Support and CX operations
I run customer support in enterprise B2B SaaS, and I build the AI the function actually needs. Ten years in the queue and the org chart. This past year I shipped it for real: Throughscan, an independent support-ops audit that is live and taking payment, plus a paid iOS app, an internal support assistant, and document pipelines.
Ten years in enterprise B2B SaaS · Production AI, shipped and running
Where it started
Each of these answers one question I kept asking inside a support org and could never get a straight number on. They run entirely in your browser, nothing uploads anywhere. The full audit at throughscan.com now does both, and the rest of the read, on your own export.
A resolution rate is measured the moment you close a ticket. This measures what happens after: how often a resolved issue comes back as the same account opening the same kind of ticket inside a window you set. Upload a ticket export and see the honest number.
Open the tool →Before you ground an AI on your help center, you need to know what state it is in. Paste a Zendesk help-center URL and it reads every published article and flags what is quietly rotting: pages years out of date, near-duplicates, and articles too thin to answer the question.
Open the tool →From the Lab
An independent support-ops audit I built as its own product and business, now live and taking payment. A support leader uploads one ticket export and gets the read most dashboards hide: a plain-language diagnosis, their real median and p90 response times, what customers actually contact them about, and starter macros and a knowledge base drafted from their own history. Cloudflare Worker, Claude, and Stripe, with every figure computed in code or labeled a draft.
How it's built →An internal assistant I built at my day job. First I systematized that two-person team's knowledge, and with no added headcount we absorbed roughly 30% ticket growth over two years, driven by client and product expansion, at a 72% single-reply resolution rate. The assistant came after: I loaded a decade of judgment in once, so the answers I used to repeat now generate themselves, grounded and human-reviewed.
How it's built →A paid iOS app with a Claude-powered conversational guide: cost guardrails, crisis-safe escalation, on-device encryption, and App Store compliance. Live on the App Store, a subscription with a recurring AI cost and the unit economics worked out before launch.
How it's built →About
I'm Johnny Khabushani. I spent ten years inside enterprise B2B SaaS running support, success, and implementation: the migrations, the workflows, the escalations, and the systems underneath all of it. In the past year I started building production AI for the function, directing it end to end and shipping it: Throughscan, an independent support-ops audit that's live and taking payment, plus an internal support assistant, a paid iOS app, and document-extraction pipelines.
That combination is the point: AI does the implementation, and operations judgment decides what gets built, what will break, and what it should cost. Everything in the Lab is something I designed and run in production, with real users and real unit economics behind it.
If you're leading or building a support or CX function and you want AI that actually holds up, that's the background I bring to it.
Get in touch
If you're working on support, CX, or AI that has to hold up in production, say hello. I read every message.