Heads & Hands:
Forward-Deployed RevOps Engineers for HubSpot

A Commercial Strategist who can rebuild your funnel logic, and a RevOps Engineer who can ship it the same week. One pair. One channel. One accountability for outcomes.

What "Forward-Deployed" means in plain English

Now OpenAI, Anthropic, Scale AI, Databricks, and Ramp all deliver the Forward-Deployed Engineer (FDE) model to enterprise customers.

We brought that model to HubSpot and B2B RevOps. The difference: because we live in one stack (HubSpot) and one domain (B2B revenue ops), our cycle time is days, not the 6–18 months an AI-lab FDE typically takes. You get the embedded-engineer benefits without the embedded-engineer price tag.

Who hires us

💼

B2B SaaS founders (Seed → Series B)

where the GTM motion needs to become an actual machine before scaling spend

📊

CROs and Heads of RevOps

who inherited a HubSpot instance that isn't producing pipeline and need it fixed without a 6-month consulting engagement

🤝

CMOs

generating MQLs that never become pipeline — and who need someone to rebuild the conversion path, not just audit it

💵

PE/VC portfolio companies

that need fast value creation inside the revenue stack post-investment

⏳

Founders

coming off spreadsheets who need HubSpot stood up properly the first time, not re-done in a year

The pair that scopes is the pair that ships

No junior handoffs. No account manager who learned Workflows last month. Every engagement includes both.

Heads

Full-funnel B2B GTM — ICP definition, buyer personas, MQL/SQL definitions, lead scoring, account-based motions, segmentation.
Outbound at scale — messaging architecture, multi-touch sequencing, deliverability infrastructure. 100–1,000 touches/day per sender.
Conversion path design — triggers, scoring shifts, and handoffs that move contacts from cold to closed-won. Not a diagram — a deployed system.
Sales execution — MEDDPICC, BANT, SPICED qualification, pipeline stage definitions, forecasting discipline, win/loss loops.
AI-native RevOps — where Breeze, Claude, GPT, and custom LLMs actually move pipeline metrics. Deploying AI in HubSpot before HubSpot had Breeze.
Service & retention — lifecycle marketing, expansion motions, churn forecasting, NRR/GRR instrumentation.

Hands

Custom workflow architecture — Marketing, Sales, Service, Content, Ops Hubs. Branching logic, error handling, workflows behind the workflows.
API integrations — HubSpot ↔ Stripe, BigQuery, Snowflake, Smartlead, Apollo, Clay, ZoomInfo, OpenAI, Anthropic, custom RAG pipelines.
Custom objects & data models — deals-to-accounts-to-products-to-renewals. Not HubSpot's defaults forced onto your business.
Reporting & attribution — UTM governance, multi-touch attribution, custom dashboards, exec-ready revenue views.
Lead scoring & lifecycle engines — model design, threshold calibration, decay logic, monthly recalibration.
CRM migration at scale — Salesforce / Pipedrive / Zoho / Close / spreadsheets → HubSpot, without breaking active pipeline.

What makes the engagement different

Six things agencies say. Six things we actually do.

💬

We embed

Slack, your HubSpot, calls with your team. Not a separate "agency portal" with weekly status PDFs. In your stack from day one.

⚠️

We accept underspecified problems

"We're losing deals after demo and we don't know why" is a valid brief. We diagnose before we build. You don't need to write the spec.

📅

We ship in days, not quarters

Working prototype → test → deploy. No "Phase 2" that never happens. Shipped artifacts, measured against your baseline.

🎯

We're accountable to outcomes

Pipeline created, MQL→SQL conversion, sales cycle length, CAC payback. Not deliverable checklists. If we don't move the metric, you don't continue.

⏹️

We say no

When the Forward-Deployed model isn't the right fit, we say so on the first call. We don't take work that should go to a junior freelancer.

⚒️

Proprietary tooling

We carry our own outreach + CRM enrichment platform (ScaleboX App) into engagements when it accelerates outcomes. 100s of field-tested RevOps patterns ready to deploy.

Typical engagement types

1. Conversion path rebuild

Diagnosing and rebuilding where MQL→SQL is leaking. Triggers, scoring, handoffs — deployed, not diagrammed.

2. Outbound infrastructure

Sequences, warmed domains, deliverability, reply handling. High-volume motions from 100 to 1,000 touches/day.

3. CRM migration

Salesforce / Pipedrive / Zoho → HubSpot without breaking active pipeline. Data model first, migration second.

4. PQL pipelines

Product event tracking into HubSpot for PLG motions. Identify ready-to-buy signals from usage data.

5. Attribution & source tracking

UTM governance, multi-touch attribution, custom dashboards across multi-channel demand gen.

6. HubSpot from scratch

Full instance setup for companies off spreadsheets. Proper data model, not a default that gets rebuilt in a year.

7. Tech stack rationalization

Replacing 4–6 point tools with HubSpot-native equivalents. Fewer tools, cleaner data, lower spend.

8. AI / Breeze deployments

Agents and automations that produce measurable revenue lift — not demos, not pilots, not "exploration."

Why Trust Us

400+ Projects

across countries and industries

Hubspot Partner

HubSpot Diamond Solutions Partner, App Partner, Startup Partner

100+ Patterns

for RevOps, field-tested, ready to deploys

Outreach Platform

In-house ScaleBoX App for outreach & CRM enrichment

How to start

30-minute discovery call

We listen to the actual problem, not your prepared brief.

Scoping note within 2–3 business days

What we'd actually do, ranked by outcome impact, with a fixed price for the first sprint.

First sprint: 1–4 weeks

Fixed scope, shipped artifacts, measured against your baseline. If we don't move the metric, you don't continue.

After the Sprint:

Ongoing embedded engagement, productized retainer, or clean handoff to your internal team — your choice.

Your HubSpot is underperforming.

Tell us what's broken -

We'll come back with a real point of view.