01
GA4 says one number. Your bank says another. Nobody knows which one to trust.
Data & automation engineering for revenue teams
The data infrastructure your revenue actually runs on.
We build the data pipelines, AI agents, and system integrations that run real businesses — true ROAS and attribution, marketplace and ERP automation, and the reliability underneath all of it.
Built on the tools you already run
Google Analytics 4
Google Ads
Meta Ads
X Ads
NetSuite
SAP / Oracle
Shopify
Slack
BigQuery
dbt
Document AI
Looker Studio
Cloud Run
Systems in production for ecommerce and DTC teams
0%
Comms automated
0
dbt models in production
−0%
Cloud infra cost
“Dashboards used to be the finish line. Now they’re the input — an AI agent reads the same numbers and acts on them before a person opens the report.”Rick Halstyan · Data & Product Analyst, Twinslytics
Sound familiar?
You don't have a dashboard problem. You have a truth problem.
02
You have dashboards nobody opens — and the ones you check don't change a single decision.
03
You want to put AI to work, but your data is too scattered and messy to build anything on.
What we do
Five things, done to production standard.
01
Marketing analytics & true ROAS
Connect Meta, Google, your CRM and ERP into one source of truth. Optimize on real closed revenue and true ROAS — not platform-reported conversions. This is where most of the money hides.
See a case study →Ad platforms2.1×
Real closed revenue4.8×
Correction+128%
02
AI agents & automation
Chat-based bots and ops agents that read, decide, and act inside the tools you already use — Slack, Teams, email, whatever's in place — with every write gated behind a human confirmation.
20+ countries, one pipeline1 of 5 steps left for a human
See a case study →
03
Marketplace & ERP integration
Marketplaces and ERPs that were never meant to talk to each other, wired into one automated pipeline — order-to-fulfillment, inventory sync, whatever the flow needs. Any stack: NetSuite, SAP, Oracle, Shopify, and beyond.
0 manual order entriesContinuous inventory sync
See a case study →
04
Data engineering & pipeline reliability
Warehouses and pipelines that fail loudly instead of silently — schema drift, cost blowouts, and the reconciliation that catches a platform quietly disagreeing with itself before it costs you a decision.
−95% nightly scan$6.9k/day caught double-counted
See a case study →
05
SEO systems & content operations
Technical SEO and the automation that ships pages on a schedule — for sites stuck with nothing happening in search — plus bulk edits (titles, images, copy) across a whole network of sites at once.
150+ inbound leads$0 ad spend
See a case study →
Reporting
Reports your clients actually read.
Clear, real-time, on-brand dashboards that answer one question — where the money comes from — without BI complexity or manual work. Live on desktop and phone.
See a live exampleor try the free True ROAS calculator
True ROAS
4.8×
Revenue
$312K
CAC
$41
↑ swap for a real Looker Studio screenshot
Selected work
Systems that run every day, in real businesses.
SEO · Content systems
Took reprolegal.com out of Google's sandbox
Built the technical SEO and content system for our own site from scratch — structure, indexing, and a generator that ships new pages on a schedule. It cleared Google's sandbox and started bringing in inbound leads with zero paid traffic. Read the case study →
150+
Inbound leads, zero ad spend
Automation · Marketplaces & ERP
End-to-end order automation across marketplaces and an ERP
A manufacturer had every marketplace order keyed into their ERP by hand. We built the pipeline that closes the loop automatically — order in, shipment confirmed, inventory synced across every channel. Same pattern, any stack. Read the case study →
0
Manual order entries
AI agent · Finance ops
Turn a chat message into an approved invoice
A company keyed every vendor invoice into their ERP by hand. Our bot reads a message or a PDF, extracts the line items, and routes it for approval before it ever touches the accounting system. Read the case study →
1 of 5
Steps left for a human
Data engineering · Ad spend
Caught a doubled ad spend line and an $11B phantom revenue bug
A daily reconciler between the ad accounts and the warehouse — built to catch silent failures, not just mismatches. Found a connector double-writing spend, a data export failing silently behind a green checkmark, and a currency bug that turned $1,294 into $11.07 billion in GA4. Read the case study →
$6.9k/day
Double-counted spend, caught
AI agent · Media buying
Automated campaign launches across dozens of countries
A media buyer built every campaign by hand from Drive creatives and a spreadsheet. Our agent scans both and creates the full campaign — cards, ad groups, budgets, UTMs — paused and ready for one click, with every API call logged and reversible. Read the case study →
20+
Countries, one pipeline
Marketing analytics · Ad reporting
Turned day-old ad reporting into hourly
Spend decisions were running up to 30 hours behind. We built an hourly pipeline across Google Ads, Meta, and X reconciled to the cent against the daily numbers — and fixed a conversion-value bug that was overstating value by up to 76×. Read the case study →
30h→1h
Reporting lag, multi-brand
Data engineering · BigQuery
Cut a nightly BigQuery scan by 95%
Two months of raising the timeout hadn't fixed the nightly pipeline failures. The real cause was unpartitioned sources scanning the full history every night — measured, fixed, and verified value-for-value, not just row counts. Read the case study →
−95%
Nightly scan, 0 timeouts
Why Twinslytics
The hard part isn't the dashboard. It's the plumbing underneath.
01
Engineers who speak revenue
We came out of marketing analytics, so we build for the number that matters — money — not vanity metrics that look good in a deck.
02
Production, not prototypes
Our systems run daily in the real world, with monitoring and alerting. When something breaks at 3am, it's built to tell you.
03
We own the messy middle
The real work is the integration between systems that were never meant to talk. That's exactly the part we do best.
Who you work with
Three engineers. No handoffs.
Vlad Halstyan
Data & Platform Engineer
Builds the pipelines, integrations, and cloud infrastructure — from ad platforms and CRMs to ERPs — and turns raw, scattered data into a clean warehouse the whole business can trust. Automation that runs in production, not in a slide.
Rick Halstyan
Data & Product Analyst
Turns the data into decisions — attribution, cohorts, and reporting that shows where the money comes from. Builds AI agents and chatbots, and applies ML to forecast and segment, so you act on what's next, not just what happened.
Tigran
Full Stack Developer & Data Engineer
Ships the AI agents, bots, and full-stack systems that turn a manual workflow into software — from chat-based tools to marketplace and ERP integrations, running in production, not a demo.
You work with the people who build it. No account managers, no layers, no telephone game between you and the engineer writing the code.
Get in touch
Let's find your real numbers.
Tell us where your data hurts — the untrusted dashboard, the number that never matches, the process you're still doing by hand.
Got it — we'll be in touch shortly.