AI you can audit
Every scheduling vendor says AI-powered. Most planners have learned to ignore the output, because a schedule you cannot interrogate is a schedule you rewrite by hand. Semia is built for that skepticism: it explains every call in plain language, keeps a full audit trail, and nothing reaches the floor until a named human approves it.
Every scheduling tool on the market says AI-powered, and planners have heard it before. Most have a story about a black-box schedule they quietly rewrote in Excel. That distrust is earned, and any AI production planner that wants to change it has to show its work.
A schedule that arrives without reasons gets overridden the first time it looks wrong, and after that it is decoration. Planners carry context no model saw: the line that runs slow after a changeover, the customer who always doubles the Friday order, the allergen sequence quality insists on. If the software cannot explain itself against that context, the planner is right to ignore it.
A copilot is useful, but it assists a human who still builds the plan: pulling orders, checking stock and lots, checking who showed up, sequencing the day. Semia works the other way around. It delivers a finished draft plan and asks your planner to approve it, so the human effort moves from assembling to deciding.
APS and ERP scheduling modules can absolutely produce plans; the honest problem is everything around them. Deployments tend to be heavy and slow, they depend on clean structured data most plants do not have, and the model drifts away from the undocumented rules in the planner's head. Semia is built for messy reality: it reads the systems you already run and learns the unwritten rules by shadowing.
Every decision in the plan comes with the why written out: why this batch runs first, why a lot close to its shelf-life limit ships today, why the cleanout sits between the allergen runs. Your planner can check the logic instead of guessing at it, and correct it where it is wrong. Terms like FEFO and changeover are defined in /glossary if your team wants the vocabulary.
Semia never pushes a schedule to production on its own. A named person on your team reviews tomorrow's draft and approves it, every day. Semia proposes; your planner decides. That single rule is why planners work with it instead of around it.
Every plan, every re-plan, and every override is recorded with its reasoning. When a customer or quality asks why a run was sequenced the way it was, you show the trail instead of reconstructing the morning from memory. The captured planning logic belongs to your company, and your data never leaves it.
Semia onboards itself. It sits next to your planner, asks questions, and learns the rules that never made it into the ERP, the ones everyone means when they say it all lives in one person's head. Granting read access to your systems takes about 30 minutes, and Semia is useful in about two weeks.
Every morning Semia writes tomorrow's plan, sequenced for finite capacity, shelf life and FEFO, and allergen and changeover cleanouts. It reads orders, inventory and lots, ingredients, attendance, and machine status from the systems you already run: SAP, Odoo, Microsoft Dynamics, Excel, Google Sheets, even the order emails in Outlook or Gmail and the WhatsApp thread with the warehouse. Read-only, nothing migrated, nothing installed on the line.
A mixer goes down, a driver calls in sick, a big customer moves an order: in most plants the schedule is fiction by Wednesday. Semia redraws the plan when the day changes, shows what moved and why, and sends it back to your planner for approval. No spreadsheet hell at lunchtime.
At the Natalie bakery and desserts plant in Or Akiva, which supplies the Ben Ami coffee and bakery chain, daily planning went from about 3 hours a day to roughly 15 minutes. That is design-partner data, not a projection: 12x faster planning and 700+ hours a year returned to the plant. If you run a bakery, see /industries/bakery for the specifics; dairy and meat plants have their own pages at /industries/dairy and /industries/meat.
A single plant bleeds $2-3M a year on overproduction, idle capacity, and chargebacks: roughly $250K a year in waste, about $2M a year in idle capacity, and around $500K a year in chargebacks. The plan that leaks that money is usually assembled by hand each morning, from memory. Pricing is at /pricing, and you can see the plan Semia would write for your plant at /demo.
No. Semia shows plain-language reasoning for every call in the plan, why each batch is sequenced where it is, and keeps a full audit trail of every plan, re-plan, and override. A named human on your team reviews and approves each schedule before it reaches the floor. If a decision looks wrong, the planner can see exactly why Semia made it and correct it.
Planners bypass schedules they cannot interrogate, and they are usually right to. Semia is built against that failure mode: it explains every decision in plain language, it learns the plant's unwritten rules by shadowing the planner, and the planner approves every plan before it goes out. The schedule stays the planner's schedule; Semia just does the assembly.
Nothing reaches the production floor without a named human approving it, so a wrong call gets caught at review, not on the line. The planner corrects the draft, and Semia records the correction in the audit trail and learns from it, the same way it learned the plant's rules by shadowing. That captured planning logic belongs to your company, and it keeps Semia's drafts aligned with how your plant actually runs.
No. Semia is an AI employee that does the assembling, reading orders, stock, lots, attendance, and machine status, then drafting the sequence, so the planner spends the morning deciding instead of compiling. It also reduces key-person risk: replacing a skilled planner costs $20-40K by industry estimates, and the knowledge in their head is harder to replace than that. Semia captures that logic, and it belongs to your company.
APS and ERP modules can produce plans; the difference is what it takes to get there and to keep them true. Traditional APS deployments tend to be heavy, slow to roll out, dependent on clean structured data, and hard to keep aligned with the undocumented context in the planner's head. Semia reads the messy systems a plant already runs, learns that context by shadowing, and delivers a finished draft plan for human approval.
About two weeks. Granting read-only access to your existing systems takes about 30 minutes, then Semia onboards itself by sitting next to your planner, asking questions, and shadowing how the plant actually schedules. There is no data migration and nothing is installed on the line.