Intelligent automation that pays for itself

I design lean automation systems for growing SaaS, e-commerce, and B2B service businesses to cut manual ops, reduce errors, and give your team time back for higher-impact work.

Book a short intro call

Send me a message

Services

What I offer

I start with a focused Audit, then build and maintain the systems that eliminate pain points and improve your margins.

Steps

Deliverables

Map workflow
As-is process
Interview team
Identify pain points
Review tools & data
Systems & data flow
Design automation
To-be process
Estimate ROI
90-day upside

Steps

Deliverables

Map workflow
As-is process
Interview team
Identify pain points
Review tools & data
Systems & data flow
Design automation
To-be process
Estimate ROI
90-day upside

Steps

Deliverables

Map workflow
As-is process
Interview team
Identify pain points
Review tools & data
Systems & data flow
Design automation
To-be process
Estimate ROI
90-day upside

Audit

Process Audit & Automation Roadmap

A structured review of your workflows, tools and data, with a prioritised 90-day automation roadmap and an estimated ROI.

Build

Implementation & integration

Design and implementation of lean automation systems that orchestrate your tools, reduce failure points, and support scalable growth.

What should we automate first?

Describe the workflow once, and I’ll design a lean automation that runs it reliably.

Add details

See flow

Run test

View docs

What should we automate first?

Describe the workflow once, and I’ll design a lean automation that runs it reliably.

Add details

See flow

Run test

View docs

What should we automate first?

Describe the workflow once, and I’ll design a lean automation that runs it reliably.

Add details

See flow

Run test

Keep your automation healthy over time

A care plan for monitoring, fine-tuning, and small enhancements.

Automated processes:

Core automations

Lead to invoice, onboarding, support

Care Schedule

Monthly monitoring

10:00 am to 10:30 am

Incident & error review

04:00 pm to 04:30 pm

Keep your automation healthy over time

A care plan for monitoring, fine-tuning, and small enhancements.

Automated processes:

Core automations

Lead to invoice, onboarding, support

Care Schedule

Monthly monitoring

10:00 am to 10:30 am

Incident & error review

04:00 pm to 04:30 pm

Keep your automation healthy over time

A care plan for monitoring, fine-tuning, and small enhancements.

Automated processes:

Core automations

Lead to invoice, onboarding, support

Care Schedule

Monthly monitoring

10:00 am to 10:30 am

Incident & error review

04:00 pm to 04:30 pm

Care

Ongoing improvement

Monitoring, fine-tuning, and small enhancements so your automations stay reliable as your organisation and team evolve.

About Chris

Who I am

I’m an automation architect with more than a decade of experience leading operational excellence, automation, and commercial strategy projects, including several years at Zalando.

Strategy & design

Clarifying what to automate, and why.

Strategy & design

Clarifying what to automate, and why.

Strategy & design

Clarifying what to automate, and why.

Systems & data

Linking tools so information flows reliably.

Systems & data

Linking tools so information flows reliably.

Systems & data

Linking tools so information flows reliably.

Teams & change

Making automation usable in real life.

Teams & change

Making automation usable in real life.

Teams & change

Making automation usable in real life.

From manual overload to measurable, scalable systems

A clear four-step process to cut manual work, increase your team’s efficiency, and build operations that scale.

Step 1

Discover

I map key workflows, data flows, and pain points so we know where automation will actually pay off.

Mapping current workflows..

Workflow map

Data flow

Bottlenecks

Manual steps

Edge cases

Mapping current workflows..

Workflow map

Data flow

Bottlenecks

Manual steps

Edge cases

Step 2

Design

I design a lean automation architecture with clear data structures, triggers, and safeguards.

