Today
Scattered inputs, one lonely decision
- Each source explains itself, never your choice
- Costs, ranking, careers and deadlines never sit side by side
- Advice arrives as opinion, without reasoning
- The student decides alone, under time pressure
AI Decision Intelligence for students
Better Match.
Bigger Futures.
SajiGo is an AI-powered Decision Intelligence Platform for students. It turns fragmented university, scholarship, affordability, career and application information into personalised, explainable decisions.
- Personalised to the profile
- Explainable by design
- One decision layer
02 — The problem
Information isn't the bottleneck. Decisions are.
Students piece the picture together from dozens of unrelated places — university sites, scholarship databases, cost calculators, career data and application portals. Every source answers a different question, and none of them answers the one that matters: what should I actually do?
- University websites
- Scholarship databases
- Fee & cost calculators
- Course catalogues
- Career outlook reports
- Entry requirements
- Application portals
- Deadline trackers
- Ranking tables
- Advice from friends
- Group chats
- Agent leaflets
Twelve sources. Twelve deadlines. Twelve opinions — and still no answer.
With SajiGo
One profile, one analysis, one clear decision
- One profile holds goals, budget, constraints and preferences
- Options are analysed against the student, not the crowd
- Every recommendation arrives explained, with its trade-offs
- The decision is the student's — made with clarity
03 — How it works
From a student profile to a decision you can defend
Six connected stages. Each one hands the next a clear, structured input — so nothing important gets lost between research, shortlisting and applying.
GoalsBudget
ConstraintsPreferences
Student Profile
The student sets the context: what they want, what they can afford, what they cannot compromise on and what they simply prefer.
Structured inputsWeighted in parallel
AI Analysis
SajiGo's AI reads the profile and analyses the available options against it — profile, budget, goals, constraints and preferences held together instead of judged separately.
RankedPersonalised
Match
Options are matched to that specific student — not to an average ranking, and not to whoever shouts the loudest.
Why this one?
Fit with goals
Affordability
Trade-off
Reasoning shown
Explain
Every match comes with its reasoning in plain language. SajiGo shows what pushed an option up — and what it asks the student to give up.
Trade-offs surfaced
Decide
Trade-offs are laid out side by side so the student makes the call with the full picture in front of them — and owns it.
Guidance continues
Support
The decision is not the end. SajiGo stays alongside the student as they act on it — through the next steps and the applications that follow.
04 — Product
The real SajiGo product surfaces
The interface, the matching layer, the decision report and Bob, the AI assistant — shown here with SajiGo's own product visuals.
SajiGo MVP
The working product, not a mock-up
One workspace where a student's profile, the options in front of them and the reasoning behind each one live together. The MVP is the foundation every other surface sits on.
- Profile-driven, not search-driven
- Options kept in context with the student's constraints
- Built on an explainable recommendation core
AI Match
Matches built from the profile
The AI Match surface lines options up against what this student actually needs — goals, budget, constraints and preferences weighed together, then ranked.
- Ranked against the individual, not the crowd
- Budget and affordability carried into the match
- Feeds directly into the decision report
Decision Report
The decision, written down and explained
A decision report the student can read, question and take with them — the recommendation, the reasoning behind it and the trade-offs it carries.
- Recommendation with its reasoning attached
- Trade-offs stated rather than hidden
- Next steps the student can act on
Bob AI Assistant
Ask, and get an answer you can follow
Bob is the assistant inside SajiGo. He takes the student through the reasoning — what changed a match, what a trade-off really costs, and what to do next.
- Answers tied to the student's own profile
- Explains, rather than just asserts
- Keeps the decision moving forward
05 — Meet Bob
Meet Bob.
Your AI study & decision advisor.
Bob intro
Bob introduces himself
Press play — sound on
Helping you make smarter study decisions, from choosing your path to taking your next step.
06 — Decision Intelligence
Personalised, explainable, and honest about trade-offs
SajiGo holds profile, budget, goals, constraints and preferences in one model — so a recommendation always arrives as a recommendation with reasoning: why it won, what it costs, and what to do next.
Set the context
Illustrative scenarioConstraints
The weights and constraints above are illustrative inputs. They exist to show how SajiGo turns a profile into a ranked, explained decision.
Recommendation
—
Explanation
—
Trade-offs
—
Next steps
07 — Progress
What exists today
Only what is verified by the materials in this release is shown here. No projections, no borrowed numbers.
Working product interface
The MVP interface is built and running — the decision workspace shown in the supplied product capture.
Verified by supplied product capture
iPhone product experience
The student experience is designed and built for iPhone, carried through the supplied device visuals.
Verified by supplied device visuals
Bob, the AI assistant
Bob exists as part of the product — the assistant that walks students through the reasoning behind a recommendation.
Verified by supplied assistant assets
Brand & app identity
The SajiGo identity — logo, app icon and visual language — is defined and in use across the product.
Verified by supplied brand assets
Decision journey framework
The full student journey is defined end to end, from first discovery through to graduation.
Verified by supplied journey framework
On numbers: traction, adoption and outcome metrics are deliberately absent from this page. SajiGo publishes measurements when they can be verified — not before.
08 — Demo
See a decision being made
A short walkthrough of SajiGo: building a profile, watching the AI analyse it, and following a recommendation all the way to an explained decision.
0:00 / 0:00
09 — Business & vision
Students stay free. The ecosystem pays.
Students never pay for the decision layer. The value SajiGo creates sits with the wider ecosystem around the student — the organisations that want to be there at the moment a student chooses. Students get clarity. The ecosystem gets relevance.
- Free for studentsThe decision layer stays open to every student.
- Aligned with the ecosystemValue flows from those who benefit when a student decides well.
- Explainable by defaultEvery recommendation arrives with its reasoning attached — nothing hidden.
The long-term journey
One student, eight stages — SajiGo's ambition reaches the whole way through.
01
Discover
Where a student first sees what is actually possible.
SajiGo Early Access
Be first in line.
Decision Intelligence for Students. Faster. Smarter. Simpler. Safer.
- Early access to the website and the app, before public launch
- A direct line to the team building it
- One email when it's ready — nothing else
Join the waitlist
You’re on the list! 🎉
Thank you for joining SajiGo Early Access. We’ll let you know when access is available.
SajiGo
Make a better decision.
Better Match. Bigger Futures.
SajiGo doesn't just help students find universities. It helps students decide what is right for them.