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I build the revenue infrastructure most B2B teams can’t.

I work with B2B companies where post-capture leakage is killing pipeline math. Four or five engagements a year, boutique by design. You own the system when I walk away.

Book a 30-min call See how I work
Live in production. 412 signals routed today.
Clay, n8n, HubSpot, Salesforce, Claude, OpenAI, Segment, Postgres, Supabase, Apollo, Smartlead, Airtable, LeadMagic

What I build

Four phases. One operator.

Diagnose, Architect, Build, Activate and Transfer. You can engage on any phase, or all of them. Most clients run the full sequence in 4 to 8 weeks.

  1. Diagnose

    A 2-week look at what you actually have. I map signal sources, attribution gaps, tool sprawl, and handoff leakage. Honest read, not a sales audit.

    Ends with: a GTM infrastructure audit you can act on

  2. Architect

    The blueprint before the build. Data flows, pipeline topology, tool roles, integration contracts. What's custom, what's bought, what's ripped out.

    Ends with: a blueprint your team can build against

  3. Build

    I implement the system end-to-end. Clay workbooks, n8n workflows, HubSpot architecture, AI qualification, attribution. In production, not in slides.

    Named delivery patterns

    • Agent-based GTM infrastructure

      Agent stacks for qualification, enrichment, lifecycle, orchestration. The Cerebrium build cut AI operating cost 95% ($10.5K to $467/mo).

    • Open-source-stack GTM infrastructure

      n8n, Ollama, Qdrant foundations. Cost-efficient and sovereign. Talked through at Warsaw IT Days 2026; taught in the Udemy GTM Engineering 101 course.

    Ends with: infrastructure running in production, with weekly progress you can see

  4. Activate + Transfer

    Team training, documentation, handoff. You own the system and the runbook when I walk away. No agency dependency, no monthly retainer.

    Ends with: 30 days of daily Slack during handoff, then you run it · Open-source foundation

How I work

Five steps. You see the system at every one.

Most agencies run discovery, then disappear into a Notion doc for six weeks. I work in the open. You see what I'm building as I build it, and you keep everything when I leave.

  1. A 30-minute call, no deck

    I want to know what's actually broken: where pipeline math falls apart, what tooling you've stitched together, what your team is doing by hand. If we're a fit, you'll know on the call. If we're not, I'll tell you who is.

    Outcome: a clear read on whether infrastructure is the right lever

  2. Diagnose: I map your stack in two weeks

    I trace signal sources, attribution gaps, tool sprawl, and handoff leakage. I sit with your reps, RevOps, and data. You get an audit document and a prioritised list of what to rebuild and what to leave alone.

    Outcome: an audit you can act on without me

  3. Architect: the blueprint before the build

    Pipeline topology, data flows, tool roles, integration contracts. We agree what's custom, what's bought, and what's ripped out. Nothing gets wired until the architecture is signed off.

    Outcome: a blueprint your team can build against

  4. Build: I ship the system in production

    I write the code, configure the stack, wire the integrations. Clay workbooks, n8n workflows, HubSpot architecture, AI qualification, attribution. You see weekly progress in the live system, not in a status deck.

    Outcome: infrastructure running on real traffic

  5. Activate and Transfer: you keep the keys

    I train your team, document every workflow, and stay on Slack for 30 days during handoff. After that, you run it. The code is yours, the data is yours, the runbook is yours. No retainer, no agency lock-in.

    Outcome: you own the system and the runbook

Numbers tied to mechanisms.

Three results from real systems. Every number names the verb and the stack underneath it.

  1. 95%

    realized AI operating cost reduction

    Cerebrium: $10.5K → $467/mo via multi-provider LLM routing, 90% prompt caching, semantic cache on Upstash Vector.

  2. 2.5×

    ARR (B2B SaaS client, mid-eight to nine figures)

    7-signal lead qualification system, multi-inbox outbound infrastructure, full-funnel attribution.

  3. 4 weeks

    typical build time

    Diagnose, Architect, Build, Activate, Transfer. Infrastructure live, team trained, keys handed over.

What I think

  • Most GTM consultants are top-of-funnel only. I build the full funnel.

  • Open-source GTM stacks beat SaaS sprawl — n8n + Ollama + Qdrant ships faster than Clay + HubSpot + Apollo.

  • The competitive moat in AI is orchestration, not the model.

Mathew Joseph, GTM Infrastructure Architect
Mathew Joseph GTM Infrastructure Architect

The operator behind GTM Wizard.io.

I'm Mathew Joseph. I architect, build, and ship GTM infrastructure for B2B SaaS companies that have outgrown the duct-taped Clay-plus-HubSpot-plus-Apollo stack. Not slide decks. Not retainers. Working systems with the keys handed over at the end.

Before I went solo, I led RevOps and growth engineering inside venture-backed B2B SaaS teams. The pattern repeated: pipeline math broke after the lead was captured, attribution went dark past the first touch, and reps spent two-thirds of their week on work software should have been doing. I started building the infrastructure to fix it. Then companies started asking me to build it for them.

Today I run four to five engagements a year. Based in the UK. Every system I ship is documented, transferable, and yours when I leave.

Selected for

  • Warsaw IT Days Speaker · 2026
  • AI DevCon Bangalore Speaker · 2026
  • JetBrains for Startups Mentor · 2026

Case study

A system I built.

B2B SaaS mid-eight to nine figures

Rebuilt a leaking GTM stack. Lifted ARR 2.5×.

7-signal lead qualification, multi-inbox outbound infrastructure, and full-funnel attribution wired into one system. Reps stopped copy-pasting between tools. The board got a pipeline number it could trust.

  • 7-signal qualifier
  • multi-inbox outbound
  • full-funnel attribution
Read the full case study