Hard Constraints
Never defer an order near cutoff, never exceed active-work cap, and never assign work to a blocked zone. Enforced inside the optimization model and configured per tenant.
Trust
Autonomy you can verify.
Hard constraints. Anomaly detection. Graduated autonomy. Full audit trail. Every decision replayable.
AUTONOMY, WITH GUARDRAILS.
Anomaly Detection
If reality diverges from predictions — pick times exceeding estimates for consecutive cycles, supervisor overrides exceeding a threshold, unexpected spike in late-risk orders — Tessera pulls itself back to advisory mode automatically. The system knows when it's wrong.
Graduated Autonomy
Start with low-risk decisions. Move higher-stakes decisions to automation only after confidence is earned.
Audit Trail
Every recommendation, override, and predicted impact is logged. Each cycle is replayable and reviewable.
ADVISORY OR CLOSED LOOP.
Same optimization core. Same explanations. What changes is whether the plan goes to a dashboard or gets pushed back into the WMS.
ADVISORY
Tessera recommends, the operator decides. Read-only connection, recommendations on a dashboard with full reasoning. The operator reviews and approves, modifies, or rejects each cycle.
CLOSED-LOOP
Tessera executes, the operator oversees. Decisions push directly into the WMS with hard constraints, anomaly detection, and graduated autonomy as guardrails. The operator sets the posture and intervenes by exception.
AI THAT SHOWS ITS WORK.
Tess is an AI copilot. That means earning trust, not assuming it.
GROUNDED IN OPTIMIZER DATA. NOT GENERATED NARRATIVES.
Tess is not a language model guessing at warehouse operations. It has direct access to the optimization engine — when you ask a question, Tess modifies inputs and runs the optimizer to find the answer. When Tess says "this batch was deferred because Zone C is congested," that points to a specific binding constraint in the model. When it says "zero late-risk requires raising the Zone A cap to 48," that's the result of an actual optimizer run with modified parameters. If Tess can't ground a statement in optimizer output, it doesn't make the statement.
THE OPERATOR VERIFIES. ALWAYS.
In advisory mode, Tess helps operators review recommendations efficiently — "Summarize the top three changes," "Which ones are reversible?," "Which one reduces deadline risk the most?," "Apply only the priority updates." In closed-loop mode, Tess becomes the transparency surface — "Why did the system fall back to advisory?," "Pause automatic release changes next cycle," "Require approval for large deferrals." The operator always has the tools to check the system's work.
RIGOR YOU CAN MEASURE.
Before/after metrics and constraint adherence - every run.
-12%
Travel distance
-8%
Pick time
+15%
Throughput at same labor
100%
Constraint compliance
Placeholder metrics. Replace with observed facility data when available.
Tessera does not ask you to trust a black box. Every recommendation includes predicted impact, and every cycle produces measurable before/after comparisons. The track record is visible, queryable, and auditable.