Alchymie services

Move from scattered AI use to business leverage.

Alchymie helps businesses choose the highest-value entry point, build practical AI systems, seed shared business memory, and explore what AI could change about the business itself.

Explore the Pathway
Where AI creates value

AI can enter through different parts of the business.

Sometimes the first move is customer-facing. Sometimes it is operational, decision-related, or about the deeper business model. The right entry point depends on where the strongest learning loop is.

These four domains are lenses, not steps. The offers below are different ways of working across them, depending on what the business is ready to learn or build.

Offer

What customers experience

Products, services, packages, client experience, and the customer-facing promise.

Operate

How value is delivered

Workflows, agents, automations, business memory, handoffs, and quality control.

Decide

How the business learns

Signals, feedback loops, decision support, governance, and better judgement.

Model

How value scales

Pricing, margins, distribution, defensibility, owner role, and how value scales.

Ways to work together

Start from the situation you are in.

This is the quick routing layer. Each card points to the deeper offer detail below; the offers are entry points, not a fixed ladder everyone has to climb.

Build capability

First, help people work with AI well.

These offers build shared language, confidence, habits, and working setup before the business tries to scale AI.

You need orientation

Public Workshops

A practical introduction to what AI can do beyond everyday chatbot use.

orientationfirst possibilities
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Your team needs capability

AI Fluency Foundations

Training that helps people use AI in actual business work, not just prompts.

shared standardsreal-work AI habits
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You need hands-on setup

AI QuickStart

A practical AI workbench for real files, memory, tools, and workflows.

business memoryone useful workflow
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Turn capability into business leverage

Then apply AI where it can change the business.

These offers turn capability into systems, sequencing, implementation, and model-level opportunities.

One process is ready

First AI Business System

Turn one asset or workflow into a working proof point.

visible valuenext opportunity map
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You need sequencing

AI Business Blueprint

Map the opportunities, model the ROI, and choose the order.

quick wins12-month roadmap
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The ROI case is clear

Implementation Sprint

Build a clear use case: AI receptionist, website chat, intake, follow-up, proposals, or internal support.

AI receptionistlead follow-upproposal support
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The business model question is alive

AI Business Model Lab

Explore where AI could turn expertise, delivery, or customer support into more scalable value.

productized expertiserecurring modelsAI workbenches
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Offer details

Different offers for different kinds of readiness.

This is the slower read: who each offer is for, what happens, what you leave with, and when another pathway is a better fit.

Public Workshops

Public Workshops

For opening the door without overcommitting.

Short practical sessions that help business leaders see what AI can do beyond one-off chatbot use. These are useful when the first job is orientation, shared language, and a concrete sense of what might be worth exploring.

Best for: A group, room, network, or leadership team needs a clear introduction to practical AI business use.
Not the best fit when: You already know the use case and want something scoped, built, or diagnosed in detail.
  • AI beyond chat
  • examples of real business workflows
  • prompting, context, and verification basics
  • first workflow opportunity prompts
  • next-step routing
People leave with a more practical mental model and a clearer sense of whether they need training, setup, a first system, or a roadmap.
AI Fluency Foundations

AI Fluency Foundations

For teams and cohorts still using AI superficially.

This is not generic AI literacy. It is practical, real-work training that helps people use AI with better context, stronger verification, shared habits, and a clearer sense of what should become a system.

Best for: A business, team, or cohort needs a practical baseline before investing in deeper AI systems.
Not the best fit when: Only one person needs a personalised workbench, or the business already has a clear build ready to go.
  • structured prompting and verification
  • project and file-based AI work
  • business-context exercises
  • agentic workflow examples
  • first system opportunity mapping
Your people stop treating AI as a novelty and start seeing where it can support real work.
AI QuickStart

AI QuickStart

For an owner, operator, or small team that needs an AI workbench.

A focused setup session for one operator or a small working group. The point is not a full assessment or strategy. The point is getting actual tools, files, memory, and a first useful workflow in place.

Best for: Someone needs hands-on help moving beyond isolated chats into a working operating layer for real business work.
Not the best fit when: A whole team needs common standards, or the business needs a broader diagnostic before setup.
  • local AI tool orientation
  • Markdown or Obsidian memory setup
  • starter instructions
  • one useful workflow
  • next-step recommendation
You leave with a practical AI workbench and a clearer sense of what to apply it to next.
First AI Business System

First AI Business System

For turning capability into proof.

