Business practice
Advice that ships.
Operations consulting and manager training for SaaS and AI companies of 20 to 200 people that have been handed enough slide decks. Every engagement ends with something running, measured, and owned by your team.
The situation
None of this is hypothetical.
Your managers were never trained.
Your best reps became your managers, and the job changed under them. Escalations climb, the queue drifts, and the one-on-ones don't happen. It isn't a talent problem. Nobody taught them the next job.
The work is invisible.
Nobody can say, precisely, how your highest-cost workflow actually runs today. It lives in habits, Slack threads and two people who can't take vacation at the same time. What isn't written down can't be improved, priced or handed off.
AI arrived without permission.
Your team is already using AI tools, quietly, sometimes on customer data. Your enterprise customers' security reviews have started asking about it, and "we're working on it" isn't an answer that closes the deal.
What we do
Our services.
You need someone who has run the work, not only studied it. The Intentional Company brings fourteen years of SaaS customer operations to the problems in front of you now: the managers, the queue, the handoffs, the customers who go quiet, and the AI your team is already using.
Most work starts one of two ways. Manager Fundamentals trains the frontline managers who run the work. The 30-Day Proof puts one operational fix live inside thirty days, owned by a named person on your team.
Managers and teams
Manager Fundamentals
Your best reps became your managers, and nobody taught them the next job. Eight live sessions later, each one runs the work with a charter, a scorecard and a plan for every person on the team.
- Eight 45-minute sessions, live, one a week
- An artifact every week, built on their own team
- Measured against each manager's own baseline
New-Hire Ramp
New reps learn by shadowing whoever's free, so the standard drifts with every hire. You get a ramp with milestones that makes productivity predictable.
- Milestones at 30, 60 and 90 days
- Built on the procedures your team already follows
- Refreshers aimed at where the work slips
Support Team Structure
Roles grew around whoever happened to be there. You get tiers, escalation paths and owners that make it obvious who decides what.
- L1 to L3 tiers and escalation paths
- Named owners across support, CS and implementation
- Decisions that stop queuing
Capacity Planning
When the queue grows, the instinct is to hire. You get an honest read on which pressure is staffing and which is process, before the offer goes out.
- Capacity measured, not estimated
- Staffing problems split from process ones
- A plan you can defend to a board
Customers
Customer Retention
Accounts don't announce they're leaving. They go quiet. You see it early enough to act, and the handoffs that used to cost you renewals get an owner.
- Exit points found from the accounts you already lost
- First 90 days rebuilt around visible value
- A review cadence that surfaces a cooling account
Customer Onboarding
The first ninety days set the whole relationship. You get a first win on the calendar, a clean handoff to CS, and an exit that tells you why.
- Time to value designed, not hoped for
- A clean implementation-to-CS handoff
- Offboarding that returns an honest reason
Customer Journey Mapping
Nobody has drawn the path a customer actually takes, so every team optimizes its own piece. You get the whole path, first call to renewal, with every handoff owned.
- Every touchpoint from first call to renewal
- The handoffs where customers go quiet, owned
- One view the whole team works from
Operations
Process and Workflow
The work gets done because specific people remember how. You get your costliest workflow measured, simplified and running the same way twice.
- Your highest-cost workflow mapped as it runs
- A cost baseline every later claim is measured against
- Automation only after simplification
SOPs and Documentation
The procedures that matter live in two people's heads. You get the ones worth writing captured in your team's words, owned, and reviewed on a date.
- Internal SOPs and knowledge base articles
- Written from the real work, not from memory
- An owner and a review date on every document
AI
AI Adoption
Buying the tool was the easy part. You get named use cases in support, success and ops, one owner each, and adoption you can see in the work.
- The work AI should take on, and the work it shouldn't
- Named use cases, each with an owner and a measure
- Adoption tracked where the work happens
AI Change Management
A rollout that arrives as an announcement gets treated as one. You get a change plan built with the people doing the work, so the new way survives the first busy week.
- Where the resistance actually sits, asked not assumed
- Training built around real tasks
- A checkpoint after go-live
AI Use Policy
Security questionnaires, SOC 2 auditors and cyber insurers now ask whether you have a written AI policy. Within weeks the answer is yes, and it holds up.
- Tools tiered, data classes in plain language
- Signed by your whole team
- A named owner and a review date
Shadow AI Exposure
Your team is using AI tools nobody approved, some of them on customer data. In about ninety minutes of your time, you know which, and what to do this week.
- An anonymous team survey for the real picture
- Which customer data went into which tool
- A one-page exposure map in 72 hours
How we engage
The 30-Day Proof
You've paid for advice before and received a document. Thirty days from now one workflow runs differently, a named person owns it, and you have a before and after number.
- One fix built and live before the engagement ends
- Every finding scored on impact and complexity
- Nothing running on day thirty means no invoice
Fractional Operations
The operation is running on you, and everyone knows it. You reach a point where it has an owner who isn't you, and you still make the calls that matter.
- A weekly operating cadence that's run, not attended
- A governed roadmap, including what you're not doing
- One client at a time, with a successor built in
Results
20%
Lower support cost, one year
50%
Faster customer onboarding
50%
Less customer churn
Results achieved in prior operating roles, across fourteen years in SaaS customer operations. Every company is different, so treat these as evidence of the approach, not a forecast of your numbers.
Fit
This works when it fits.
Works well when
- You're a SaaS or AI company of roughly 20 to 200 people.
- The CEO or COO is in the room and can make a decision.
- Your support, success or ops teams are growing faster than the managers leading them.
- You suspect your team is already using AI and would rather know than wonder.
- You want one thing measurably improved more than you want a strategy document.
Works badly when
- You've already decided the answer is building a custom AI agent.
- Your core problem is pipeline or marketing, because that's not this lane.
- You're under twenty people, where the pain is real but the structure isn't there yet.
- You're an enterprise with a procurement cycle longer than the engagement.
- Nobody with authority can give the work four scheduled hours in thirty days.
Questions
Asked before, answered plainly.
Exactly what it says. If day thirty of the 30-Day Proof arrives and no fix is running and measured in your business, the invoice is zero. Not discounted. Zero. The guarantee attaches to shipping, which we control, not to a promised percentage, which nobody honestly controls. If the fix breaks within sixty days for a reason inside scope, we repair it at no charge.
No. It's an operations practice. We help SaaS and AI companies lower operating costs through manager training, process improvement and practical AI integration. Most findings in a typical diagnostic aren't AI at all. They're unwritten processes, duplicate software and broken handoffs, and AI has to earn its place like everything else.
With one of two things. Manager Fundamentals, if the problem shows up as managers who were never trained for the job, or the 30-Day Proof, if it shows up as one workflow that costs too much. Plenty of companies do both, usually in that order.
The engagement is structured so a document can't be the final deliverable. The readout includes a fix that's already live, its written procedure, and its measured before and after. Findings are included, but findings are the beginning of the engagement, not the end of it.
No, and we say so on the first call and in the document itself. It's an operational policy: which tools are sanctioned, what data may enter them, and how your team acknowledges it. It's the document security reviews and insurers ask about. Your counsel should review it, and it's written so that review is fast.
Four scheduled hours of access across the thirty days, timely decisions on the fix we scope together, and honesty about how the work really happens today. The guarantee is a two-way agreement. We commit to shipping. You commit to being reachable enough that shipping is possible.