Academic scheduling without the spreadsheet chaos.
Schedence helps colleges and universities build conflict-aware faculty schedules, balance teaching workloads, manage room constraints, and make complex scheduling decisions easier to understand.
Weekly Schedule Grid
Mon – Fri / Core HoursFaculty Workload Distribution
Policy limits* ILLUSTRATIVE PRODUCT CONCEPT — Fictional academic data representing planned constraint checks and workload planning capabilities. Schedence is in early development.
The Higher Ed Scheduling Dilemma
Academic scheduling gets complicated fast.
Building an academic timetable means balancing faculty availability, teaching loads, room requirements, subject assignments, institutional policies, and hundreds of possible conflicts.
Scheduling Conflicts
Overlapping course times, double-booked professors, and cohort collisions create friction across departments that static spreadsheets fail to prevent.
Uneven Faculty Workloads
Opaque tracking leads to some professors exceeding contractual teaching limits while others are under-allocated, complicating institutional equity and compliance.
Room & Resource Constraints
Matching specialized labs, seat capacities, audio-visual equipment, and campus transit gaps to courses requires balancing hundreds of intertwined variables.
Hours Spent Manually Revising
A single last-minute instructor adjustment often triggers a chain reaction of timetable changes, demanding weeks of manual spreadsheet recalculations every term.
Product Capabilities
Built around the realities of academic scheduling.
Every feature is calibrated for university registrars, deans, and academic departments to turn complex constraint matrices into transparent schedules.
Automated Timetable Generation
Deterministic algorithms designed to synthesize conflict-aware lecture and lab timetable candidates, eliminating weeks of manual spreadsheet iteration.
Faculty Workload Management
Real-time tracking of teaching credits, contact hours, and prep loads ensures equitable allocation and contract compliance.
Conflict Detection
Continuous constraint validation spots double-booked instructors, room overlaps, and student cohort collisions instantly.
Room & Subject Constraints
Matches seating capacities, specialized lab infrastructure, campus building transit, and subject requirements precisely.
Faculty Availability
Respects teaching preferences, research release days, sabbaticals, and adjunct availability windows without manual cross-checking.
Designation Load Adjustments
Automatically offsets teaching loads for department chairs, research directors, and administrative appointments.
Scheduling Intelligence
Specialized academic heuristic modeling balances institutional policy rules with faculty preferences and student progression needs.
Building intelligent scheduling assistance with Claude
Schedence is exploring Claude to help administrators understand scheduling conflicts, workload recommendations, and generated timetable decisions in natural language.
Mathematical Constraint Engine
Core SchedulerSchedence is architected to perform timetable generation through mathematical and constraint-based scheduling, deterministically modeling room caps, blackout hours, and faculty credit limits.
Claude Natural Language Layer
Exploratory InterfaceRather than forcing deans to decipher constraint matrices, Claude is being explored to explain tradeoffs, clarify slot assignments, and summarize workload distributions in conversational English.
Academic Dean • Inquiry
"Why did the generator move CS-402 (Distributed Systems) from Tuesday morning to Thursday at 1:00 PM?"
The constraint solver identified two policy violations with Tuesday 10:00 AM:
- •Campus Transit: Prof. Vance has an in-person lab ending at 9:55 AM in West Science Complex (violating the 20-minute inter-building transit policy).
- •Capacity Fit: Hall 102 provides 60 seats for 55 enrolled students on Thursday, while Tuesday's available room capped at 40 seats.
Implementation Workflow
From raw curriculum to verified timetable.
A structured, repeatable six-stage process designed to bring clarity and control to university scheduling operations.
Set up academic data
Import academic catalog terms, course sections, lecture hall inventories, seating capacities, and lab equipment profiles.
Assign faculty
Connect faculty members to eligible subjects, tenure tracks, administrative designations, and contractual teaching limits.
Define constraints
Configure instructor availability windows, research release blocks, room prerequisites, and campus transit buffers.
Generate timetable
Run the deterministic constraint solver to evaluate schedule permutations and generate a balanced timetable.
Resolve conflicts
Review trade-off summaries, inspect constraint checks, and make granular adjustments with clear feedback.
Publish
Export verified timetables for distribution across academic departments, faculty, and campus offices.
About Schedence
Built for a difficult problem.
Schedence is an early-stage education technology project founded in 2026, focused on making academic scheduling and faculty workload planning easier for higher-education institutions.
Focus on Academic Realities
Higher-education scheduling is fundamentally distinct from corporate calendar management. Universities balance specialized course prerequisites, limited laboratory resources, adjunct contracts, and complex faculty governance rules.
Schedence is architected to address these nuances directly through rigorous constraint modeling rather than generic appointment scheduling.
Project Leadership
Schedence is currently led by its Founder & Developer, combining deep software engineering with academic domain research to build dependable scheduling infrastructure.
Interested in Schedence?
Schedence is currently in early development. Universities, faculty members, and academic administrators interested in the project can get in touch.
Inquiries typically receive a direct reply within 1-2 business days.
Share institutional scheduling constraints to directly influence the solver roadmap.
Discuss departmental workflows and explore upcoming prototypes with zero commercial obligation.
Institutional inquiries and scheduling parameters remain strictly confidential.