Growth engineering for owner-led service businesses
A common pattern is to buy a website, then an SEO retainer, then a CRM, then an automation tool, and end up with four vendors and no clear view of where the path is losing money. Ariadne designs the whole path from first search to closed customer, builds it in code, wires in the measurement, and hands you the keys.
The path check is free, needs no access, and comes back in writing within 3 business days. The audit is the qualified next step, not a prerequisite.
Start here
It is easy to arrive with a proposed fix before the constraint has been measured. Find the sentence below that sounds most like your business, then inspect that checkpoint before buying the work.
Demand problem. Before spending on visibility, check that the page they land on can convert them.
SEO and AI visibility 02 · ConversionConversion problem. Traffic is not the constraint; belief is.
Conversion optimization 03 · CaptureCapture problem. Anything not recorded in one place cannot be measured or followed up.
Lead generation systems 04 · RoutingRouting problem. Measure the handoff before assuming the website or demand is the constraint.
CRM and sales systems 05 · Follow-upFollow-up problem. Opportunities can stall without a recorded decision or next action.
CRM and sales systems 06 · SalesSales-process problem. If the process lives in your head, the business cannot hire its way out.
CRM and sales systems 07 · MeasurementMeasurement problem. Without attribution, every budget decision is a guess with a confident tone.
Analytics and attribution 08 · AutomationAutomation problem. Repetition is a design failure, not a staffing one.
Business automation 09 · CompoundingCompounding problem. Effort is going in and nothing is accumulating.
Growth experimentationThe growth system
Demand is useful only when the rest of the path can carry it. Ariadne connects discovery, conversion, capture, sales, retention, measurement, and automation before optimising any one layer in isolation.
See what growth engineering actually involvesEarn attention through search, local visibility, useful content, and answer-engine eligibility.
Turn relevant attention into a clear decision with positioning, UX, proof, speed, and a useful next step.
Record every enquiry, its source, and enough context to qualify and route it without inbox archaeology.
Give each opportunity an owner, a next action, a response standard, and a pipeline another person can run.
Keep useful follow-up, recall, reactivation, and referral prompts running after the first conversation.
Carry source and campaign context through to qualified opportunities and closed revenue.
Remove repeatable manual work while keeping monitoring, failure alerts, and a human fallback.
Measurement and automation feed the next demand and retention decisions. The audit decomposes sales and retention into routing, follow-up, repeatable sales, and compounding, creating nine checkpoints that can be tested separately.
Five service clusters, one system
These five build disciplines sit inside the same machine. Which ones belong in a scope depends on where the path is breaking; a focused project may need one, while a connected build may span several.
Layer 1 · Demand
Technical SEO, content built around real service questions, local and entity consistency, and the structured signals AI answer engines read. Organic discovery that compounds instead of renting attention monthly.
Feeds → Conversion
How this worksLayer 2 · Conversion
Positioning, page architecture, and copy shaped around the actual decision your best customer has to make, plus the build, the performance work, and the conversion events that let you see what happened.
Feeds → Capture
How this worksLayer 3 · Capture
Forms, calls, chat, and inbox inquiries land in one place, get qualified against your criteria, and reach the right person with the context they need. Nothing depends on someone noticing an email.
Feeds → Follow-up
How this worksLayers 4–5 · Sales and retention
A CRM that reflects how you actually sell, a pipeline someone other than you can run, and consent-aware follow-up that keeps chasing without sounding automated.
Feeds → Measurement
How this worksLayers 6–7 · Measurement and automation
Attribution from source to closed customer, reporting a founder can actually read, and automation of the repeated steps, with failure alerts and a manual path, because automation you cannot see is a liability.
Feeds → back into Demand
How this worksWhy this is structured differently
A common way to grow is to buy pieces. A web agency ships a site. An SEO agency sends traffic to it. A CRM consultant configures a tool. An automation freelancer connects two of them with Zapier. Each one may be measured on its own piece while the end-to-end customer outcome has no clear owner.
The gaps between those pieces are where money can be lost. The handoff from the website to the CRM may have no clear owner. A stopped follow-up sequence may go unnoticed. The SEO retainer may produce traffic without revenue attribution ever being wired in.
We build the pieces and the gaps, in that order.
| Dimension | Buying pieces | Growth engineering |
|---|---|---|
| Deliverable | A website, a report, a tool configuration | A working, instrumented system |
| Accountability | Each vendor owns their channel | One team owns the path from search to sale |
| Measurement | Per-channel metrics | Source to closed customer |
| The gaps between systems | Ownership often unclear | Explicitly owned |
| What you own afterwards | Access, sometimes | Code, accounts, data, documentation |
| When it breaks | You find out from a client | The system alerts you |
Public artifacts · measured builds
Ariadne is new, so there are no client logos here and no invented ROI. What exists instead is inspectable: one public system that turns an ambiguous research question into a repeatable automated pipeline, and one measured teardown of this website. Each is labelled with exactly what the evidence supports and what it does not.
How do you test whether an AI agent’s stated reasoning actually drives its answer? Our applied AI team designed and implemented a Python workflow that makes that question testable.
Did the stated reasoning actually matter to the answer?
Capture → intervene → rerun → score → export.
The system captures an agent’s reasoning, applies controlled changes, reruns the agent, compares answers, flags possible faithfulness problems, and exports structured results.