class AutomationBlueprint:
def __init__(self, name, trigger, actions, safeguards):
self.name = name
self.trigger = trigger
self.actions = actions
self.safeguards = safeguards

lead_to_deal = AutomationBlueprint(
name="Lead to deal",
trigger="New qualified website lead",
actions=[
"Create deal in CRM",
"Post summary in Slack"
],
safeguards=[
"Skip if deal already exists",
"Alert if any step fails"
]
)
class AutomationBlueprint:
def __init__(self, name, trigger, actions, safeguards):
self.name = name
self.trigger = trigger
self.actions = actions
self.safeguards = safeguards

lead_to_deal = AutomationBlueprint(
name="Lead to deal",
trigger="New qualified website lead",
actions=[
"Create deal in CRM",
"Post summary in Slack"
],
safeguards=[
"Skip if deal already exists",
"Alert if any step fails"
]
)

class AutomationBlueprint:
def __init__(self, name, trigger, actions, safeguards):
self.name = name
self.trigger = trigger
self.actions = actions
self.safeguards = safeguards

lead_to_deal = AutomationBlueprint(
name="Lead to deal",
trigger="New qualified website lead",
actions=[
"Create deal in CRM",
"Post summary in Slack"
],
safeguards=[
"Skip if deal already exists",
"Alert if any step fails"
]
)
class AutomationBlueprint:
def __init__(self, name, trigger, actions, safeguards):
self.name = name
self.trigger = trigger
self.actions = actions
self.safeguards = safeguards

lead_to_deal = AutomationBlueprint(
name="Lead to deal",
trigger="New qualified website lead",
actions=[
"Create deal in CRM",
"Post summary in Slack"
],
safeguards=[
"Skip if deal already exists",
"Alert if any step fails"
]
)

Step 3

Build & integrate

I build robust automations in Make and Airtable, add AI agents where they help, and integrate everything with your existing tools.

Automation layer

Your tools

Automation layer

Your tools

Step 4

Launch & Improve

I test with real data, launch safely into production, and improve the automations based on how your team actually uses them.

Lead routing

Live and monitored

Onboarding workflow

Update in progress

Support Workflow

Up to date

Lead routing

Live and monitored

Onboarding workflow

Update in progress

Support Workflow

Up to date

Portfolio

Examples of what I automate

Swipe through a few representative automation projects I design for tech-forward SMEs.

