Syllably · EdTech AI module
Course materials in, a draft syllabus, lessons and quizzes out.
Syllably turns an instructor's or designer's source materials (program outcomes, textbook chapters, lecture notes, policies or SOPs) into a draft syllabus: outcomes mapped to the program, a week-by-week plan, assessments that add up, lessons and quiz items. A person reviews and edits it before anything is published.
A reference build, not software you license. It is built to ship under your product's name.
admin.northstarcampus.com / courses / HIT-210 / syllabus
Northstar College · Syllably
DemoStep 1 of 3
Illustrative demo on a fictional institution. Not client work.
The problem
Every new course, and every revision, starts from a blank syllabus. Instructors and designers rebuild the week-by-week plan by hand, map outcomes for accreditation in a spreadsheet, and write quizzes from scratch. Generic AI drafts drift away from the materials and the program's rules.
The worked example
Northstar College (fictional). An instructor uploads the program outcomes, four textbook chapters and last term's lecture notes for a redesigned evening course, HIT-210 Health Information Technology.
Document parsing into structure, generation constrained to the uploaded materials and the program's rules, outcome mapping, and an approval workflow with versioning. Works the same way for corporate courses built from SOPs and policies.
From course materials to a draft syllabus
Outcomes, chapters and lecture notes become a syllabus that maps, adds up and cites its sources.
Draft the syllabus to watch outcomes, the weekly plan, assessment weights and a quiz item appear, while the material each part came from lights up.
Course materials · HIT-210 · Northstar College
InputProgram outcomes · AAS Health Information Technology
- PO1 Apply diagnosis and procedure coding systems
- PO2 Protect health information under HIPAA
- PO3 Work in electronic health record systems
- PO4 Check the quality and integrity of health data
Textbook · Health Information Management, 6th ed.
- Ch 1 The health record
- Ch 3 Coding systems
- Ch 5 EHR systems
- Ch 7 Privacy and security
Last term's lecture notes · 12 decks
- Lecture 4: ICD-10-CM vs CPT, worked examples
- Lecture 9: Data quality audits
Department rules
- 10-week evening term, Tue and Thu
- Assessments total 100%
- Practicum worth at least 25%
Outcomes, chapters, lecture notes and rules in. A draft syllabus out, every part traced to its source.
Illustrative demo on a fictional institution. Not client work.
AI inside the workflow
Syllably inside the product, not a chatbot beside it.
Switch between the product as it ships today and the same screen with the module working inside it. Ask a question, then approve what it prepares.
Northstar Campus · fictional product
Northstar Learn today: every syllabus is written from scratch and outcomes are mapped in a spreadsheet.
The assistant runs Syllably, branded as Northstar Author, the way it is built to ship under your product's name.
Illustrative demo on a fictional institution. Not client work.
What it does
What Syllably does inside your product.
Best fit: Higher ed and courseware, CE, corporate LMS and compliance training.
Outcomes mapped
Writes course learning outcomes and maps each one to the program outcomes it serves, ready for accreditation reviews.
Week-by-week plan
Lays out topics, readings and assessments across the term from the uploaded materials, within your department's rules.
Assessments that add up
Proposes assessments and weights, checked against the program's grading rules.
Lessons and quiz items
Drafts lesson plans and quiz items with answer rationales, each traced to the chapter, slide or policy it came from.
Reviewer in the loop
Nothing is published until an instructor, designer or program chair approves it; versions are kept.
How it works
One AI feature, working inside your product, in two weeks. $10,000, fixed.
In two weeks: Syllably working in your staging environment behind a feature flag, drafting syllabi or courses from three of your customers' real materials, delivered as pull requests, scored by your team with customer instructors invited where available, with a cost per draft and a fixed production quote.
- 01
EdTech Product Review
30 minutes, free
We look at your product with you and pick the AI feature that fits your next release, what it would cost to serve, and what your customers' security review will ask.
- 02
The Sprint
$10,000 fixed · setup week, then two weeks of build
In the setup week we agree the feature, the eval cases and the data, and you grant staging and repository access; no build time is used. Then two weeks of build: one AI feature working inside your product, running in your staging environment on your catalog, published documents or synthetic data, behind a feature flag, delivered as pull requests. You also get quality and safety evals, a cost estimate on two models, a data-flow sheet and a fixed-price quote for production.
- 03
Targeted Unlock, then Capability Waves
Quoted at the end of the Sprint
The first production capability, delivered by pull request into your repo with no standing production access. Then the next module, on the foundation the first one built.
Built for education data
Controls your customers' security reviews ask about.
Each control is a design fact about how the module is built and how we work, not a compliance claim.
- Reads your catalog, courses, rosters and gradebook through the APIs and roles your product already has. No rebuild.
- Sprint work uses synthetic or de-identified data and ships as pull requests to your repo. No production student data.
- Answers cite the catalog page, policy or help article they came from; anything that changes a grade, an application or a student record waits for staff approval.
- Built around FERPA, COPPA, accessibility and institutional requirements.
- Built to ship under your product's name. Model and hosting are your choice.
We build around your FERPA, COPPA, accessibility, security and institutional requirements. Compliance depends on the complete product, contracts, policies and operating environment; Datics does not present software engineering alone as legal certification.
How we handle student dataWork this builds on
Projects we have delivered that use the same engine or the same engineering pattern.
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See Syllably on your own product.
Bring one product, workflow or AI initiative. In 30 minutes we pick the module that fits first, what it would cost to serve and what your customers' security review will ask.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.