This is the same discipline a growth system needs: define the question, instrument the process, run it repeatably, and export results someone else can check. The domain was AI safety. The method is what you are buying.The live site was inspected on August 3, 2026. The receipt below records the August 4 release that addressed those findings; it predates the current expansion and is retained as a dated baseline.
Lighthouse 13.4.1 mobile lab · local production build · Chrome 150 · August 4, 2026. Every system our teams build ships with a dated baseline like this one, so performance is measured at handover rather than asserted in a pitch.
Where the work can be measured and the client gives written publication permission, a proposal may include a reduced fee for a founding case study. Every published study will follow the same structure: problem → baseline → system built → result → time window.
From diagnosis to system
You work directly with the engineers doing the diagnosis and the build. No account manager, no relay, no handoff to someone who was not in the room.
We trace how people find you, what they see, what happens when they act, who responds, how fast, and what gets recorded. The checkpoint with the strongest evidence of loss becomes the first priority, even if it is not the one you expected.
You get a system map, a defined scope, the measures we will judge it by, and a timeline before anything gets built. If part of what you asked for is not worth doing, that is in the document too.
We design, engineer, and connect the parts, including easy-to-miss edge cases: duplicate submissions, failed integrations, the lead that arrives at 2am, and the workflow that silently stops.
You receive the code, the accounts, the documentation, the analytics, and a measured baseline. Then we improve from evidence rather than opinion.
Clear starting points
Real engagements vary. These ranges exist so you can decide whether a conversation is worth your time.
Why the prices are published. Many firms in this space hide pricing so the number arrives after you are invested in the conversation. We would rather you decide whether this is affordable before either of us spends an hour on a call. The ranges are real starting points. The audit produces the actual number.
Growth system audit
For any founder who wants to know which checkpoint is broken before spending on the wrong one.
Credited in full against a build
Start with the auditSystem build
For a business ready to build or rebuild the machine the audit mapped.
Growth Systems Care
For a business with the machine in place that wants it monitored and improved.
What isn’t included. Third-party software subscriptions, paid media budget, photography, and video production are quoted separately or bought directly by you at cost. We do not mark up other people’s invoices.
Engineering-led delivery
Ariadne is a Toronto growth engineering firm, founded by software engineer and AI researcher Sourena Khanzadeh. Its teams cover diagnostics, web and conversion engineering, CRM and sales systems, automation, applied AI, demand, analytics, and post-launch care.
Ariadne exists because some problems that look like marketing problems are actually systems problems, and systems problems are an engineering discipline. The method is the same one used on any complex system: understand how it currently behaves, find the constraint, change one thing, measure what happened.
Work directly with our engineersDesign, code, and workflow decisions stay tied to the number they are supposed to move.
Automations include visibility, failure alerts, and a practical manual path.
You receive the accounts, code, documentation, and data your system depends on.
Qualified conversations matter more than traffic screenshots and vanity charts.
Straight answers
If your question is more specific, put it in the audit form. We answer it directly.
support@ariadne.fyiIt is building the machine that produces customers instead of operating it by hand. A marketing agency runs a channel. A consultant writes a recommendation. Growth engineering designs the connected path from first search to closed customer, builds it in code and configuration, and instruments it so you can see which part is working.
Owner-led service businesses where one new customer is worth several thousand dollars, the sale starts with a quote or consultation, and the founder is still personally involved in most deals. Roughly 3 to 25 staff. If manual follow-up is slowing the team down and nobody can say which channel produced last month’s revenue, there is usually a system worth building.
No. The nine checkpoints are a diagnostic view, not nine products to rebuild. The audit exists to find the two or three that matter, and a useful outcome may be a smaller project than the one you first had in mind.
No honest provider can guarantee a ranking, citation, or sales result. We can guarantee a defined scope, careful implementation, transparent measurement, and full ownership. We agree on the signals to improve—qualified inquiries, response time, booking rate, or visibility—then measure what changed.
Yes. Your business owns the source code, content, accounts, domain, and data. The handoff includes documentation and Git history, so another capable engineer can understand and maintain the work.
Usually not. The first step is understanding what already works. We prefer connecting the smallest reliable set of tools over adding another dashboard. If something should be replaced, you will see the tradeoff before we decide.
Ariadne is organised as capability teams — diagnostics, engineering, CRM and sales systems, automation, applied AI, demand, analytics, and systems care — so a project draws on whichever ones the diagnosis calls for. We staff engagements deliberately rather than filling capacity, and we tell you our availability before you commit rather than after. Where a project needs specialist capacity outside those teams—paid media, video, high-volume content—we bring in partners we have worked with and manage them, or we tell you to hire them directly and stay out of the markup.
Answer engine optimization makes your business easier for AI-assisted search tools to understand and cite. It is not a trick or a separate magic channel. We start with the same durable foundations search engines recommend: crawlable pages, clear factual content, real expertise, consistent business information, and useful structured data where it fits.
Your practical starting point
Send your website and a sentence about where the path feels stuck. You will get back a written review of all nine diagnostic checkpoints, the two or three highest-priority constraints supported by the available evidence, what it would take to fix them, and an honest note about anything that is not worth rebuilding.
If the answer is that your systems are fine and you just need more demand, that is what the review will say.