B2B Services · Use case
Inbound lead intake & qualification
New leads from your website are validated, deduplicated, and logged in your CRM. The system enriches company data with AI, scores lead quality, notifies you in Slack, and sends prospects a confirmation email with next steps and a link to book a call.
Impact :
Validated, deduplicated lead capture from your website
AI-assisted company research and 1–10 lead scoring
Instant Slack notifications so follow-up doesn’t depend on inboxes
Automatic confirmation emails with calendar link and clear next steps
B2B SaaS · Use case
Implementation & onboarding command centre
When a deal is marked as won, the system creates a structured onboarding workspace that pulls in data from the CRM, billing, and product. AI helps turn that data into a tailored onboarding plan, assigns tasks across CS, ops, and tech, flags stalled accounts, and gives both your team and the customer a clear view of progress.
Impact :
Single source of truth for onboarding across teams
Tailored onboarding plans generated from deal and product data
Early warning when accounts stall or key milestones slip
Shorter time-to-value and fewer dropped implementations
E-commerce · Use case
Customer intelligence engine
Customer feedback from support tickets, reviews, returns comments, and social channels flows into one workspace. AI clusters themes, spots low-frequency issues scattered across agents and channels, links them to metrics like refunds or churn, and routes a clear problem statement with suggested actions to the right product, CX, or ops owner.
Impact :
Single view of customer feedback from support, reviews, returns, and social
AI surfaces hidden patterns humans miss because they’re rare or spread across agents
Issues ranked and framed by business impact (refunds, churn, repeat purchase)
Clear owners and suggested actions so feedback turns into concrete changes
E-commerce · Use case
Order to happy customer automation
Orders flow from the webshop into a central ops hub that syncs with fulfilment and support tools; clean orders go straight to the 3PL, while exceptions land in a Slack queue with one-click fixes. An AI returns agent reads customer requests and order context, applies your return policies, creates labels and draft replies where it’s safe to do so, and escalates edge cases to humans with clear guardrails.
Impact :
Far fewer manual touches per order, especially around exceptions and returns
Fewer “Where is my order?” tickets and repetitive returns emails
Faster, more reliable fulfilment against your shipping SLAs
Returns handled consistently by policy, with a clear trail in your ops hub
B2B SaaS · Use case
AI revenue intelligence cockpit
Data from your CRM, email, product usage, and billing flows into a single revenue workspace. AI scores and prioritises leads, suggests discovery questions and next best actions, highlights risky deals and high-potential accounts, and learns from wins and losses so your pipeline gets more accurate over time.
Impact :
Less time spent on manual research and qualification tasks
Consistent, transparent lead and account scoring across the team
Smarter conversations driven by AI-suggested questions and talking points
Systematic win/loss learning that feeds back into targeting and messaging
B2B Services · Use case
Inbound lead intake & qualification
New leads from your website are validated, deduplicated, and logged in your CRM. The system enriches company data with AI, scores lead quality, notifies you in Slack, and sends prospects a confirmation email with next steps and a link to book a call.
Impact :
Validated, deduplicated lead capture from your website
AI-assisted company research and 1–10 lead scoring
Instant Slack notifications so follow-up doesn’t depend on inboxes
Automatic confirmation emails with calendar link and clear next steps
B2B SaaS · Use case
Implementation & onboarding command centre
When a deal is marked as won, the system creates a structured onboarding workspace that pulls in data from the CRM, billing, and product. AI helps turn that data into a tailored onboarding plan, assigns tasks across CS, ops, and tech, flags stalled accounts, and gives both your team and the customer a clear view of progress.
Impact :
Single source of truth for onboarding across teams
Tailored onboarding plans generated from deal and product data
Early warning when accounts stall or key milestones slip
Shorter time-to-value and fewer dropped implementations
E-commerce · Use case
Customer intelligence engine
Customer feedback from support tickets, reviews, returns comments, and social channels flows into one workspace. AI clusters themes, spots low-frequency issues scattered across agents and channels, links them to metrics like refunds or churn, and routes a clear problem statement with suggested actions to the right product, CX, or ops owner.
Impact :
Single view of customer feedback from support, reviews, returns, and social
AI surfaces hidden patterns humans miss because they’re rare or spread across agents
Issues ranked and framed by business impact (refunds, churn, repeat purchase)
Clear owners and suggested actions so feedback turns into concrete changes
E-commerce · Use case
Order to happy customer automation
Orders flow from the webshop into a central ops hub that syncs with fulfilment and support tools; clean orders go straight to the 3PL, while exceptions land in a Slack queue with one-click fixes. An AI returns agent reads customer requests and order context, applies your return policies, creates labels and draft replies where it’s safe to do so, and escalates edge cases to humans with clear guardrails.
Impact :
Far fewer manual touches per order, especially around exceptions and returns
Fewer “Where is my order?” tickets and repetitive returns emails
Faster, more reliable fulfilment against your shipping SLAs
Returns handled consistently by policy, with a clear trail in your ops hub
B2B SaaS · Use case
AI revenue intelligence cockpit
Data from your CRM, email, product usage, and billing flows into a single revenue workspace. AI scores and prioritises leads, suggests discovery questions and next best actions, highlights risky deals and high-potential accounts, and learns from wins and losses so your pipeline gets more accurate over time.
Impact :
Less time spent on manual research and qualification tasks
Consistent, transparent lead and account scoring across the team
Smarter conversations driven by AI-suggested questions and talking points
Systematic win/loss learning that feeds back into targeting and messaging
