The Corridome blog.
Posts on what we’re building, seeing, and learning in lead-sourcing infrastructure.
What 11.4 million PPP loans tell you about every US small business with employees
The 2024 SBA Paycheck Protection Program FOIA release is the closest thing in the public domain to a registry of every US small business with employees. Here is what you can pull from it for M&A sourcing without enrichment.
Earlier posts.
Add-on acquisitions: how sourcing differs from platform deals
Platform deals get sourced from a national funnel. Add-ons get sourced from a tight radius around an asset the firm already owns, and almost nobody writes about the difference.
DealCloud alternatives: an honest comparison for PE operators
DealCloud is configurable, slow to deploy, and priced for the upper-middle-market. Most firms shopping alternatives need a framework, not another vendor list.
Independent sponsor economics in 2026: what the cohort actually earns
Real fee, carry, and rollover ranges for fundless sponsors, pulled from the McGuireWoods survey and the law-firm primaries that nobody quotes in full.
What proprietary deal flow actually looks like at the lower-middle-market level
Proprietary deal flow is a system, not a tool and not a Rolodex. What the system looks like at LMM scale, and what running it actually costs.
Quality of earnings from the sourcing side: what to know before you commission one
What a deal team should decide about scope, period, and add-back posture before the QoE provider quotes, and how those choices echo back into the next target screen.
What a custom M&A advisory platform actually looks like: a build walkthrough
Seven CDK stacks, sub-$100/month infra, two Bedrock models, and a self-mutating pipeline. The architecture of one middle-market advisory build, with the trade-offs and the parts we'd redo.
Outsourced deal sourcing: when it works, when it breaks
A buyer's guide to the three models of outsourced sourcing (offshore analyst farms, agency retainers, software-with-services) and the structural reason each one tends to stall around month six.
When 'AI deal sourcing' is just a wrapper (and when it isn't)
Most AI deal sourcing pitches are GPT prompts on top of someone else's database. Here is what AI actually doing the work looks like: signal discovery, scoring iteration, and a ranking function the firm owns.
When PitchBook isn't the answer (and what to do instead)
A PitchBook alternative is usually the wrong frame. The right question is whether the firm should rent another aggregator or own the layer that sits above it.
Sourcing acquirable SaaS in the $1-25M ARR band
The trend pieces have the macro right and the sourcing wrong. Where lower-mid-market SaaS targets actually live in 2026, and the signals that surface them before a banker does.
The operational signals that precede a PE exit
McKinsey and Bain tell you about cycle conditions. Public web data — LinkedIn, company sites, job boards, press — tells you which specific portfolio companies are quietly tightening up for a process, months before the bankers get the mandate.
What Secretary of State filings tell you about an acquisition target
Secretary of State filings deal sourcing works when you pull the right fields on the right cadence. A tactical guide to registered-agent changes, officer turnover, dissolutions, name changes, and assumed-name filings as buy-side signals.
Why most M&A cold outreach fails
The SERP blames the email. The data, when you look at it, blames the list and the cadence. A view from the people who build the pipelines that feed these campaigns.
The lower-middle-market 100-day plan (not the McKinsey version)
A post-merger integration playbook for the team folding a $20M acquisition into a $60M platform, staffed by the same eleven people who closed the deal, with the data stack as the part that usually breaks.
What the HVAC roll-up SERP is missing
The HVAC roll-up SERP is full of playbooks and short on data. Here is the size of the universe, the cohort the consolidators are actually buying, and the signals worth scoring.
Reading an M&A advisor fee structure
Every M&A advisor fee structure is also a behavior contract. Here is what each model (retainer, success, hybrid, Lehman, Double Lehman, modified Lehman) actually pays the advisor to do, mapped to deal size.
What an open EBITDA multiples database would actually need to do
Every result on page one for EBITDA multiples by industry 2026 is either a public-company aggregate from January or a private-company range with no sample size. Here is what a live, sortable, filing-driven version of that table would have to ship.
Reading consolidation pressure off the open web
The macro reports tell you M&A volume is up. They don't tell you which county will roll up next quarter. Here's the data trail that does.
The 2026 state of founder-led business acquisition
Where the founder-led-acquisition thesis is grounded in public data, what the public record actually shows, and what a buyer can ask of the data.
Building an off-market pipeline that doesn't rot
Off-market deal sourcing for M&A buyers is a pipeline problem, not a list problem. What owning that pipeline changes about which founders you actually reach, and when.
Data sources for M&A target identification that aren't LinkedIn
A working catalog of public-record data sources for M&A target identification, what signal each surfaces, how to extract it, and what it reveals about an operator.
What actually makes a good acquisition target
Most criteria checklists are diligence questions, not sourcing signals — useless until you're already in the room. A working scorecard for what you can measure upstream, and where the standard list quietly falls apart.
How the $5M-$50M EBITDA segment actually moves
Lower middle market private equity reads like the upper middle market from a distance. Up close, the target firms, the sourcing math, and the bandwidth problem are different enough that copying the playbook breaks.
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