RevOps · Vilnius · UTC+2

Idea → System → Result.

Marketing & Revenue Operations manager — five years and five roles at CAST AI, from Customer Success to MOps Manager. I'm the person between a vague idea and a working result: I think the problem through, design the system, and see it shipped — whether that means GTM automation, an internal tool built by directing AI coding agents, or a team that knows what it's doing and why.

1. ReviewOpen ↗
open ./Algimantas_Stuopelis_CV.pdf
2. Contact
mail AL@elhaz.space

See It In Action

Algimantas
Fig. 01 — Operator

Capabilities

GTM Automation

Lead routing, scoring, and lifecycle automation across HubSpot and Salesforce — built to remove busywork, not add tools.

Attribution & Signals

Attribution models built on product-interest signals, so sales talks to the right people at the right moment.

AI-Directed Development

Full-stack apps shipped with AI coding agents. I own the architecture, data flow, and product decisions end-to-end.

Integration Debugging

When a sync silently fails, I find it — API payloads, network layer, proxies, webhooks. Systems-level, not guesswork.

Pipelines & Dashboards

Real-time data pipelines feeding dashboards people actually open. Telemetry in, decisions out.

People & Enablement

Led 30+ person support teams. Onboarding programs, training, documentation — and migrations like moving a sales org to Outreach.io in one week with zero downtime.

Projects

2025 — 2026Personal Project
Full-Stack · In Use

moniHZ — Live Fleet Telemetry

Problem33 unattended game clients on one machine, zero cross-client visibility — rare events missed, dead instances indistinguishable from quiet ones.

BuildA Node.js/Express server ingesting every client's events into one reconciled log, streamed live to a React 19 dashboard over SSE. Time-windowed cross-source deduplication keeps the stats truthful; Discord webhooks push rare-event and health alerts; clients pick up config changes through a heartbeat endpoint.

OutcomeOne screen replacing manual check-ins — ~5,800 lines of TypeScript, 15+ endpoints, the fleet supervises itself.

React 19TypeScriptNode.jsExpressSSEDiscord API
Read Case Study →
2025 — 2026Personal Project
Desktop · Rust · Working

moniRAM — Desktop Session Manager

ProblemStaging and supervising dozens of client sessions on one Windows machine — credentials, launch queues, and process tracking — on top of a legacy app too heavy to maintain.

BuildA ground-up rebuild of a ~27,700-line .NET/WPF app into a Tauri 2 + Rust port with a deliberately smaller surface: DPAPI-encrypted credential vault in SQLite, a single command bridge, file-backed session state, and a test suite that fails the build if legacy modules creep back in.

Outcome107 Rust tests and 57 Playwright tests green — the port's limits are a build contract, not a promise.

RustTauri 2React 18.NET 8SQLiteDPAPI
Read Case Study →
2026Personal Project
Web + Mobile · Prototype

Bicycle Builder — Parts & Compatibility

ProblemBike builds fail at the workbench: mismatched standards (BSA vs BB86, freehub bodies, brake mounts) discovered after the parts arrive.

BuildA Next.js 16 + Expo monorepo on Supabase Postgres with row-level security. A rule-driven compatibility engine compares canonical part specs stored as JSONB; a scraper pipeline normalizes 286 parts from six sources; selected parts derive their own workshop-tool requirements.

OutcomeIncompatibilities flagged before checkout — ~24,300 lines, 17 compatibility tests passing. Honest label: prototype.

Next.js 16SupabasePostgresExpoTypeScriptZod
Read Case Study →
2025Personal Project
Computer Vision · Working

VelotFit AI

ProblemBike fit is expensive and opaque — riders buy frames on vibes, then pay to fix the consequences.

BuildA tool that combines manufacturer geometry data with the rider's body measurements to recommend sizing and fit adjustments. Includes AI video analysis of riding position and a simulator for testing angle changes before touching the bike.

OutcomeData-backed fit recommendations from a browser, before money changes hands.

AI Video AnalysisGeometry ModelingWeb App
All personal projects — architecture & debugging by me, keystrokes by AI coding agents. Screenshots redacted for privacy.

Experience

CAST AI
Marketing Operations Manager2025 – 2026
Attribution modeling on product-interest signals, advanced lead routing, webinar workflow redesign cutting prep time 30%+.
CAST AI
Marketing Operations Analyst2024 – 2025
Lead scoring rebuild (+17% lead-to-opportunity conversion), lead-stage automation, one-week Outreach.io migration.
CAST AI
Sales Operations Analyst2022 – 2024
Salesforce reporting and flows, inbound routing logic in LeanData, pipeline analysis with sales leadership.
CAST AI
Demand Generation · Customer Success2020 – 2022
Early-stage hire; grew with the company from CS into go-to-market operations.
Tesonet
CS Operations Manager · Team Lead2017 – 2020
Led a 30+ person support operation for major consumer VPN & cybersecurity products — 94% CSAT, sub-1:30 response times.

Need someone to think it through and see it shipped?

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Algimantas Stuopelis Vilnius · UTC+2 Built with AI agents © 2026