B2B Services · Use case
Inbound lead intake & qualification
New leads from your website are validated, deduplicated, and logged in your CRM. The system enriches company data with AI, scores lead quality, notifies you in Slack, and sends prospects a confirmation email with next steps and a link to book a call.
Impact :
Validated, deduplicated lead capture from your website
AI-assisted company research and 1–10 lead scoring
Instant Slack notifications so follow-up doesn’t depend on inboxes
Automatic confirmation emails with calendar link and clear next steps
B2B SaaS · Use case
Implementation & onboarding command centre
When a deal is marked as won, the system creates a structured onboarding workspace that pulls in data from the CRM, billing, and product. AI helps turn that data into a tailored onboarding plan, assigns tasks across CS, ops, and tech, flags stalled accounts, and gives both your team and the customer a clear view of progress.
Impact :
Single source of truth for onboarding across teams
Tailored onboarding plans generated from deal and product data
Early warning when accounts stall or key milestones slip
Shorter time-to-value and fewer dropped implementations
E-commerce · Use case
Customer intelligence engine
Customer feedback from support tickets, reviews, returns comments, and social channels flows into one workspace. AI clusters themes, spots low-frequency issues scattered across agents and channels, links them to metrics like refunds or churn, and routes a clear problem statement with suggested actions to the right product, CX, or ops owner.
Impact :
Single view of customer feedback from support, reviews, returns, and social
AI surfaces hidden patterns humans miss because they’re rare or spread across agents
Issues ranked and framed by business impact (refunds, churn, repeat purchase)
Clear owners and suggested actions so feedback turns into concrete changes
E-commerce · Use case
Order to happy customer automation
Orders flow from the webshop into a central ops hub that syncs with fulfilment and support tools; clean orders go straight to the 3PL, while exceptions land in a Slack queue with one-click fixes. An AI returns agent reads customer requests and order context, applies your return policies, creates labels and draft replies where it’s safe to do so, and escalates edge cases to humans with clear guardrails.
Impact :
Far fewer manual touches per order, especially around exceptions and returns
Fewer “Where is my order?” tickets and repetitive returns emails
Faster, more reliable fulfilment against your shipping SLAs
Returns handled consistently by policy, with a clear trail in your ops hub
B2B SaaS · Use case
AI revenue intelligence cockpit
Data from your CRM, email, product usage, and billing flows into a single revenue workspace. AI scores and prioritises leads, suggests discovery questions and next best actions, highlights risky deals and high-potential accounts, and learns from wins and losses so your pipeline gets more accurate over time.
Impact :
Less time spent on manual research and qualification tasks
Consistent, transparent lead and account scoring across the team
Smarter conversations driven by AI-suggested questions and talking points
Systematic win/loss learning that feeds back into targeting and messaging
B2B Services · Use case
Inbound lead intake & qualification
New leads from your website are validated, deduplicated, and logged in your CRM. The system enriches company data with AI, scores lead quality, notifies you in Slack, and sends prospects a confirmation email with next steps and a link to book a call.
Impact :
Validated, deduplicated lead capture from your website
AI-assisted company research and 1–10 lead scoring
Instant Slack notifications so follow-up doesn’t depend on inboxes
Automatic confirmation emails with calendar link and clear next steps
B2B SaaS · Use case
Implementation & onboarding command centre
When a deal is marked as won, the system creates a structured onboarding workspace that pulls in data from the CRM, billing, and product. AI helps turn that data into a tailored onboarding plan, assigns tasks across CS, ops, and tech, flags stalled accounts, and gives both your team and the customer a clear view of progress.
Impact :
Single source of truth for onboarding across teams
Tailored onboarding plans generated from deal and product data
Early warning when accounts stall or key milestones slip
Shorter time-to-value and fewer dropped implementations
E-commerce · Use case
Customer intelligence engine
Customer feedback from support tickets, reviews, returns comments, and social channels flows into one workspace. AI clusters themes, spots low-frequency issues scattered across agents and channels, links them to metrics like refunds or churn, and routes a clear problem statement with suggested actions to the right product, CX, or ops owner.
Impact :
Single view of customer feedback from support, reviews, returns, and social
AI surfaces hidden patterns humans miss because they’re rare or spread across agents
Issues ranked and framed by business impact (refunds, churn, repeat purchase)
Clear owners and suggested actions so feedback turns into concrete changes
E-commerce · Use case
Order to happy customer automation
Orders flow from the webshop into a central ops hub that syncs with fulfilment and support tools; clean orders go straight to the 3PL, while exceptions land in a Slack queue with one-click fixes. An AI returns agent reads customer requests and order context, applies your return policies, creates labels and draft replies where it’s safe to do so, and escalates edge cases to humans with clear guardrails.
Impact :
Far fewer manual touches per order, especially around exceptions and returns
Fewer “Where is my order?” tickets and repetitive returns emails
Faster, more reliable fulfilment against your shipping SLAs
Returns handled consistently by policy, with a clear trail in your ops hub
B2B SaaS · Use case
AI revenue intelligence cockpit
Data from your CRM, email, product usage, and billing flows into a single revenue workspace. AI scores and prioritises leads, suggests discovery questions and next best actions, highlights risky deals and high-potential accounts, and learns from wins and losses so your pipeline gets more accurate over time.
Impact :
Less time spent on manual research and qualification tasks
Consistent, transparent lead and account scoring across the team
Smarter conversations driven by AI-suggested questions and talking points
Systematic win/loss learning that feeds back into targeting and messaging

