Sato SystemsSato Systems

Sato Systems

Structured Systems Intelligence

Your systems are holding you back.You just can't see where.

Sato Systems helps growing teams choose the right operating layer, implement it, and then enhance it with AI and automation so the work notices changes, takes action, and stays easier to run.

Structured Systems Intelligence

AI and Automation

Use AI and automation to notice changes, act, and keep people aligned.

Add automation inside the existing stack so the workflow can trigger the next action automatically.

NotificationsCalendar visibility
Salesforce

Systems and Forecasting

Evaluate, choose, and implement the operating layer the business can actually trust.

Choose the right CRM, PMO, and communication stack before the workflow gets more expensive.

Comms stack
monday.com
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30 minutes. No pitch. Just clarity.

100+ systems built. Here is what I keep seeing.

Most growing businesses do not have one giant problem. They have the same drag showing up in new places.

I've seen what breaks first when a company scales without a system people can actually follow. The website, the inbox, and now the AI conversation usually expose the same thing: too much of the work still lives in memory, scattered handoffs, and whoever happens to know the answer today.

The Pattern

Customers notice the pattern first. They feel the same friction again and again: the website feels dated, the reply path is unclear, and the business feels a little harder to trust than the real work deserves.

They do what customers always do. They tell the frontline worker who is easiest to reach, long before leadership treats it like a system problem.

The Stall

The stall starts when approvals slow down, ownership stays fuzzy, and the team keeps patching around the issue instead of fixing the system. Employees start asking for the same things every day: approval, ownership, onboarding answers, lead replies, and the right next step. The drag is obvious, but the work is still not routed clearly enough to teach, repeat, or automate.

The drag is visible, the issue is real, and yet decisions still depend on one person saying yes, one person remembering the answer, or one person pushing the work forward.

The Cost

QuickBooks

Overdue

$304K overdue and still not collected

Cash flow squeezed

CRM

Untouched

$5M+ a year lost to poor data

Revenue left behind

Spreadsheet

Behind Goal

$12.9M a year can disappear into bad data

Future revenue missed

The cost shows up when leadership realizes the business has been winging too much of the work. By the time the problem reaches that level, trust, time, and revenue have already been burned through avoidable friction.

The goal is to see this chain early and get ahead of it before leadership is paying for improvising instead of operating.

Book a Free Strategy Call →

How I Help

Build the operating layer first. Then let AI and automation make it move.

Sato Systems publicly sells two work types: AI and Automation, and Systems and Forecasting. Systems work helps you choose and implement the right operating layer. AI and Automation enhances that layer so the workflow can notice changes, move data, trigger actions, and keep teams aligned.

Website refresh and lead-capture cleanup still happen, but as supporting scope inside the two main work types instead of as a competing primary lane.

How systems and forecasting creates relief

This board shows the systems-and-forecasting move more clearly: the messy work gets organized into sales and pipeline, delivery and onboarding, and reporting and visibility first. Then AI and automation helps that structure notice changes, trigger the next step, and keep teams aligned with less manual work.

Situation

The work lives in too many places, follow-up happens by memory, and people keep acting like the missing system. That is what makes forecasting feel shaky and day-to-day operations feel stressful.

Salesforce
monday.com
Gmail
Notion
Zapier
ChatGPT
Claude
Gemini
Spreadsheets / Docs
Task

Figure out what the stack should actually do, who owns each step, and where the work belongs so the business stops depending on one person remembering everything.

→
Action

Organize the work into sales and pipeline, delivery and onboarding, and reporting and visibility. Then layer AI on top so the system notices changes, routes the next step, and keeps everyone working from the same truth.

Result

The business becomes easier to trust, easier to train, and easier to run because the system finally shows what changed, what needs attention, and who owns the next move.

Sales and Pipeline

CRM + forecasting

Pipeline ownership, cleaner forecasting, and customer records the business can actually trust.

Forecast you can trust

Delivery and Onboarding

PMO / work management

Cleaner handoffs, smoother onboarding, and clearer ownership once the work leaves the sales conversation.

New customers get moving faster

Reporting and Visibility

Comms stack + alerts

Shared reporting, team updates, and alerts so the right people see the right information without manual chasing.

