Kosher-Aware Planning
Kashrut turns a production schedule into a chain of run-order rules: what can follow what, on which line, after which cleanout, with which supervision. Semia, an AI employee for food and beverage production planning, treats those rules the way it treats allergen changeovers: it sequences the week around them, re-plans when the day changes, and keeps a record your certifier can audit. A named human approves every plan before anything reaches the floor.
The sequence decides the status. Run a parve dessert on a line that just ran dairy and, under most certifiers' rules, it can no longer be labeled parve. Planners hold this in their heads: which line is parve today, what ran last, what the agency allows to follow it. It is exactly the kind of context that lives in one person's head and never makes it into the ERP.
Moving a line between dairy, meat, or parve status takes the procedure your certifier specifies, often with idle time before kashering. That window has to be planned like any other changeover, except it can swallow a whole shift. Skip it, or squeeze it, and the status of everything that runs next is in question.
Some runs need a mashgiach on site, and that supervision window is a scheduling constraint like any other, except nobody put it in the system. If supervision moves, the run moves, and everything sequenced behind it moves too. Most scheduling tools do not even have a field for it.
A plant that keeps Shabbat and the holiday calendar plans the same demand into fewer days, and the run-up to a chag rewrites the schedule daily. Operators already say the schedule is fiction by Wednesday. In a holiday week it is fiction by Tuesday morning.
Semia already sequences plans for finite capacity, shelf life and FEFO, and allergen changeover cleanouts, the same machinery described on /industries/bakery and /industries/dairy. Kosher status is handled the same way: run-order rules for dairy, meat, and parve, required cleanouts, and kosherization windows placed on the calendar instead of carried in someone's memory. If a term is unfamiliar, /glossary covers changeovers, FEFO, and the rest.
Semia reads orders, inventory and lots, ingredients, attendance, and machine status from the systems the plant already runs: SAP, Odoo, Microsoft Dynamics, Excel, Google Sheets, even the WhatsApp thread where line status actually lives. Everything is read-only, nothing is migrated, and nothing is installed on the line. Granting read access takes about 30 minutes.
The mashgiach postpones, a mixer goes down, a priority order lands mid-morning. Semia re-plans the day without breaking status rules, shelf-life sequencing, or the cleanouts in between. It shows plain-language reasoning for every call it makes, so the planner can see why a run moved before deciding whether to accept it.
Every plan carries a full audit trail: which runs were scheduled, on which line, in what order, and which cleanouts and kosherization steps sat between them. Certification agencies review production records during audits, and this log shows how each day's plan was built, adjusted, and approved. A named human approves each plan before it reaches the floor, so the log also shows who signed off and why.
Semia onboards itself: it sits next to your planner, asks questions, and learns by shadowing real decisions, which lines are parve, which products need supervision, what your agency requires between statuses. It is useful in about two weeks, without a data-cleanup project first.
Semia's design partner is the Natalie bakery and desserts plant in Or Akiva, which supplies the Ben Ami coffee and bakery chain. Daily planning there went from about 3 hours a day to roughly 15 minutes (design-partner data). Semia is not endorsed by any certification agency and does not claim to be; the point is that its constraints were learned in a working plant, next to a real planner, not written from a spec sheet.
Your data stays inside your company, and the planning logic Semia captures, including your kashrut sequencing rules, belongs to you. See /pricing for how that is structured commercially, or book a walkthrough at /demo and bring your ugliest holiday week.
Yes. Semia models dairy, meat, and parve status as run-order rules, the same way it models allergen changeovers: parve runs are sequenced ahead of dairy, and when the order has to flip, the plan includes the cleanout and kosherization window your certifier requires. Every sequencing decision comes with plain-language reasoning, and a named human approves the plan before it reaches the floor.
Semia keeps a full audit trail of every plan: which runs were scheduled, on which line, in what order, which cleanouts or kosherization steps sat between them, and who approved each plan. Kosher certification agencies review production records during audits, and this log gives them a complete, timestamped account of how each day was planned, re-planned, and approved. It documents the planning record; your certifier decides what it means.
No. Kashrut decisions belong to your mashgiach and your certification agency, and Semia makes no ruling on what is kosher. What it does is schedule production around supervision windows, sequence runs to respect status rules, and keep the run log that makes the mashgiach's and the auditor's job easier.
Semia treats non-production days as hard constraints and plans the remaining capacity around them, sequencing for shelf life, changeovers, and kosher status rules at the same time. When a holiday compresses the week, it rebuilds the plan for the days you actually have instead of leaving the planner to squeeze it by hand.
About two weeks. Semia onboards itself by sitting next to your planner, asking questions, and shadowing real decisions, which is how it picks up plant-specific rules like which lines are parve and what your certifier requires between statuses. Nothing is migrated and nothing is installed on the line; it reads the systems you already run.
No, and it does not need to be: Semia is production planning software, not a kashrut authority. Your certification agency's rules stay authoritative; Semia encodes them as sequencing constraints and keeps an audit trail of how each plan applied them. Its sequencing rules are learned by shadowing real planners, in its case at its design-partner plant, the Natalie bakery and desserts plant in Or Akiva.