DRAG TO EXPLORE

B2B Services · Use case

Inbound lead intake & qualification

New leads from your website are validated, deduplicated, and logged in your CRM. The system enriches company data with AI, scores lead quality, notifies you in Slack, and sends prospects a confirmation email with next steps and a link to book a call.

Impact :

Validated, deduplicated lead capture from your website

AI-assisted company research and 1–10 lead scoring

Instant Slack notifications so follow-up doesn’t depend on inboxes

Automatic confirmation emails with calendar link and clear next steps

B2B Services · Use case

Inbound lead intake & qualification

Impact :

Validated, deduplicated lead capture from your website

AI-assisted company research and 1–10 lead scoring

Instant Slack notifications so follow-up doesn’t depend on inboxes

Automatic confirmation emails with calendar link and clear next steps

B2B SaaS · Use case

Implementation & onboarding command centre

When a deal is marked as won, the system creates a structured onboarding workspace that pulls in data from the CRM, billing, and product. AI helps turn that data into a tailored onboarding plan, assigns tasks across CS, ops, and tech, flags stalled accounts, and gives both your team and the customer a clear view of progress.

Impact :

Single source of truth for onboarding across teams

Tailored onboarding plans generated from deal and product data

Early warning when accounts stall or key milestones slip

Shorter time-to-value and fewer dropped implementations

B2B SaaS · Use case

Implementation & onboarding command centre

Impact :

Single source of truth for onboarding across teams

Tailored onboarding plans generated from deal and product data

Early warning when accounts stall or key milestones slip

Shorter time-to-value and fewer dropped implementations

E-commerce · Use case

Customer intelligence engine

Customer feedback from support tickets, reviews, returns comments, and social channels flows into one workspace. AI clusters themes, spots low-frequency issues scattered across agents and channels, links them to metrics like refunds or churn, and routes a clear problem statement with suggested actions to the right product, CX, or ops owner.

Impact :

Single view of customer feedback from support, reviews, returns, and social

AI surfaces hidden patterns humans miss because they’re rare or spread across agents

Issues ranked and framed by business impact (refunds, churn, repeat purchase)

Clear owners and suggested actions so feedback turns into concrete changes

E-commerce · Use case

Customer intelligence engine

Impact :

Single view of customer feedback from support, reviews, returns, and social

AI surfaces hidden patterns humans miss because they’re rare or spread across agents

Issues ranked and framed by business impact (refunds, churn, repeat purchase)

Clear owners and suggested actions so feedback turns into concrete changes

E-commerce · Use case

Order to happy customer automation

Orders flow from the webshop into a central ops hub that syncs with fulfilment and support tools; clean orders go straight to the 3PL, while exceptions land in a Slack queue with one-click fixes. An AI returns agent reads customer requests and order context, applies your return policies, creates labels and draft replies where it’s safe to do so, and escalates edge cases to humans with clear guardrails.

Impact :

Far fewer manual touches per order, especially around exceptions and returns

Fewer “Where is my order?” tickets and repetitive returns emails

Faster, more reliable fulfilment against your shipping SLAs

Returns handled consistently by policy, with a clear trail in your ops hub

E-commerce · Use case

Order to happy customer automation

Impact :

Far fewer manual touches per order, especially around exceptions and returns

Fewer “Where is my order?” tickets and repetitive returns emails

Faster, more reliable fulfilment against your shipping SLAs

Returns handled consistently by policy, with a clear trail in your ops hub

B2B SaaS · Use case

AI revenue intelligence cockpit

Data from your CRM, email, product usage, and billing flows into a single revenue workspace. AI scores and prioritises leads, suggests discovery questions and next best actions, highlights risky deals and high-potential accounts, and learns from wins and losses so your pipeline gets more accurate over time.