Leaders see what changed faster

AI action layer

Once the operating layer is clean, AI notices changes, routes the next step, and sends the right update without turning into a fourth lane your team has to manage.

DetectRouteNotifyBriefRemind

98% admin reduction

More selling time

Manual updates, reporting cleanup, and repeated follow-up stop eating the day once the operating layer and automation are finally connected.

~$100K saved annually

Lower operating drag

When repetitive handoffs, reporting chores, and cross-team busywork are automated, the business keeps more time and money inside the work that actually matters.

3 months -> 1 month ramp

Faster onboarding

Structured onboarding, role clarity, and repeatable workflows help new people become productive much faster than tribal-knowledge handoffs ever could.

This is the systems-and-forecasting move: build the operating rhythm first, then let AI accelerate it without creating more chaos.

Swipe or tap a card to see the next step

AI and automation

AI and Automation

What changes

The business gets practical AI and automation that can watch the workflow, move data, trigger actions, and keep teams aligned without rebuilding the same support by hand.

  • AI implementation and training inside the real workflow
  • Trigger-based automations across CRM, email, calendar, and project tools

Starting point

Custom scoped

Ongoing support Optional

Operating relief

Systems and Forecasting

What changes

The business becomes easier to train, manage, and forecast because CRM, communication, onboarding, reporting, and internal workflows stop living in scattered workarounds.

  • CRM, PMO, and communication system evaluation + implementation
  • Cleaner ownership, onboarding, and operating rules

Starting point

Custom scoped

depends on system choice, architecture depth, and rollout scope
AI and automationAI and Automation

Implement AI and automation that notices, acts, and keeps teams aligned.

This is the right first move when the business already has demand or internal complexity, but the follow-through still depends on inboxes, copied notes, scattered prompts, and manual updates between teams. The default path is usually implementing AI and automation inside ChatGPT, Claude, and the tools your team already uses, then training the team so the workflows actually stick. That can include trigger-based automations, structured handoff briefs, reminders, notifications, summaries, and coordinated updates across CRM, calendar, email, and project tools. One common implementation is an AI Command Center when the workflow needs one managed home for prompts, automations, training material, and repeated support.

AI implementation and training inside the real workflowTrigger-based automations across CRM, email, calendar, and project toolsStructured handoff briefs, reminders, and follow-through support where appropriate

This will feel familiar if

The AI handoff is still broken

Someone says `just use ChatGPT`, then the next person asks how to use ChatGPT or Claude for the actual work in front of them.

The same answers get rebuilt

Training, replies, research, and internal help still depend on whoever remembers the right prompt, doc, or next step.

The tools are not the real issue

The business usually already has enough software. What is missing is a practical automation layer that can watch the system, move the right information, and keep everyone informed with less human error.

What this can look like

Cross-system handoff

A closed-won update can trigger the whole next step

When a seller closes a deal and Salesforce updates, the automation can pull the right fields, organize the data, update the record, and generate a structured handoff brief for the customer, accounting, and operations teams.

What changes

Everyone sees the same organized next-step brief without relying on copied notes or manual forwarding.

Salesforce triggerAI field extractionStructured handoff brief

Manager visibility

The system can turn next steps into reminders and calendar visibility

If an account executive updates the next step and date in the CRM, the automation can create the right reminder, create the calendar event, and help leadership stay informed without living inside Salesforce all day.

What changes

Sellers get cleaner follow-through and managers get faster visibility with less chasing.

CRM updatesCalendar eventsReminders + alerts

From here to there

A simple view of where the business usually is now, what gets set up, and what starts working next.

  1. 1

    Signals are easy to miss

    Updates, next steps, approvals, and handoff details live in different tools and different people's heads.

  2. 2

    People improvise the handoff

    The team keeps copying notes, forwarding emails, or asking who owns the next move.

  3. 3

    Add one practical automation layer

    The first useful AI workflows get organized inside the existing stack so changes can trigger the next action automatically.

  4. 4

    Launch with training

    The team gets grounded guidance, repeatable workflows, and AI support they can actually use in real work.

  5. 5

    Tune what the business learns

    The automation layer gets refined as new edge cases, follow-up needs, and training requests appear.

