Los Angeles · Technical co-founder for equity

You have the company. Grigoryan builds the product.

Liana Grigoryan partners with founders as their technical co-founder, building apps and marketplaces end to end — for equity rather than an invoice. Three products have gone from empty repository to production and through App Store review. For founders who hold the market and the customers but not the person who can build it — and automate what should never need a person — this is that partnership.

Liana Grigoryan
3
Shown here, more on request
2
Native apps shipped
19
Person team led
175+
Pages indexed
Selected work
The Care Royal Live · Web, iOS, Android CFO · 2021–now
The Care Royal running in production
The Care Royal — onboarding in the live product

A multi-tenant platform that home care agencies run their day on: shift scheduling, caregiver and client records, applicant tracking, messaging and documents. Four roles — owner, manager, caregiver and family — each seeing a different product.

The work that matters most here is invisible: per-tenant isolation enforced at the database layer, so no agency can reach another's records even if the application code is wrong. Security that depends on the UI behaving is not security.

Caregivers clock in and out with GPS verification and the timesheet builds itself, then the platform computes gross, tax and net against current federal and California tables. When two payroll partners declined the applications, the integration was replaced with an in-house calculation engine — which removed the dependency and kept the platform out of the money-transmission path entirely.

Tegula Stone Live · Web, iOS, Android Product & Engineering · 2025–now
Tegula Stone running in production
tegulastone.com — contractor marketplace

A two-sided marketplace connecting homeowners with stone and tile contractors — quoting, bookings, messaging, reviews, and subscription billing driven by Stripe webhooks.

A production error-monitoring pipeline captures browser and backend faults, groups them by normalized signature, and alerts once per issue rather than once per occurrence — then does the less obvious half: filters out third-party scripts the business does not control. Most of the alerts were a bug in someone else's analytics beacon. An alert stream nobody reads is worse than none.

The most valuable finding was an uncomfortable one. Reconciling edge traffic counts against analytics showed our numbers overstated real demand by roughly thirty times — the rest was bots. A strategy had already been built on that figure, and killing a conclusion beats defending it.

Unified Savers Live · Web COO · 2024–now
Unified Savers running in production
unifiedsavers.com — consumer product

A consumer savings product built on a serverless edge stack with static generation, holding a 90+ Lighthouse performance score across the site. Content architecture, technical SEO and the automated publishing pipeline are all owned in-house.

Shipped, not prototyped
Tegula Stone live on the App Store
Tegula Stone — live on the App Store

Two of these are native apps built, signed and pushed through App Store and Google Play review in-house — certificates, provisioning, store listings and all. Most products never survive that last mile.

Three examples, not the full list — an e-commerce storefront, an internal operations agent and several under wraps are not shown here.

AI & automation

AI is used where it removes work that would otherwise need a person, and kept away from the parts that have to be exactly right. Every system below runs in production today, not as a demo.

Content at scale

Article generation on edge inference

A publishing pipeline that researches and drafts articles, running on Cloudflare Workers AI. It replaced a paid API that had quietly expired and stopped producing for five weeks. The replacement has no key to revoke and no per-article cost.

Autonomous operations

An operations agent that runs overnight

Every night it collects business data, scans six separate error sources, runs the SEO work, drafts marketing, then asks one question per business: what would win the next paying customer. The morning report is ready before the day starts.

Cost discipline

The right model for the job

Volume work — drafting, summarising, classifying — goes to a free tier. Judgement calls go to a stronger model. That split keeps inference cost near zero while the reasoning stays sound.

Guardrails

Deterministic where it counts

Audits count real faults in code; a model only prioritises and writes. Payroll maths is arithmetic against published tax tables, never inference. An AI that invents a problem is worse than no AI, so it never gets to decide what is true.

Approach

Shipping is the job

Code that is not in production has not been tested by anything that matters. Work goes all the way through review, signing, release and the monitoring that follows.

Measure before concluding

Numbers mislead more often than they lie. Every metric is reconciled against a second source before a plan is built on it, and the disagreement gets said out loud.

Leadership, not just delivery

A nineteen-person call centre operation, led to first place across the entire organization. Coordinating people is a separate skill from building systems, and a technical co-founder needs both.

Build your product for equity.

Share what you are building. If it is a fit, expect a call to talk through scope and what an equity split looks like.

Goes straight to Liana. No list, no newsletter.

M.B.A., University of Hertfordshire · B.A. Psychology, American Military University · U.S. Army, Sergeant (E-5)