Trust the forecast
Replace opinion-led pipeline calls with governed stages, live deal data and clear inspection rules.
Revenue architecture for UK B2B companies
Your CRM is not the problem. The revenue system behind it is.
Headless Revenue helps UK B2B teams rebuild the architecture behind sales, marketing, success, finance, data and AI so leadership can trust the forecast, reduce manual work and scale without operational drag.
Architecture before automationGovernance before AIRevenue truth before dashboards
01Revenue
02Process
03Data
04CRM
05Automation
06AI
The architecture behind predictable revenue.
What headless means for AI
One intelligence layer across every revenue tool.
Headless Revenue separates the intelligence from the interface: every app can feed the model, every model output can trigger governed action, and every team receives the answer where they already work.
Applications
InputsSalesforce
HubSpot
Stripe
Gong
Pipedrive
Notion
Zendesk
Sheets
context
LLM orchestration layer
Revenue brain without a new front end.
Permissions
Memory
Rules
The model reads governed context, reasons across systems, then sends the right output to the right channel with auditability and human review where needed.
decisions
Actions
DoRoute
Assign leads, tasks and risk alerts
Write
Draft emails, briefs and deal notes
Update
Clean CRM fields and next steps
Insights
KnowForecast
Pipeline movement, commit risk and gaps
Signal
Churn, expansion and stalled-deal triggers
Explain
Board-ready narrative from live systems
Delivered into channels
SlackEmailCRMTeamsDashboardsWorkflows
Growth exposes the system nobody owns.
The symptoms look familiar: forecast debates, CRM mistrust, manual handoffs, duplicate data and leaders asking five teams for one number.
Why is the forecast unreliable?
Which team owns this data?
Why is the CRM full of noise?
Where do handoffs break?
Which tools duplicate work?
What should AI be allowed to do?
Which reports can leadership trust?
What should we fix first?
Commercial systems that move the numbers.
Not RevOps theatre. Not AI demos. Practical architecture for the way revenue actually moves.
Clean the CRM
Fix fields, ownership, routing, duplication and lifecycle logic so the system reflects how revenue really moves.
Connect the stack
Align CRM, marketing automation, billing, CS, finance and data tools around one operating model.
Reduce manual work
Automate handoffs, approvals, enrichment, hygiene alerts and reporting without losing human control.
Prepare for AI
Create the data, permissions, process boundaries and semantic layer that make AI agents useful and governable.
Scale without hiring first
Give growing revenue teams the architecture and operating cadence they need before adding more headcount.
Revenue Systems Audit
Start with the leaks.
Before buying another tool, map where revenue trust, ownership and execution are breaking.
01
Diagnose
Map the revenue lifecycle, systems, data ownership and where confidence breaks.
02
Simplify
Remove process noise, unused fields, unclear stages and reporting that no longer helps decisions.
03
Architect
Design the target CRM, lifecycle model, integrations, governance and automation layer.
04
Implement
Build the workflows, dashboards, data controls and operating cadence inside the existing stack.
05
Enable
Document, train and embed the rules so Sales, Marketing, CS, Finance and leadership use the same model.
06
Improve
Measure adoption, conversion, forecast confidence, manual work and operational reliability.
From diagnosis to operating system.
Services are designed as one connected revenue architecture, not separate consulting tracks that leave the stack more fragmented.
A practical build path for CRM, data, automation and AI readiness.
01
Revenue Systems Audit
A focused diagnostic across pipeline, CRM, data quality, handoffs, reporting and stack overlap.
02
CRM & Salesforce Architecture
Data models, stage governance, system-of-record design, release discipline and platform standards.
03
Fractional RevOps Leadership
Embedded senior ownership for revenue systems, operating cadence and cross-functional execution.
04
Lead-to-Cash Architecture
The flow from lead capture to qualification, CPQ, billing, renewal, expansion and finance visibility.
05
AI Revenue Operations
Governed AI workflows and agents for forecasting, hygiene, enrichment, routing and executive insight.
06
Data Governance & Reporting
Metric definitions, ownership, dashboards and controls that make revenue data trusted.
07
Automation & Integration
API-first workflows connecting CRM, marketing, CS, billing, finance and data platforms.
Where the architecture usually pays back.
Concrete operating problems across the revenue lifecycle, not vague transformation claims.
Forecasting
Deal stages, commit logic, inspection views and AI-assisted risk signals for leadership confidence.
Pipeline Governance
Qualification, hygiene alerts, stage controls and MEDDPIC/Bowtie logic built into the CRM.
Sales-to-CS Handoffs
Renewal, expansion, onboarding and churn-risk workflows connected across revenue teams.
Billing & Finance
Failed payments, CPQ, invoicing, dunning and finance signals surfaced where teams act.
Marketing Attribution
Campaign, account and lifecycle data tied to opportunities, revenue and customer outcomes.
Executive Reporting
Board-ready dashboards based on shared metric definitions and trusted data ownership.
AI Agents
Bounded agents for enrichment, deal summaries, forecast review, data hygiene and workflow triage.
01Revenue model
02Lifecycle process
03Data ownership
04CRM and stack
05Automation layer
06AI agents
07Measurable outcome
How we think
Do not bolt AI onto a system your team already distrusts.
Useful automation depends on clear process, governed data and explicit decision rights. Once those foundations exist, AI can improve forecast review, enrichment, hygiene, routing, summaries and executive insight.
Built for the UK scale-up operating gap
Many B2B teams are too complex for founder-led CRM admin, but not ready to hire a full senior RevOps and enterprise systems function.
Headless Revenue fills that gap: senior architecture, hands-on implementation and operating cadence without forcing a permanent hire before the system is ready.
Best fit: B2B SaaS, technology, services and revenue-led companies with 20-250 commercial users, a CRM in place, and leadership pressure for better revenue visibility.
Founder-led
Fábio Magalhães
Revenue and enterprise systems architect with hands-on experience across Salesforce, platform governance, revenue architecture, data, automation and AI-enabled workflows in complex B2B and enterprise environments.
"Headless Revenue exists for the moment when growth is no longer limited by demand, but by the system behind the revenue team."View LinkedIn profile
Revenue Systems Diagnostic
Find where your revenue system is leaking.
Share the context behind your CRM, forecast, handoffs, data or automation challenge. The first conversation should clarify what to fix, what to ignore and what to sequence.