How implementation works

A simple delivery path: diagnose the real gap, get the first useful version live, then stay close enough for training, cleanup, and next requests.

Implementation stages

1. Evaluate the trigger and the handoff

Free call + optional strategy session

Map the event, the systems involved, the people affected, and the exact moment where information starts getting dropped or delayed.

2. Design the automation path

Scope phase

Define what should trigger, which fields matter, how the logic branches, who gets notified, and what the finished output should look like.

3. Build the automation layer

Implementation window

Implement the workflow across CRM, email, calendar, project, and communication tools, then add AI where extraction, formatting, routing, or summarizing makes the workflow better.

4. Test the real edge cases

Before launch

Run the automation against real data paths so field mapping, notifications, formatting, and fallback behavior work before the team depends on it.

5. Train + launch

Launch week

Show the team how the automation works, where the system still needs human judgment, and how to troubleshoot the main scenarios.

6. Support and improve

Optional ongoing support

Stay close for tuning, retraining, and new workflow requests when the business wants a managed relationship instead of a one-time handoff.

Support through every step

Hands-on setup

Keith maps the real trigger, the right fields, the logic, and the first useful version with you instead of handing over a vague AI strategy doc.

Training that sticks

Launch includes practical training, grounded docs, and support flows tied to the real work the team is doing so the automation actually gets adopted.

Structured outputs, not plain noise

When the workflow needs it, the output can become a structured handoff brief with polished formatting, organized data, and role-specific context instead of a plain-text alert.

Why this works

Real operating proof, client examples, and outside research that all point in the same direction.

Client proof

Client implementation proof

A multi-state secure transport operator used OpenAI across Google Calendar, Salesforce, and monday.com to cut admin work, improve reporting, support onboarding, and keep downstream teams in sync faster.

Internal proof

Internal operating proof

Keith's own AI command center now runs research, planning, support, and workflow help from one clearer setup instead of scattered prompt work.

Research

Workplace friction research

The broader pattern still holds: most teams are already frustrated by disconnected workplace tools before AI complexity gets layered on top.

View source

Best when

Best when the team is already using ChatGPT or Claude, but the business still depends on copied updates, scattered prompts, weak reminders, and too many manual handoffs between systems and people.

Starting point

Custom scoped

depends on trigger complexity, systems touched, and testing depth

Ongoing support

Optional

available when the team wants training, tuning, and troubleshooting help

Use AI and automation to watch the workflow, take action, and keep people aligned.

Working with Keith

Direct point of contact

Keith stays your direct point of contact from the first call through rollout, support planning, and next-step decisions.

Direct support from Keith

You work directly with Keith for rollout questions, training follow-ups, and next-step decisions. You are not handed off to a support queue.

Access organization + setup basics

Account access, API keys, permissions, and setup notes are organized carefully so the system is easier to manage and easier to hand off cleanly.

Start here

The business gets practical AI and automation that can watch the workflow, move data, trigger actions, and keep teams aligned without rebuilding the same support by hand.

AI and Automation work is custom scoped by workflow complexity. Some automations stay narrow and fast. Others touch multiple systems, stakeholders, and testing steps before launch. The goal is one practical automation layer the team can actually run.

Where this can go next

This becomes the practical automation layer the business grows inside. If the workflow depends on deeper CRM structure, ownership, reporting trust, or operating-system design, the next move is Systems and Forecasting.

Free Strategy CallStarting point depends on complexitySupport plan if needed
Ask About AI and Automation

Free 30-minute strategy call · optional $500 Strategy Session · custom-scoped AI and Automation · custom-scoped Systems and Forecasting

Who This Is For

If this sounds like you, we should talk.

Owners, growth leads, ops people, and finance-minded buyers show up again and again. Each one is trying to solve a different version of the same small-business growth problem.

Swipe or tap a perspective

Owner / FounderBest fit: Systems and Forecasting

Their situation

The website needs love. New leads come in from different places. You are still the backup plan for what to say, where to look, and what happens next.

What changes: You get a business that looks more buttoned up online and runs with less dependence on your memory.

Relevant example

Secure logistics — leadership visibility

Legacy spreadsheets stopped running the business

Rebuilding the CRM and sales operations layer replaced spreadsheet-heavy workflows with a system leadership could actually trust.

