Business AI Architecture · AI for BPO · Blank Canvas Thinking

What if you could help other businesses work better?

Not by selling more software.

Not by convincing everyone they need AI.

But by understanding how businesses actually work, finding what’s getting in the way, and engineering something better.

I’ve spent more than 20 years doing versions of this with enterprise systems, business processes, and technology. And lately, I’ve been wondering…

What if more people could do the same thing?

Start here Read the ideas

Not necessarily as employees of big consulting firms.

But as independent architects, consultants, developers, and entrepreneurs building solutions for businesses that genuinely need them.

So I started putting together the ideas, methods, and tools I’ve learned and developed along the way. Some are things I’ve built. Some are things I’m still experimenting with. And some are lessons I wish someone had shared with me 20 years ago. 😂

Anyway, welcome. Maybe you’ll find something here worth building a business around.

Featured exploration · AI for BPO

What if a BPO could grow without adding people at the same rate?

A BPO provider wins another client. Great news. Now come more transactions, exceptions, service commitments, training, and operational complexity.

What if we redesigned how work gets done, so people, automation, and AI could work together instead of just adding another tool?

Not AI for the sake of AI. Better execution and a better experience for everyone involved.

The problem

More clients usually means more people.

Growing without adding people at the same rate Illustrative chart. As client work grows, people usually grow at almost the same rate. The design goal with an execution layer is for people to grow more slowly, with workflows, automation and AI absorbing the difference while people stay in the lead. more clients, more work → effort work volumepeople, the usual waypeople, with an execution layer (goal)absorbed by workflows, automation, AIwith people in the lead Illustrative design goal, not measured data.

Independent product concept

ClarisTXM

Total Execution & Experience Management

Better Service Delivery. Lower Cost to Serve. More Room to Grow.

Helping BPO companies deliver more services, with better quality, at a lower cost.

ClarisTXM is designed to help BPO providers manage and improve the services they deliver to their clients. It brings together their people, daily work, service commitments, and performance in one place, using AI to reduce manual effort, improve decisions, and help teams handle more work without adding people at the same rate.

Three promises to BPO providers

  1. Deliver better servicesMeet client commitments, improve quality, and manage work consistently across accounts.
  2. Improve profitabilityReduce manual effort and cost per transaction while protecting service quality.
  3. Grow without growing costs at the same rateTake on more clients and higher work volumes using better processes, automation, and AI.

Explore the concept

Conceptual exploration. Features and outcomes are design goals, not claims of a deployed product.

ClarisTXM as an operating layer Concept diagram. Clients, services and SLAs sit on top. In the middle, the ClarisTXM execution and experience layer orchestrates people, workflows, automation and AI; governs approvals, exceptions and evidence; and keeps service quality, performance and cost-to-serve visible, with people setting direction and owning outcomes. Systems of record such as CRM, ERP, ticketing and data sit underneath. Clients · services · SLAs · experience ClarisTXM · execution & experience layer Human in the lead: people direct, approve, own outcomes Orchestrate· People· Workflows· Automation· AI Govern· Approvals· Exceptions· Evidence· Accountability Experience· Service quality· Performance· Cost-to-serve· Capacity Systems of record: CRM · ERP · ticketing · data

How I work

Make things better, cheaper, faster.

Most of what I share follows three principles:

  1. Engineer.

    Understand the problem. Question assumptions. Design the right solution.

  2. Execute.

    Build it. Test it. Make it work in the real world.

  3. Excel.

    Measure what happened. Improve it. Make it repeatable.

That’s the foundation of my work on Transformation Execution Management (TXM), and it maps straight onto the AI-DLC: engineer the canvas and the architecture, execute the build and the approvals, and excel with the customer. You don’t need to memorize another framework. But you might find the thinking useful.

See how it works

Architecture in practice

From operating model to measurable service.

Business AI Architecture defines how work should happen across people, processes, applications, data, and AI.

Execution management connects the design to daily delivery: assigning work, handling exceptions, keeping humans accountable, and measuring the experience.

  1. 01

    Discover

    Map services, work volumes, SLAs, experience, and friction.

  2. 02

    Design

    Define the target operating model, controls, and outcomes.

  3. 03

    Orchestrate

    Coordinate people, workflows, automation, and AI.

  4. 04

    Govern

    Keep approvals, exceptions, evidence, and accountability visible.

  5. 05

    Improve

    Measure productivity, service quality, cost-to-serve, and experience.

Explore the methods

From an idea to something you can use

Methods, templates, patterns, and tools.

Over time, I’ve developed methods, templates, architecture patterns, and software tools to make this work more repeatable. I’m organizing them here for people who want to learn, experiment, and eventually use them in their own professional practice.

TXM Body of Knowledge, book cover

The Books

Longer-form thinking on transformation, engineering, and AI.

Explore

THE METHODS Engineer.Execute.Excel. TXM

The Methods

A repeatable way to go from discovery to architecture to results.

Explore

THE TOOLS DiscoveryCanvas + toolkits

The Tools

Templates, patterns, and software to cut the repetitive work.

Explore

THE WORK ThingsI’mexploring experiments

The Work

Experiments and demonstrations, clearly labelled for what they are.

Explore

One last thing.

You don’t have to become an AI expert overnight.

You don’t have to quit your job and start an agency tomorrow.

And you definitely don’t need to build an AI agent for every business problem.

Start by learning to see problems differently. Then build something useful. The rest can follow.

— JP