Scheduling that does the calendar math for you

Every interviewer, room and rule, solved into one working schedule.

Calgebra is a scheduling optimization engine. You give it your people, rooms, hours and rules, and it returns the schedule that honors all of them, with every compromise shown, in seconds instead of an afternoon of calendar work.

Tuesday onsite, six interviewers
Illustrative schedule
8:009:0010:0011:0012:001:002:003:00
PriyaPanelPanelPanelLunchPanel
MarcusPanelPanelPanelLunchPanel
DanaPanelMovedPanelLunchPanel
LeoPanelLunchPanelMoved
SamPanelLunchPanelPanel
AishaPanelPanelLunchMovedPanel

Zero hard conflicts. Three panels moved, each inside the interviewer’s stated availability.

Scheduled Clash Moved by the solver Unavailable
Calendar juggling comes at a cost

When time, people, rooms, and other resources collide, someone fixes it by hand, every day.

A single operating week can hold six hard conflicts, and coordinators reconcile them one at a time, which is a poor use of good people. The hours are real, they recur daily, and they almost never appear in a budget line where anyone can see them. Those hours could be better spent with the candidates, keeping them engaged throughout the process.

There is a better way to schedule… well, everything

A “workable” schedule is not a solved schedule.

Take a moment with the video on the right to see what settling for a schedule that technically works really costs, and what changes when Calgebra solves for every rule at once.

Calgebra explainer, 1:31See the four recruiting demos
Musts and preferences

How the engine thinks

Every scheduling problem Calgebra solves is written the way a mathematician would write it, which is also the way your best coordinator already thinks about it.

The rules come in two kinds. Hard constraints are the musts: rules the schedule can never break, and if no schedule satisfies them, the engine says so instead of guessing. Soft constraints are the preferences, such as a VP on the final panel when one is available, which the engine satisfies whenever it can and reports when it cannot.

Example constraints from an interview loop
Must (hard constraints)
panels_per_interviewer_per_day ≤ 4
interviewers_per_panel ≥ 3
room_capacity ≥ panel_size + 1
Prefer (soft constraints)
vp_on_final_panel if vp_available
candidate_wait_between_rounds_min ≤ 15
prioritize_vetted_internal_candidates
Given

Your interviewers, candidates, rooms and shifts, along with everyone’s availability.

Subject to

The rules you enforce today and the ones you wish you could: availability, time zones, panel composition, a daily cap on interviews per person, and travel time between rooms.

Find

The schedule that satisfies every hard rule and does the best possible job on the soft ones, with each compromise listed so a coordinator can accept or override it.

What you get
We show the schedule

Results come back as a schedule you can read, with names, rooms and times.

We list every compromise

When a rule has to bend, you see which one and why before anything goes out.

We work from your rules

The constraints come from how your operation runs, modeled with you first.

Next step

Send us your worst scheduling scenario.

We will send it back solved, with every compromise listed.

Send your scenario