Impact :

Less time spent on manual research and qualification tasks

Consistent, transparent lead and account scoring across the team

Smarter conversations driven by AI-suggested questions and talking points

Systematic win/loss learning that feeds back into targeting and messaging

B2B SaaS · Use case

AI revenue intelligence cockpit

Impact :

Less time spent on manual research and qualification tasks

Consistent, transparent lead and account scoring across the team

Smarter conversations driven by AI-suggested questions and talking points

Systematic win/loss learning that feeds back into targeting and messaging

Benefits

The key benefits for your team and business

Lean automation that cuts busywork, improves performance, and gives you cleaner data without adding more tools to babysit.

Less manual work

Reduce copy-paste, status chasing, and repetitive admin in your core workflows so your team can focus on higher-impact work and consistent, high-quality delivery.

Less manual work

Reduce copy-paste, status chasing, and repetitive admin in your core workflows so your team can focus on higher-impact work and consistent, high-quality delivery.

Less manual work

Reduce copy-paste, status chasing, and repetitive admin in your core workflows so your team can focus on higher-impact work and consistent, high-quality delivery.

Better Customer Experience

Deliver faster, more consistent responses across sales, support, and fulfilment, with fewer dropped balls and “who owns this?” moments.

Better Customer Experience

Deliver faster, more consistent responses across sales, support, and fulfilment, with fewer dropped balls and “who owns this?” moments.

Better Customer Experience

Deliver faster, more consistent responses across sales, support, and fulfilment, with fewer dropped balls and “who owns this?” moments.

Faster cycle times

Leads, orders, and tickets move from step to step automatically, so deals close sooner and customers get what they need without waiting on inboxes.

Faster cycle times

Leads, orders, and tickets move from step to step automatically, so deals close sooner and customers get what they need without waiting on inboxes.

Faster cycle times

Leads, orders, and tickets move from step to step automatically, so deals close sooner and customers get what they need without waiting on inboxes.

Lower cost per transaction

Automations handle the repetitive work, reducing operational cost per lead, order, or ticket so your team can handle more volume without burning out.

Lower cost per transaction

Automations handle the repetitive work, reducing operational cost per lead, order, or ticket so your team can handle more volume without burning out.

Lower cost per transaction

Automations handle the repetitive work, reducing operational cost per lead, order, or ticket so your team can handle more volume without burning out.

Data you can trust

Your key tools stay in sync, noisy data is cleaned at the source, and you get a single view of what’s going on instead of reconciling dashboards.

Data you can trust

Your key tools stay in sync, noisy data is cleaned at the source, and you get a single view of what’s going on instead of reconciling dashboards.

Data you can trust

Your key tools stay in sync, noisy data is cleaned at the source, and you get a single view of what’s going on instead of reconciling dashboards.

Ready to scale

As volume grows, your systems absorb more work without breaking, so you can scale revenue without scaling chaos at the same pace.

Ready to scale

As volume grows, your systems absorb more work without breaking, so you can scale revenue without scaling chaos at the same pace.

Ready to scale

As volume grows, your systems absorb more work without breaking, so you can scale revenue without scaling chaos at the same pace.

FAQs

Practical details before we work together

Some of the questions that usually come up before a first project are answered here. If something else is on your mind, we can cover it in the intro call or by email.

How do you price your work?

How long does a project take?

How do we start and what does the process look like?

What happens if something breaks after go-live?

What kinds of companies do you work with?

Which countries do you work with?

Do you only work remotely, or do you also do on-site workshops?

What language can we work in?

Do we need technical skills to work with you, and who owns the system afterwards?

How do you handle data privacy and security?

We already have internal IT or a freelancer. Can you still help?

How do you price your work?

How long does a project take?

How do we start and what does the process look like?

What happens if something breaks after go-live?

What kinds of companies do you work with?

Which countries do you work with?

Do you only work remotely, or do you also do on-site workshops?

What language can we work in?

Do we need technical skills to work with you, and who owns the system afterwards?

How do you handle data privacy and security?

We already have internal IT or a freelancer. Can you still help?

Ready to fix your most painful workflow?

Book a short, free intro call to discuss your current challenges. If automation is not a strong fit, I will be transparent and we simply stop there.

Book a short intro call

Prefer to write instead?

Send me a message

Book a short intro call