Broken API hooks
Zapier integrations failing silently. Webhooks 4xx-ing into the void. The form said "thanks!" but nothing reached your CRM.
Saor Systems · Data Engineering & AI Consultancy
I audit the data communications
your business depends on.
Stop leaving $500 a day on the table.
Roofing. HVAC. Construction. High-ticket trades. Most established businesses lose 15–20% of their leads to silent data failures — broken API hooks, slow response times, disconnected CRM data. I find them. You plug them. Localized AI. Your data stays yours.
- Localized AI · Gemma 3, DeepSeek-R1
- Private by design · on-prem only
- Engineering, not marketing
The Problem
Your leads are vanishing into broken pipes.
Marketing agencies optimize the funnel they can see. The leaks are upstream — in the plumbing they can't read.
Slow server response
TTFB over 800ms = a third of mobile leads bounce before the form loads. You'll never see them in analytics — they were never measured.
Unoptimized capture scripts
Forms that double-fire, validation that locks out real customers, mobile keyboards that hide the submit button. Death by a thousand papercuts.
Disconnected CRM data
Leads in three different inboxes. No single source of truth. Follow-up windows blown because nobody knew the lead existed for six hours.
These aren't marketing problems. They're engineering problems. That's why agencies miss them.
How It Works
The three-phase audit.
A clean engineering process. No kickoff fluff. No quarterly retainers.
01
Deep Scan
Saor Core, my localized AI agent stack (Gemma 3, DeepSeek-R1), analyzes every layer of your communication stack: DNS, TLS handshakes, API hooks, form submission paths, webhook delivery, response budgets.
Output: a complete graph of every data path between your visitor and your sales pipeline.
02
Leak Detection
I correlate the scan against real telemetry — load times, error rates, CRM ingest deltas — to find where leads actually drop out, not where they should drop.
Output: ranked list of failure points with measured impact — "this leak costs you N leads per week."
03
The Roadmap
You get a technical plan you can hand to any developer. Specific failures. Specific fixes. Specific revenue-impact estimates.
Output: a remediation document — engineer-ready, no marketing speak. You decide whether to use my team, your team, or your existing dev shop.
Why Local AI
Your data never leaves your secure workstation.
If you handle customer names, addresses, project values, or supplier contracts — that matters.
- On-premise inference. Saor Core runs on dedicated hardware in my workshop. Nothing routes through OpenAI, Anthropic, or any third-party cloud.
- Not training fodder. Your business data isn't used to train public models. It can't be — it never gets there.
- Open-weight models. Gemma 3 (Google) and DeepSeek-R1. Auditable. Reproducible. Yours to inspect.
- Audit log. Every prompt, every response, every tool call — captured locally. Your compliance officer will love it.
"Most consultancies pipe your data through someone else's GPUs. I won't. The whole point of Saor is to keep the work where the work belongs — on your iron, not in someone's training set."
— James, founder · Saor Systems
Proof of Competence
This is what a scan looks like.
Live-style excerpt from an audit log. Real format. Sample data.
[boot] saor-core v0.4.2 — local inference: gemma3:12b, deepseek-r1:14b
Leak distribution
Estimated daily revenue at risk
7leads/day lost
$2.1krevenue/day at risk
~$63kover 30 days
Calculated from observed funnel deltas × avg ticket value. Final report includes full methodology and per-leak fix difficulty.
Sample deliverables
Download the sanitized sample audit.
This is exactly what you receive — engineer-ready, no marketing speak. Both files are real artifacts from a representative scan, with the target domain and identifiers replaced.
audit_2026-04-29.json
Machine-readable audit report. 5 findings, severity-ranked, with evidence, impact estimates, and remediation steps per leak.
Download →
roadmap_2026-04-29.md
Engineer-ready remediation document. Hand it to your dev shop. Each fix maps to a finding and includes effort and impact estimates.
Download →
Preview the JSON inline
{
"audit_id": "saor-aud-7f3c9e2a",
"saor_core_version": "0.4.2",
"engine": {
"runtime": "saor-core",
"host": "z420.workshop.local",
"models": [
{ "id": "gemma3:12b", "role": "log-correlation" },
{ "id": "deepseek-r1:14b","role": "impact-inference" }
],
"isolation": "air-gapped (no egress to public inference APIs)"
},
"summary": {
"leaks_found": 5,
"by_severity": { "critical": 2, "high": 3 },
"estimated_daily_revenue_at_risk_usd": 2100,
"estimated_30day_revenue_at_risk_usd": 63000,
"confidence": "high"
},
"findings": [
{
"id": "saor-find-001",
"severity": "critical",
"category": "crm_ingest",
"title": "Pipedrive webhook ingest delta — 14% of submissions never arrive",
"estimated_impact": {
"leads_lost_per_day_range": [1, 3],
"revenue_at_risk_per_day_usd_range": [300, 900]
},
"estimated_fix_effort_hours": 6
}
/* … 4 more findings in the full file … */
]
}Field Notes
The patterns we look for.
Three failure modes that show up over and over in trade businesses. Engineer observations, not testimonials. Real client case studies will be published here once those clients sign off — until then, this is what to expect us to find on your site.
The CRM ingest delta
WordPress + Zapier + Pipedrive (or Salesforce, or Jobber) is the most common stack we audit. We routinely find that 10–18% of form submissions never become CRM records — the form said "thank you," the lead never made it into your pipeline, the customer called a competitor while waiting for a callback that was never going to come.
Typical fix: 6 engineer-hours. Typical recovery: 1–3 leads/day.
The task-quota cliff
Trades on Zapier or low-tier automation tiers often blow through monthly task quotas mid-month and don't realize it. The most important zaps — lead routing, SMS follow-up, calendar invites — start failing silently. The marketing agency has no visibility because they don't watch automation telemetry. We catch it on the first scan.
Typical fix: 8–10 engineer-hours, often paired with a migration off Zapier.
The TLS + form-UX combo
Slow handshakes, render-blocking scripts, and submit buttons hidden under iOS keyboards combine into a quiet ~30% mobile session loss at the p95. Service trades get most of their leads from mobile. This is the silent killer most agencies don't measure because their dashboards report on visits, not on completed conversions per device.
Typical fix: 6–9 engineer-hours across TLS, deferred scripts, and form layout.
Note on social proof: Saor Systems is in early launch. Real named case studies (with named clients, signed quotes, and verified before/after numbers) are published here only after explicit client permission. Until then, the patterns above are the honest ground truth — what we look for and what we typically find. Verifiable on request during a discovery call.
About
I'm a Data Communications Engineer.
Not a marketer. Not a copywriter. I don't write your ads or A/B test your headlines.
I find the broken pipes between your traffic and your sales — the ones agencies can't see because they don't read code, don't trace HTTP requests, and don't audit webhook delivery.
That's the gap. That's what's costing you 15-20% of your leads. That's what I fix.
The Tooling
Saor Core.
A localized AI agent stack I built and run on dedicated hardware in my workshop. It does the heavy lifting on every audit — pattern detection across thousands of HTTP transactions, anomaly correlation, automated reproduction of failure modes.
Open-weight models (Gemma 3, DeepSeek-R1). Air-gapped from the public internet for client-data work. Updated continuously — I am in the trenches with the tooling, not coasting on a 2-year-old playbook.
Ready
Book the scan.
A 15-minute discovery call. Free. If there's no leak worth fixing, I'll tell you.