What was broken

Core pipeline and reporting work lived in legacy spreadsheets

  • $4.2M pipeline built on the rebuilt system
  • ~$100K saved annually through automation

Examples come from Keith's own operating roles and real engagements. Some client work stays anonymized. Metrics reflect outcomes observed during or immediately after the implementation period.

Who's Building This

Built inside growing companies where handoffs, reporting, and adoption started to break.

Built inside growing teams, this work is designed for founder-led companies that have outgrown spreadsheets, patchwork handoffs, and unclear reporting. The goal is simple: clearer visibility, cleaner handoffs, and systems people will actually use.

Career timeline

Across founders, revenue leaders, and ops leaders, the same pattern kept showing up: growth had started outrunning the system.

  1. Justworks

    Made switching feel clear enough to buy.

    $1M in new revenue

    Built an outbound system that made a complex payroll and benefits sale easier to run, easier to repeat, and easier to trust.

  2. monday.com

    Made workflow change feel worth the rollout.

    $1.4M sold on a $1.2M target

    Sold across North America, with the strongest fit in growing teams that needed cleaner handoffs, clearer reporting, and a system people would actually adopt.

  3. Abacus.AI

    Made AI value concrete for enterprise buyers.

    $125K deals closed

    Turned complex AI into a practical business case for large teams by tying technical use cases to real operating pain.

  4. ONES.com

    Built a U.S. sales motion an international team could actually run.

    97% qualification rate

    Translated the American sales process into a teachable system for a non-English-first team and built the playbook from scratch.

  5. Multi-state secure logistics

    Rebuilt legacy operations into a system leadership could trust.

    $4.2M pipeline built

    Rebuilt CRM, reporting, and handoffs across sales, ops, and support so leadership finally had live visibility into the business.

Keith Andrade

Keith Andrade

Websites, workflows, and practical AI implementation

I build the front door and the systems behind it. That is why the work spans websites, lead capture, AI workflows, CRM, and rollout.

Revenue proof

$10M+ pipeline generated. $5M+ in revenue closed across five industries.

Systems proof

Turned messy workflows into systems teams could actually run. Owners get cleaner handoffs, better visibility, and less work trapped in one person's head.

Stack fit

Works inside the tools teams already use. Salesforce, monday.com, HubSpot, Zendesk, Claude, ChatGPT, and Zapier.

Morning Byte

Built Morning Byte. It proved the same rule I use in client work: useful systems beat flashy ones when people actually keep using them.

Featured inMemberfulUncharted Podcast

Who I helped inside these companies

Owners, revenue leaders, and ops teams when growth had outpaced handoffs, visibility, and the systems people actually had to use.

Founder-led teams. When growth started outrunning visibility, handoffs, and whatever still lived in the owner's head.

Revenue leaders. When lead capture, qualification, and follow-up needed a sales system the team could actually repeat.

Ops leaders. When CRM, reporting, and delivery updates had drifted into spreadsheets, inboxes, and too many tools.

Built systems inside

Justworks
monday.com
Abacus.AI
ONES.com
Multi-state secure logistics

Education

Zicklin School of Business, Baruch College

What owners hire me to fix

Leads stop leaking. Clean up the website, lead capture, and follow-up so interested buyers do not disappear between first touch and the next step.

The team stops guessing. Rebuild CRM, reporting, and team handoffs so leadership can see what is moving without chasing updates.

AI stays practical. Use AI where it saves time and improves visibility, not where it adds another system to manage.

Case studies + operating proof

What changes when the right part of the business finally works.

Most businesses need one of two major moves first: a stronger operating layer or a stronger automation layer. Front-door support still shows up sometimes, but only as supporting scope around the system underneath it. These cards show where the work started and why it actually stuck after launch.

The proof below shows the same operating logic applied across the two main work types: AI and Automation when the workflow needs action, and Systems and Forecasting when the business needs the operating layer rebuilt or trusted again.

AI and AutomationFounder-built AI operating engine

niche research and workflow support

1,300+ premium insights a year from one AI operating engine.

This started as a real internal need: too many tools, too many repeated asks, and too much AI work living in prompts instead of one managed system. The result became a command center that now runs research, support, planning, and team workflows in one place, mostly through the tools the team was already using.

