K–$70K in re-work | Minimal re-work | $25K–$60K saved |
| Time to data room readiness | 4–8 months | 6–8 weeks | 2–6 months faster |
| Valuation risk from data gaps | 0.5–1.5x multiple erosion | Data-backed equity story | Multiple protection |
| Deal timeline | 30–90 day overruns common | Faster buyer diligence | Months saved |
A well-organized data room with clean, indexed, searchable data reduces total adviser costs by 25–35% on a typical mid-market deal. Data quality is the single most controllable cost lever in the entire exit process.
Your exit timeline starts with a conversation.
Let's talk about your data. No forms, no sequences — a direct line to the people building the product.
Have questions? We'd love to hear from you.