// AI GTM transformation & marketing operations
I build the martech, data & AI systems that turn marketing strategy into predictable revenue.
Marketing operations and go-to-market engineering for B2B SaaS. 10+ years running Marketo, Salesforce, and the data and AI layer around them — architected as one system, with the code to go beyond any single platform.
// led by Taras Melnychenko · ex-Webflow · go-to-market engineer
$350→$90
Cost per demo, one paid program
3:1→7:1
Pipeline ratio improvement
~50 hrs/mo
Saved by brief-to-launch automation
10+ yrs
Marketing ops & GTM engineering
// what I do
Three ways I move your pipeline
Each engagement starts with the system, not the symptom. Here's where I work.
AI GTM Transformation
Put AI into the work, not the slideware
I embed AI and LLM agents into the everyday operations of your go-to-market team — triaging requests, enforcing governance, and turning briefs into launched campaigns — so the work gets faster and more consistent, not just more talked-about.
Marketing Operations & Martech Architecture
Run Marketo, Salesforce & HubSpot as one system
I architect and operate the full martech stack — automation platform, CRM, data pipelines, lead lifecycle, scoring, and attribution — so marketing strategy turns into pipeline you can measure and trust.
Tracking, Analytics & Compliance
Trustworthy data, captured compliantly
I build the measurement layer — Google Tag Manager, GA4, server-side tracking, consent, and offline-conversion pipelines — so you can capture the data you need to optimize spend without tripping over privacy regulation.
// selected work
Systems I've shipped
Anonymized case studies — the problem, the architecture, and the measurable result.
From campaign brief to launched program in one pipeline
Built a "control room" that turns a campaign brief into a live marketing-automation program and a published landing page, gated by one-click approvals in Slack.
~50 hrs/mo Execution time saved
// Series C B2B SaaS · ~$100M+ ARR
An AI agent that triages the marketing-ops request queue
Shipped a Slack-based AI agent that triages and resolves inbound marketing-ops requests on an extensible skill framework, deflecting routine questions away from the ops team.
3–5 hrs/day Team time reclaimed
// Late-stage B2B SaaS · distributed marketing team
Conversational UTM governance that enforces taxonomy org-wide
Replaced a brittle UTM spreadsheet/form with a conversational, LLM-powered builder that makes correct links the easy path and enforces campaign taxonomy across the whole org.
~10 hrs/wk Time saved
// B2B SaaS · distributed go-to-market team
// how I work
A clear path from messy to measurable
- 01
Audit
Map the current stack, data, and workflows. Find the gaps costing you pipeline and the work an agent should be doing.
- 02
Architect
Design the target system — platform, lifecycle, data pipelines, and where AI fits — and sequence the work by impact.
- 03
Build
Ship it hands-on: programs, pipelines, agents, and tracking — with the Python, SQL, and JavaScript to go beyond native features.
- 04
Hand off
Document everything and enable your team. You own durable systems, not a dependency on me.
// questions
What people ask before reaching out
What is AI GTM transformation? +
AI GTM transformation is the practice of embedding AI and LLM agents directly into the systems a go-to-market team runs on — campaign operations, request triage, tracking governance — so repetitive work is automated and the everyday work gets measurably faster. It is production tooling, not a strategy deck or a bolt-on chatbot.
What does a marketing operations consultant actually do? +
A marketing operations consultant owns the connective layer between marketing strategy and revenue: the automation platform, CRM, lead lifecycle, scoring, attribution, and data pipelines. I architect and operate that stack as one system — and write the Python, SQL, and JavaScript to connect tools when native features fall short.
Do you work with Marketo, HubSpot, or Salesforce? +
All three, and the data layer around them (Segment, Census, Clay, Snowflake, BigQuery). Marketo is my deepest platform; I run Marketo and Salesforce as a single system and have built and migrated HubSpot in both directions. I recommend the stack that fits your motion, not a vendor I am tied to.
How do you embed AI into marketing operations without breaking things? +
I start with an audit to find the agent-shaped problems — high-volume, rule-bound, currently manual — then ship one production agent end to end before scaling. Governance is built in, so AI speeds the team up without corrupting data or breaking campaign taxonomy.
What engagement formats do you offer? +
Three: a fixed-scope audit or assessment sprint to map your stack and find the gaps; a project engagement to build or rebuild a specific system; and a fractional/advisory retainer to operate and evolve your martech over time. We pick the format that matches the problem.
What size and type of company do you work with best? +
B2B SaaS, typically growth-stage to roughly $100M+ ARR, especially product-led or technically-minded teams. That said, an early-stage company with a clear AI or platform mandate is a strong fit too. The common thread is a team that wants marketing ops treated as engineering.
Let's build the system your go-to-market runs on.
Tell me where your marketing ops is stuck and I'll tell you what I would do about it. No pitch — a real conversation about the work.