Internal operating proof

1,300+ premium insights a yearMulti-team AI workflowsClient-stack-first logic

Before

AI help, reporting, and repeated work were scattered across prompts, tools, and manual follow-up instead of living in one system the team could actually run.

What changed

One command center started handling research, support, planning, and repeated workflow help without the work depending on memory or tool switching.

Why it stuck

The system stayed usable because the workflows, prompts, and automations were actively managed, documented, and improved instead of treated like a one-time experiment.

Systems and ForecastingSecure Logistics

30 states, 22 branches

$4.2M pipeline built once leadership could finally trust the system.

Leadership had been asking people for numbers instead of seeing the business live. The rebuild turned spreadsheet guesswork into one operating system sales, ops, and leadership could actually run.

Proof

98% admin reductionLive reporting leadership trustedWorking guides left behind

Before

Leadership had to ask for every number because pipeline, forecasting, and follow-up logic were still trapped in spreadsheets.

What changed

Leadership could see the pipeline live and the sales team got back to selling instead of doing admin cleanup.

Why it stuck

Training guides, automated tasks, and shared dashboards made the new workflow usable across sales, ops, and leadership.

Systems and ForecastingE-commerce brand

pet wellness

One rollout turned scattered order work into a workflow the team actually used.

This is rollout proof more than ROI proof. The team had product and order work spread across disconnected tools, then moved into one clearer workspace with hands-on support so adoption would stick.

Rollout snapshot

Hands-on rollout supportTeams adopted the workflow

Before

Orders and product updates were scattered across tools, so the team kept piecing together status by hand.

What changed

The team had one place to manage order and product work instead of chasing updates across disconnected systems.

Why it stuck

Hands-on rollout support and training helped the team use the new workspace instead of working around it.

Systems and ForecastingDev tools SaaS

U.S. market entry

A repeatable lead path hit a 97% qualification rate from a standing start.

There was no shared CRM, no follow-up rhythm, and no onboarding path for new reps. The lead flow had to be built from zero fast enough for the team to actually use it.

Proof

97% qualification rateRamp time cut from 3 months to 1Shared playbook for new reps

Before

Leads depended on individual memory because there was no shared CRM, qualification path, or follow-up rhythm.

What changed

The team had one repeatable lead path instead of rebuilding follow-up and qualification from scratch every time.

Why it stuck

New reps could ramp in one month because the CRM, playbook, and onboarding path were built to be reused.

Client work plus internal operating proof, anonymized where needed.

Why It Sticks

You should end up with something your team can actually run.

We build it. We connect it. We train your team on it.

Keith stays close from the first decision through rollout. The goal is calmer handoffs, less guesswork, and less dependence on one person keeping the whole thing alive.

What changes after go-live

The work is not done when the tool goes live. The real win is that your team knows what to do next and can keep the work moving without constant rescue.

Fewer handoff surprises

Usual outcome

Advice, build work, and training happen in separate lanes, so ownership gets fuzzy after go-live.

What changes here

Keith stays close from the decision through rollout, so the next step does not get lost.

Less dependence on one person

Usual outcome

The new setup makes sense to the builder or one power user, and everyone else keeps guessing.

What changes here

Training and support are part of the work, so the team can use the setup with confidence.

A better fit on day one

Usual outcome

A smart-sounding package creates extra steps and more friction for the people doing the work.

What changes here

The systems, automation, and follow-through are shaped around your real handoffs and day-to-day rhythm.

What people say

Less manual work
“He doesn't just manage pipelines, he transforms them.”

Built scalable, tech-driven workflows that slashed manual administrative tasks and enhanced team efficiency.

Darius Rostami

Payments & secure logistics

Former direct report in secure logistics

Training + support
“He went above and beyond to onboard and train me, and nurtured my growth the entire time.”

Patricia Pham

Business Development Representative at Valant

Former direct report

Clear translator
“Keith has a unique ability to bridge the gap between technology and sales, two worlds that often speak different languages.”

Bryce Perram

Logistics & supply chain professional

Former colleague

Safer decisions
“He was an exceptional resource in our decision making process and made us feel very comfortable with our decision to move forward.”