Once the pattern is visible, we apply it to one meaningful business asset: an assessment, proposal process, intake flow, content engine, follow-up workflow, SOP, or client onboarding sequence.

Best for: You have one asset worth improving and want a concrete proof point before a broader roadmap.
Not the best fit when: There are many competing opportunities and the business needs sequencing before choosing what to systemise.
  • AI workbench and business memory
  • business-specific instruction pack
  • one upgraded asset
  • prototype, workflow, or lightweight tool
  • next opportunity map
One part of the business becomes more useful, and the next investment becomes easier to judge.
AI Business Blueprint

AI Business Blueprint

For broader diagnosis and sequencing.

A structured diagnostic for businesses with several possible AI opportunities, unclear sequencing, or enough complexity that guessing would be expensive. The Blueprint maps across the offer, operate, decide, and model layers.

Best for: You need the business case, constraints, quick wins, implementation options, and roadmap before investing heavily.
Not the best fit when: There is one obvious high-value build and the business is ready to implement rather than diagnose.
  • business pre-assessment
  • opportunity and constraint mapping
  • ROI and business-case modelling
  • implementation options
  • 12-month roadmap
You know what to build first, what to leave alone, and how the next investments should compound.
Implementation Sprint

Implementation Sprint

For a clear practical build with visible ROI.

A contained build for a clear opportunity. This is for the moment where the business can name a useful thing worth implementing: an AI receptionist, website chat assistant, enquiry triage, intake flow, booking workflow, follow-up system, proposal helper, assessment assistant, or internal knowledge tool.

Best for: The use case is selected, there is enough value or volume to justify a build, and the business can name the owner, success measure, and review points.
Not the best fit when: The use case is vague, the data/tools are unclear, or several opportunities need prioritising first.
  • use-case design and scope
  • custom build or AI-enabled workflow
  • tool integration where appropriate
  • testing and handover
  • improvement plan

Common high-ROI sprint examples:

  • AI receptionist or website chat assistant: answer common questions, capture enquiries, qualify intent, book appointments, and hand off to a person when needed.
  • Lead response and follow-up: draft replies, trigger reminders, keep prospects warm, and reduce lost opportunities after the first enquiry.
  • Intake, booking, or quoting workflow: turn messy inbound information into structured next steps, estimates, or booking-ready context.
  • Proposal or assessment assistant: create stronger proposals, recommendations, reports, or client-facing assessments from repeatable inputs.
  • Internal knowledge assistant: make policies, SOPs, past work, templates, and project context easier for the team to find and use.
A specific business capability gets implemented without turning the first win into a whole transformation program.
AI Business Model Lab

AI Business Model Lab

For founders asking what the business could become.

A selective strategic lab for businesses where AI might change more than internal efficiency. We look at whether expertise, delivery, customer support, methodology, or decision-making could become a more scalable product, workbench, subscription, licensing model, retainer, or outcome-based service.

Best for: IP-rich expert businesses, agencies, educators, consultants, specialist service firms, and founder-led companies where the owner's knowledge or delivery model is a bottleneck.
Not the best fit when: The business first needs basic fluency, immediate operational relief, or one obvious build before exploring model-level change.
  • four-layer business model map
  • leverage opportunity map
  • AI-enabled offer and model hypotheses
  • pricing, packaging, or recurring revenue options
  • first experiment recommendation
You leave with a sharper view of whether AI can change what you sell, how you deliver it, and how the business captures value.
The larger story

The first step should reveal the next one.

A workshop should reveal whether the next move is team training, personal setup, one first system, a contained build, a broader Blueprint, or a business model lab.

The larger Alchymie pattern stays the same: build capability, turn capability into useful systems, then let those systems compound into stronger operations, better decisions, stronger offers, and a more leveraged business model.

Start where the business actually is.

Bring the current level of AI use, the team questions, or the first workflow you think might matter. We will work out whether the next step is fluency, setup, a first system, a sprint, a Blueprint, or a model-level lab.

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