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AI, revenue and data systems for B2B teams

We build three kinds of systems. Pick the one that matches your problem.

01 AI systems

Software takes over repetitive work. A person checks what matters.

Documents · reports · website checks · recurring tasks

4 services 02 Revenue systems

Find the right customers and give every lead an owner and a next step.

Clay · HubSpot · RevOps

8 services 03 Data foundation

Your forms, CRM and analytics share data you can trust.

Forms · CRM · product events · measurement

2 services
Start hereAI automation workshop: find your top five automations in half a day Not sure which one?Start with a Systems Readiness Review

01

AI systems and automation

AI workflows for defined business tasks, with clear inputs, checks and a person reviewing what matters.

Foroperations, finance, content and web teams with recurring work that follows rules

Catch broken pages before customers do

Website quality monitoring

Stop retyping invoices, forms and applications

Document processing

Hand a recurring task to an AI agent your team controls

Claude Code implementation

Run reports and data jobs on a schedule

OpenAI Codex implementation

How a first AI project is scoped, built and handed over

02

Revenue systems with Clay, HubSpot and RevOps

Target accounts, enrichment, CRM data and sales routing that give each qualified record a clear owner and next step.

ForB2B sales, marketing and RevOps teams on HubSpot, with or without Clay

1Find the right accounts

Get more good-fit accounts and contacts

Lead sourcing and enrichment

Act when target accounts show buying signals

Signal-based ABM

Cut the hours reps spend researching accounts

AI sales research and qualification

2Run a CRM sales can trust

Make pipeline and reporting reflect reality

HubSpot development and RevOps

Get every lead to the right person

Lead routing and workflow automation

Put dormant CRM records back to work

CRM reactivation

Fix forms and workflows that keep breaking

HubSpot support and maintenance

3Check before you build

Know what to fix first in Clay and HubSpot

Systems Readiness Review

All revenue-system services, tools and implemented work

03

Data and systems infrastructure

The connected base that AI and revenue workflows depend on: forms, CRM records, product events, automation and measurement.

Formarketing and growth teams, and SaaS startups building their first CRM and data stack

Make forms, CRM, automation and analytics agree

MarTech infrastructure

Set up CRM and product data that scale with a SaaS startup

Startup infrastructure

How engagements work

Three steps, one process at a time

  1. 1

    Review

    We map one workflow: the decision, the tools, the people and where information gets lost.

    You get: written findings and a plan

  2. 2

    Build

    We set the rules and pilot one path with real records, including exceptions.

    You get: a working, tested system

  3. 3

    Operate

    We document it, hand it to an owner on your side and adjust it as things change.

    You get: a runbook and optional support

Every engagement starts with a written scope: deliverables, the checks the work must pass, and the price.

Not sure where to start? Systems Readiness Review

Review one business workflow

Pick a process that costs you revenue, time or money. We review its data, systems, rules and owners, then tell you what to build first.

Book a 30-minute call
  1. Prioritized issue listWhat is broken, and what to fix first
  2. Workflow mapRecords, systems, owners and exceptions
  3. Checks for the buildHow you will know the fix works

Implemented work

Case studies

AI systems

A quality watcher for a growing comics catalog

Claude Code checks new pages and hands the team a ticket-ready backlog.

 AI systems

One growth view for an AI-written blog

A weekly dashboard OpenAI Codex keeps current from Search Console and GA4.

All case studies

Free tools and references

Inspect the work before you commission it

Lead Flow PlannerModel a Clay sourcing workflow HubSpot Routing Test LabSix routing scenarios with open files Clay Implementation FrameworkGuide and editable worksheets Sample project deliverablesA full synthetic project file set
All free tools and resources

Questions

Questions we can answer early

Do we need an AI project already defined?

No. Share the process or decision that is causing problems. We can examine the current workflow and decide whether AI, data work, an integration or a simpler process change is useful.

Does AI replace our current systems?

Usually not. We start from the systems you already use and add a component only when it has a clear role, reliable inputs and a way to review its output.

Can we start with one team or workflow?

Yes. A narrow pilot makes it possible to test data quality, ownership, exceptions and value before extending the design.

Which tools do you work with?

Most often HubSpot, Clay, n8n, Claude Code, OpenAI Codex and Google Analytics, alongside the systems you already run. Tools are chosen after the workflow review.

How is the scope agreed?

Every engagement starts with a written scope that lists the deliverables, the checks the work must pass and the price, before any build begins.

What happens after the build?

You receive a runbook, and a named owner on your side takes over the system. Ongoing support, such as HubSpot support and maintenance, is available as a separate scope.

What should your next system do better?

Tell us what your team is trying to decide or deliver, and where the current process slows down. We will suggest a focused first scope.

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