The proof

Five builds.
Every number real.

The resume sets it up: our founder, Chris Roan, took a former company from $70M to over $800M in revenue as its Director of Partnerships, building the supply-side network behind a marketplace pivot. That is the same pivot we now run for clients. These five are the payoff. We dropped into ops-heavy companies, found where the money and the hours were leaking, and shipped the owned system that stopped it. A small, elite team and a fleet of AI agents. Every client here is anonymized. Every number is exactly what it was.

$800M+
in revenue, the marketplace pivot we run for clients
$145K
in salary saved a year, no new headcount
$0/mo
in lead-gen SaaS, replaced with an asset they own
80%
of a legal back office's manual work, gone
01
Bespoke software, OCR/RPA

A 45-year-old Texas process-serving firm, 20 offices.

$145K in salary saved a year, no new headcount, a single rep now runs what used to take a team.

The leak

We saved them $145,000 a year in salary with zero new hires, and it paid for itself in two to four weeks. One rep now runs what used to take a team. Here is what we cleared: forty-five years of paperwork keyed by hand across twenty offices, then re-keyed into the case system, billable hours burned on retyping work they had already typed once.

What we built

We shipped an installer that reads the documents and writes them straight back into the case database, cutting manual handling by 80%. Nobody retypes anything. It runs on their own machines, so the savings landed without changing how they work.

The output is trustworthy enough to run unattended because the work splits across a small agent stack with narrow jobs: a Hunter that finds the documents, an Auditor that checks the extraction before anything commits, and a Clerk that performs the writeback.

OCRRPACase-DB writebackHunter / Auditor / Clerk agentsSigned installer
$145K
in salary saved a year, no new headcount
$18,750
saved per user, per year
80%
less manual handling
2-4 wks
payback

Through-line · $145K a year saved, payback inside a month, at a firm older than most software, because the system fit their machines instead of asking them to change.

02
Automation, lead engine

A Metro Vancouver landscaping company.

$0/mo in lead-gen software, an engine they own instead of rent.

The leak

We took their lead-gen software bill to $0 a month and handed them an engine they own instead of rent. Before us, they were paying Apollo and Clay anywhere from $59 to $800 every month for prospects, money that bought access and never an asset. Now the bill is gone and the system is theirs to keep.

What we built

We built them a custom lead engine that scrapes public registries, enriches the records, and feeds a clean pipeline, replacing both Apollo and Clay. The recurring spend stops and the asset stays on their books.

It is engineered to run as outbound infrastructure they can trust, built in Python with a full test suite and consent rules baked in from the first line.

PythonPublic-registry scrapingApollo + Clay replacementCASL-compliant434/434 tests
$0/mo
in lead-gen software, replaced
434/434
tests passing
Owned
open-source, theirs to keep
CASL
compliant by design

Through-line · Their lead-gen bill went to $0 a month and they stopped renting their pipeline and started owning it.

03
Bespoke software, live AI agent

A luxury DTC wellness brand.

A sales consultant that costs nothing unless it sells.

The leak

We gave them a sales consultant that costs nothing unless it sells. We take 5% of what it closes and zero otherwise. The problem it fixed: premium buyers had real questions at the moment of intent, and there were never enough expert hours to answer them. Every unanswered question was a sale walking out the door.

What we built

Now it answers around the clock and hands off to a human the instant a conversation needs one. It talks customers through their goals and generates branded protocol PDFs tailored to each one. It is in production, taking real conversations.

Because it sells a wellness product, it runs inside medical-safety guardrails so it never crosses a line on its own. It is built on LangGraph and Gemini, live on Google Cloud Run.

LangGraphGeminiGoogle Cloud RunMedical guardrailsHuman takeover
5%
revenue-share on bot-attributed sales
Live
on Google Cloud Run
Branded
protocol PDFs generated
Human
in-the-loop takeover

Through-line · It costs nothing unless it sells, it never crosses a medical line on its own, and a person can take the wheel the instant the conversation needs one.

04
Marketplace pivot, leads to network

A SaaS-enabled hauling company.

The same leads-to-marketplace pivot that took a company past $800M.

The leak

The same leads-to-marketplace pivot we run here took our founder's former company from $70M to over $800M in revenue. He ran it as Director of Partnerships who built the supply-side network. Here is why it matters for them: selling leads has a ceiling. Every handoff is where a deal dies, and you get paid for the intro, not the job.

What we built

We build the supply-side network so the completed job becomes the product, not the introduction. That is the move a lead-gen model cannot make on its own, and it is what lifts the ceiling the old model was stuck under.

We are running that same playbook again here, on their machines and their book of business, the one that already carried a company from $70M to over $800M.

Marketplace pivotSupply-side networkConversion-obstacle removalLeads-to-marketplace playbook
$800M+
the pivot's track record
Supply
side network built
Leads
to a true marketplace
Removed
conversion obstacles

Through-line · We took them off a capped lead-gen model and onto the marketplace pivot that has already carried a company from $70M to over $800M.

05
Bespoke software, social engine

A brand that had gone dark on social since Thanksgiving 2025.

Seven months silent, now an always-on presence that answers itself.

The leak

Seven months silent, now always-on. It posts on schedule and answers its own comments, with a human pulled in only when it matters. The cost of the silence: seven months of lost reach, cooling goodwill, and an unwatched inbox of comments nobody was answering, the ones that quietly decide a brand is gone.

What we built

Now it posts on a schedule, so the brand has a steady presence again without anyone posting by hand. The feed stops being a graveyard and starts being a channel.

It also auto-replies to positive engagement with on-brand affirmations and routes anything needing a person to support, opening a ticket the moment something needs real triage. A classification model reads every comment and decides what it can answer and what to escalate.

Scheduled postingDeepSeek classificationAuto-reply affirmationsZendesk triage
7 mo
dark, now always-on
DeepSeek
open-source engagement classifier
Auto
on-brand affirmation replies
Zendesk
triage on what needs a human

Through-line · A brand that had gone dark for seven months is always-on again, answering its own engagement and escalating only the conversations that need a person.

Your turn

There is a leak in your business too.

The diagnostic is how we find it. It is the front door, the qualifier, and the thing that gates a limited build calendar. Our capacity is the constraint, so the diagnostic comes first. You either find money you are losing, or you confirm you are not. Both are worth knowing.