Email:info@softosmith.com
Working Hours:Mon - Fri: 9 AM - 5 PM (PKT)
For schools and training providers weighing AI opportunities against student data risk and institutional trust. In 10 business days, fixed price, we map where AI safely fits your admissions, admin, and LMS-adjacent workflows — no software pitch at the end.
You have a “how do we adopt this safely” problem. Instructors and staff are already curious about AI, admin workflows are stretched thin, and every idea has to be weighed against student data and institutional trust before it goes anywhere.
A tool that would be a quick trial anywhere else is a real risk decision here, because it touches student records, and nobody has mapped exactly what data it would see.
Enrollment questions, admissions follow-ups, and routine admin work repeat every term, while staff capacity to handle them doesn't grow with it.
Instructors and staff are already experimenting with AI tools individually, often faster than any institutional policy on data handling or approved use has been written.
Picture admissions and admin staff spending even 8 hours a week on manual follow-up and enrollment work that a well-built automation could handle — that's over 400 hours a year of staff capacity, every year, spent on repeatable work instead of students. Gartner and other industry researchers have warned that a large share of AI projects get abandoned within their first year, most often because nobody had a clear picture of which process to target or whether the underlying data supported it responsibly. In an institutional setting, that failure mode carries more weight than a missed software trial — this audit exists to give you that picture before any tool touches student data.
Five concrete deliverables, with data handling and institutional trust treated as first-class constraints throughout — not a generic AI-in-education slide deck.
Every deliverable is something your academic and administrative staff can open, act on, and keep.
A direct conversation with your key staff to pin down the admissions, enrollment, and admin workflows eating the most time, and where AI tools are already being used informally without institutional oversight.
We map your three to five highest-friction workflows — often admissions follow-up, enrollment processing, or LMS-adjacent admin — step by step. Any workflow touching student or staff data gets flagged for data handling and access-control review as part of this step.
What's already available for your exact LMS and administrative stack, what comparable institutions are already doing with AI, and where safe, responsible adoption could realistically move you forward in a term.
Every opportunity found, scored on Impact, Effort, and Readiness — with data sensitivity factored into the Readiness score for anything touching student or staff records. You get this as a working spreadsheet you own outright.
A document built for whoever signs off institutionally: a 30-day sprint, a 90-day roadmap, a 12-month direction, budget ranges, and how each recommendation was checked against safe, responsible use of student data.
Not a strategist reading a framework. This audit is run by the person who actually builds AI systems and data pipelines for a living — including 8+ years of hands-on Moodle development experience.
$2,500. One number. No scope creep, no surprise invoice halfway through the term.
The spreadsheet and the plan are yours outright. Take them to your IT department, another vendor, or back to Softosmith.
Every workflow involving student or staff data gets a data-handling and access-control note as part of the recommendation — not an afterthought bolted on at the end.
30 minutes, free. We talk about your institution, your existing systems, and whether this audit is actually the right move right now. If it isn't, you'll hear that directly.
10 business days, $2,500 fixed. Your side commits roughly 8 to 10 hours total across the two weeks, spread across academic and administrative staff. The heavy lifting is on us.
Day 11 onward, your team runs the plan. If you'd rather have Softosmith build what it recommends, that work is scoped and billed separately at $60/hour. The audit stands on its own either way.
A good fit if:
You run a school, training provider, or education organization with a real decision pending about where AI fits, and what it means for student data.
Instructors or staff are already using AI tools informally, and nobody has a clear picture of what data those tools actually touch.
You want a sequenced plan with real budget numbers and a data-handling review, not another vendor demo.
You can commit 2 to 4 academic or administrative staff for a few hours of conversation across two weeks.
Probably not a fit if:
You run a program small enough that the audit overhead costs more than the manual work it would replace.
You already have a finished AI adoption policy and only need someone to implement it — ask about a direct build engagement instead.
You want a free strategy session disguised as a sales call — this is a paid diagnostic with real deliverables.
Nobody on your side can spare even a few hours of input over two weeks.
No client logos or star ratings here — just the commitments this audit is held to.
You work directly with Amin Ali, the person actually running the audit — no account manager relaying messages back and forth.
The $2,500 we quote upfront is what you pay. No surprise invoice halfway through the audit.
The spreadsheet and the Action Plan are yours outright, on day 11. Take them anywhere, including nowhere.
The same productized audit used across every client — just scoped around data handling, LMS context, and admin workflows.
$2,500 fixed price
The same fixed-price, 10-business-day audit, scoped around data handling, LMS context, and admin workflows.
If you're an owner-operator looking to save time on ops and admin rather than manage institutional data risk, the small-business version of this audit is built around that.
$2,500, fixed. No hourly billing, no line items that show up later.
10 business days from kickoff to the final Action Plan in your inbox.
Yes. Any workflow involving student or staff data gets flagged for data handling and access-control review as part of the Workflow Maps step. Softosmith isn't a compliance auditor and doesn't issue certifications, but student data handling is treated as a first-class constraint in every recommendation, not an afterthought.
Yes, meaningfully. Softosmith has 8+ years of hands-on Moodle development experience, so the Stack and Competitor Scan can speak directly to what's realistic inside your existing LMS rather than assuming a rip-and-replace.
Roughly 8 to 10 hours total, spread across academic and administrative staff over the two weeks. Most of the work happens on our end.
A one-page Operations Snapshot, Workflow Maps with a cost model, a Stack and Competitor Scan, a Prioritized Opportunity List as an editable spreadsheet, and a 3 to 5 page Action Plan covering 30, 90, and 365 days.
Yes, billed separately at $60 per hour and scoped to the specific recommendation. You are never required to use Softosmith for the build.
Book the free 30-minute discovery call. If it's a fit, the audit can usually begin within two weeks.
Or you can spend another quarter debating AI policy in a committee meeting. Your call.