Nichole Frazier

Senior Front End Dev at Mythic Digital

Worked with Keith during software selection

Public proof of how Keith works

These public LinkedIn recommendations are not case studies. They do show the same pattern from different people: Keith makes change easier to trust, improves workflows, and helps people use what gets built.

View public recommendations

The Approach

How Sato Systems works.

Think system partner, not black-box builder. We evaluate the real gap, choose the right foundation, model the maintenance burden, implement the system, add AI and automation where it helps, train the team, and stay close enough for the rollout to stick.

We design the operating layer together.Evaluate, build, automate, train, support

  1. Find the real gap

    1

    Step 1

    Evaluate

    Audit what is breaking, what systems already exist, and where ownership, reporting, or follow-through starts falling apart.

    You leave with

    A grounded read on what is actually breaking first.

    See the board notes

    This can start in the free strategy call or become a deeper strategy session when the team needs a real audit before choosing a build path.

  2. Choose the right stack

    2

    Step 2

    Select

    Choose the right CRM, PMO, communication stack, reporting layer, or automation starting point instead of building around the wrong foundation.

    You leave with

    A clearer system decision before expensive build work starts.

    See the board notes

    System choice is part of the offer. Sato Systems can compare options, recommend the right stack, and explain the tradeoffs clearly before implementation starts.

  3. Scope the reality

    3

    Step 3

    Model

    Make the implementation path and maintenance burden visible before the work gets approved.

    You leave with

    A visible implementation and maintenance path.

    See the board notes

    That includes scoping the build, estimating what it will take to maintain, and deciding what the business should own after launch versus what support should stay close.

  4. Build the foundation

    4

    Step 4

    Implement

    Build the system foundation or automation layer that solves the clearest bottleneck first.

    You leave with

    A cleaner operating layer the team can actually run.

    See the board notes

    Systems work can include CRM, PMO, reporting, and communication setup. AI and Automation work can include triggers, routing, summaries, structured handoff briefs, reminders, and multi-system workflows.

  5. Add the action layer

    5

    Step 5

    Automate

    Use AI and automation to monitor system changes, move data, trigger actions, and keep teams informed.

    You leave with

    Triggers, routing, briefs, reminders, and follow-through.

    See the board notes

    This is where the workflow starts noticing changes in the system and acting on them instead of depending on someone to manually move the information every time.

  6. Teach the workflow

    6

    Step 6

    Train

    Teach the team how to use the new system and automation layer in the real situations they face every week.

    You leave with

    Role-based guidance tied to the real work people do.

    See the board notes

    Training is not an afterthought. It is part of why the setup actually gets adopted across leadership, managers, and frontline users.

  7. Keep it useful

    7

    Step 7

    Support

    Stay close for troubleshooting, tuning, and next-step improvements when the business wants ongoing help.

    You leave with

    Bounded support for tuning, troubleshooting, and next requests.

    See the board notes

    The goal is bounded support that keeps the setup useful and teachable, not a vague promise that every future request is automatically included.

Collaboration is part of the build.

The reason most implementations fail is not the technology. It is that nobody stays to make sure the team is actually ready. I do.

Book a Free Strategy Call →

Ways to Start

Start with the work type that matches the real constraint.

Every engagement starts with a free strategy call. If the team needs deeper evaluation before build work, the Strategy Session is $500. From there, the work usually becomes either AI and Automation or Systems and Forecasting. Website refresh and lead-capture cleanup can still be scoped, but only as supporting work when the front door is getting in the way of the real system or automation problem.

Free Strategy Call

Not sure where to start?

Book a free 30-minute strategy call.

We'll look at what feels broken, whether the smartest next step is AI and Automation or Systems and Forecasting, which system choices or maintenance costs need to be understood first, and whether any lighter website support should simply be scoped around the real work instead of becoming the main project.

Free 30-minute strategy call · optional $500 Strategy Session · custom-scoped AI and Automation · custom-scoped Systems and Forecasting

Book the Free Strategy Call

Swipe through the ways to start

Automation layer

AI and Automation

Primary outcome

Use AI and automation to watch the workflow, take action, and keep people aligned.

