Per-tenant isolation
Every plant gets isolated data, models and vector stores. Cut recipes and species models never cross a tenant boundary — federated learning shares patterns, never your product IP.
Security & assurance
Autonomy you can prove.
In a regulated plant, a decision without evidence is a liability. Slicium records the frame, the model, the confidence, the approver and the outcome for every action it takes.
Controls
Six controls that make autonomy acceptable.
SOC 2 Type II (in progress)HACCP-alignedUSDA-FSISEU 853/2004GDPRISO 27001 (planned)
Assurance-grade audit trail
Immutable logs link sensor frames, model version, autonomy level, approvals, overrides and outcomes for every agent action — built for recall defence and model governance.
Fail-safe by design
Blade, robot and line stops are deterministic and independent of the cloud. Graceful degradation returns the cell to a safe state if perception confidence drops.
Data residency & on-prem
Run fully on-premise on the plant edge, in your VPC, or hybrid. Sensitive producers can keep every frame inside the facility.
SSO, SAML and RBAC
Enterprise identity, role-based approval gates, and separation of duties between operations, quality and engineering.
Signed, versioned edge OTA
Models and runtimes ship as signed artefacts with staged rollout, instant rollback and twin-validated gating in CI.
The assurance graph
Recall defence, by construction.
From sensor frame to final outcome
Product specs, HACCP control points, sensor frames, model versions, autonomy level, approvals, overrides and outcomes are linked in one queryable graph. When a customer or regulator asks what happened to lot 4471, the answer is a query, not an archaeology project.
- Immutable, append-only action log
- Lot and carcass genealogy
- Model version and confidence per decision
- Approver identity and timestamp
Your recipes stay yours
Federated learning shares model improvements across the fleet without moving plant recipes, supplier data or tenant images. Cut programs, specs and species models are scoped to your tenant and never used to train another customer’s model.
- Per-tenant data and model scoping
- No cross-tenant retrieval
- Contractual IP protection
- On-prem option for the most sensitive producers
Compliance
Standards and frameworks we align to.
| Framework | Scope | Status |
|---|---|---|
| SOC 2 Type II | Security, availability, confidentiality | In progress [PLACEHOLDER] |
| ISO 27001 | Information security management | Planned [PLACEHOLDER] |
| HACCP | Food-safety control points and evidence | Aligned by design |
| USDA-FSIS | US inspection and record-keeping | Aligned by design |
| EU 853/2004 | EU hygiene rules for food of animal origin | Aligned by design |
| GDPR | Personal data of plant staff | Compliant, data minimised |
Safety engineering
The loop fails safe.
Independent stop paths
Blade, robot and line stops are hardwired and independent of the model server, the network and the cloud.
Confidence gating
Below threshold, the cell degrades to a safe state, escalates to a human, or routes product to rework. It never guesses.
Bounded envelopes
Every agent action is constrained to a validated motion, force and spec envelope that operations owns, not the model.
Deterministic timing
Perception and control budgets are measured continuously; a missed budget triggers degradation, not a late action.
Signed edge artefacts
Runtimes and models are signed, versioned and staged, with instant rollback under your change-control process.
Change control
Golden datasets, LLM-as-judge scoring and twin validation gate every model or prompt change before it can ship.
Review process
How a security review runs.
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1
Scope
We map the lines, sensors, systems and data flows in scope with your IT/OT and quality teams.
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2
Architecture review
Network segmentation, identity, edge deployment, data residency and stop-path independence are reviewed jointly.
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3
Validation
Twin validation protocols, model change control and evidence formats are agreed with quality and food safety.
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4
Sign-off
A documented pack — architecture, controls, validation and evidence — supports your internal and external audits.
Reliability
Availability and response targets.
4.1%
Average saleable-yield uplift on pilot deboning lines [PLACEHOLDER]
61%
Reduction in weight giveaway per fixed-weight pack
38 ms
Median foreign-material reject decision at the plant edge
99.9%
Plant-edge runtime uptime target with fail-safe line stop
Enterprise security
Controls your security team expects.
Dedicated SLAs and support
99.9% uptime target, named solutions engineers, on-site commissioning and 24/7 response aligned to your shift patterns.
On-prem and air-gapped options
Full plant-edge deployment with no outbound data requirement. Signed OTA updates via your own change-control process.
Assurance and validation packs
Documentation for HACCP, USDA-FSIS and EU audits: validation protocols, model change control and evidence trails.
Audit view
The evidence trail, live.
Saleable yield82.4%+4.1% vs baseline
Giveaway0.7%−61% this week
FM rejects120 escapes
Line uptime99.4%+2.2 pts
Line 4 · Front-half deboning1,412 /hr83.1% yieldAutonomous
Line 2 · Breast portioning2,980 /hr0.6% giveawayAutonomous
Line 7 · X-ray screening3,140 /hr4 rejectsAdvisory
Line 1 · Primal fabrication640 /hr78.9% yieldShadow
Illustrative console data from a pilot deboning line. [PLACEHOLDER]
Quality leaders
Why QA teams sign off.
“The line does not care that every bird is different — Slicium does. We stopped programming a machine and started supervising an operator that adapts to each carcass.”
“Giveaway was the quiet leak nobody could close. Watching the portioner hold target within a couple of grams, shift after shift, changed the economics of the whole pack line.”
“What sold my team was the audit trail. Every reject links back to the frame, the model version and who approved the autonomy level. That is what a recall investigation actually needs.”
Design-partner quotes are composite and pending publication approval. [PLACEHOLDER]
Identity
Fits your identity and workflow stack.
Plant systems
- MES and production monitoring
- OPC UA / Modbus / EtherNet-IP
- Historians and time-series stores
- ERP and order specs
Quality & food safety
- HACCP control points
- QMS and CAPA workflows
- Traceability and lot genealogy
- Sanitation and hygiene records
Identity & workflow
- SSO / SAML / SCIM
- Role-based approval gates
- Ticketing and on-call alerting
- Shift handover surfaces
Security FAQ
Questions from IT, OT and quality.
Slicium runs a graduated autonomy model: shadow, then advisory, then supervised autonomy, each gated by measured accuracy and twin validation. Below the confidence threshold the cell degrades to a safe state, escalates to a human, or routes the product to rework — it never guesses on a food-safety decision.
No. The perception and control loop runs entirely on the plant edge. Cloud is used for training, fleet management and reporting, and can be disabled for on-prem or air-gapped deployments. Federated learning shares model improvements without exposing plant recipes, supplier data or tenant images.
A typical pilot runs one line for 8–12 weeks: two weeks of integration and shadow-mode baselining, four to six weeks of advisory operation, then graduated autonomy against the agreed success metric. Connectors for common cutting, grading, X-ray, portioning and MES systems are pre-built. [PLACEHOLDER]
Cells are specified for cold, wet, IP69K washdown environments with daily caustic sanitation. Perception enclosures, cabling and edge compute are selected for condensation, temperature swing and high-pressure cleaning, and validated with your sanitation crew during commissioning.
Request the security and validation pack.
Architecture, controls, validation protocols and evidence formats — everything your auditors will ask for.