The team stops rebuilding support, prompts, and follow-through in scattered tools and starts running the work through one clearer automation layer with cleaner notifications, reminders, and structured outputs.

Usually includes

  • Trigger-based workflows across CRM, email, calendar, and project tools
  • Structured handoff briefs, reminders, notifications, and summaries
  • Start inside the tools the team already uses
  • Optional ongoing support for tuning, training, and troubleshooting

Best when

The business already has enough system structure to start automating, notifying, formatting, routing, and coordinating work more intelligently.

Starting point

Custom scoped

depends on trigger complexity, systems touched, and testing depth

Ongoing support

Optional

available when the team wants training, tuning, and troubleshooting help

Ask About AI and Automation
System foundation

Systems and Forecasting

Primary outcome

Evaluate, choose, and build the operating layer the business can trust.

The business stops relying on scattered workarounds and starts running through one clearer operating layer leadership can actually see, use, and trust.

Usually includes

  • CRM, PMO, and communication system evaluation + implementation
  • Maintenance-cost and implementation guidance before build decisions
  • Ownership, reporting, onboarding, and forecast visibility

Best when

The workflow needs a better operating layer first: clearer ownership, better reporting, stronger system choice, and a setup the team can actually maintain.

Starting point

Custom scoped

depends on system choice, architecture depth, and rollout scope

Ask About Systems and Forecasting

Training + Ongoing Support

Base, Growth, and Pro keep Keith close for rollout, training, tuning, and troubleshooting without turning the relationship into unlimited custom work.

Setup gets the first useful version live. Ongoing support keeps Keith close for training, workflow tuning, scoped improvements, and rollout questions after launch. New workflows beyond plan limits, customer-facing AI, hosted or server work, and major rebuilds stay separate.

Response targets apply to in-scope requests during normal business hours. Hosted environments, incident response, and heavier custom work are scoped separately.

Base

$500/month

monthly management

Light ongoing stewardship from Keith so the AI and automation layer stays useful without turning management into an open-ended build retainer.

Best for

Teams with a small AI and automation footprint that want direct guidance, light tuning, and a reliable operating relationship after setup.

Workflow scope

Up to 2 active workflows

Meetings

1 monthly working session

Response target

Within 2 business days

Change capacity

1 small scoped change per month

Growth

Recommended

$1,000/month

monthly management

Best for teams that need regular training, steady workflow tuning, and a more active management relationship as usage grows.

Best for

Teams with multiple active workflows, a higher change volume, and a real need for regular adoption support as the AI and automation layer gets used.

Workflow scope

Up to 4 active workflows

Meetings

2 monthly working sessions

Response target

Within 1 business day

Change capacity

2 scoped changes per month

Pro

$2,000/month

monthly management

Best for teams that want Keith deeply involved in the AI and automation layer with faster in-scope turnaround and heavier direct stewardship.

Best for

Teams with a broader workflow scope, more leadership visibility needs, and a higher expectation of ongoing Keith involvement.

Workflow scope

Up to 6 active workflows

Meetings

Up to 4 working sessions per month

Response target

Same-business-day initial response target

Change capacity

Up to 4 scoped changes per month

Management is intentionally bounded. Response targets are not 24/7 guarantees, and the tiers do not include unlimited requests, unlimited automations, major rebuilds, hosted infrastructure, or emergency work. Those get scoped separately so the relationship stays clear and sustainable.

FAQ

Clear answers before we talk.

The most common questions I hear on strategy calls, answered up front so we can spend our call on your specifics instead of the basics.

Operator Notes

Process

Timeline, rollout, and what working together actually looks like.

Operator Notes

Pricing

How scoping, fixed fees, and payment structure work before work begins.

Operator Notes

Results

What adoption, handoff, and support look like after launch.

Operator Notes

Metrics

What leadership should ask, what to measure, and what a useful dashboard should actually tell you.

Next Step

Let's figure out the smartest next step.

No pitch deck. No pressure. Just a real conversation about what feels broken, what would create the fastest win, and whether I am the right person to help.

1

You tell me what's broken

What customers feel, what the team feels, what you've tried

2

I map the best next step

You leave knowing the clearest next move and whether I should help with it

3

You decide if it fits

No follow-up pressure, ever

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30 minutes · No pitch · Just clarity

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