Spin-and-Yarn
Spinning, count, twist & yarn quality
Controls draft, twist and speed across ring, rotor and air-jet frames to hold count (Ne), CV%, twist and tenacity inside buyer spec, and predicts end-breaks before they cascade.
Products
Six products, one record of the truth
Vireon sees the fabric. Spindra, Loomix and Shadeon run the spinning, formation and dyeing stages. Doffex keeps the lines fed. Twinly simulates every run before it happens. They share one edge runtime, one genealogy and one audit log.
The ecosystem
One loop across the mill
Vireon is the perception layer every agent acts on. Spindra, Loomix and Shadeon own the sequential stages and pass genealogy downstream. Doffex is the handling layer. Twinly qualifies runs before production and pushes validated actions back to the line.
Vireon
Mill-edge vision that sees every defect on the roll before the buyer does.
Spindra
Autonomous spinning that holds count, twist and evenness, roll after roll.
Loomix
Autonomous weaving and knitting that stops the fault before the pick.
Shadeon
Right-first-time dyeing. The shade hits before the bath fills.
Doffex
Robotic hands for the mill: doffing, rolls and beams moved without operators.
Twinly
The as-produced fabric twin that hits quality, shade and takt before the run.
Product · Perception layer feeding every other agent
Vireon: Mill-edge vision that sees every defect on the roll before the buyer does.
Inspection is still the labour-heavy bottleneck of the mill. Human inspectors on greige and finished rolls miss slubs, holes, streaks, stains, floats, barré, skew and width faults at line speed, fatigue on night shifts, and disagree roll to roll. A missed defect becomes a second-quality roll, a re-dye or a buyer chargeback. An over-call scraps good fabric.
What it does
The closed loop on this stage
Line-scan and RGB/NIR cameras over inspection frames, looms, knitting machines and finishing ranges feed GPU segmentation and classification models that detect, localise and grade faults in real time, with a per-metre defect map, a severity grade and an immutable roll genealogy that Spindra, Loomix, Shadeon and Twinly all consume.
- Real-time line-scan and RGB/NIR detection, localisation and four-point grading
- Per-metre defect map with immutable roll genealogy
- Fibre- and construction-aware models for cotton, polyester, blends and technical textiles
- Human review, active-learning label capture and golden-set evaluation
- Feeds defect and shade events to Spindra, Loomix, Shadeon and Twinly
| Component | Role |
|---|---|
| Jetson Orin | Mill-edge inference on inspection frames and looms; Thor later ASPIRATIONAL |
| RTX / L4 edge servers | Multi-camera line aggregation and heavier models per cell |
| DeepStream + TensorRT | Line-scan video pipelines and low-latency inference |
| Metropolis + Holoscan | Vision application framework and sensor fusion with spectrophotometers, evenness meters and PLC events |
| Triton | Serves defect, shade and anomaly models per cell |
| DGX/HGX | Training on roll images ASPIRATIONAL |
Product · Spinning stage; publishes yarn genealogy downstream
Spindra: Autonomous spinning that holds count, twist and evenness, roll after roll.
Spinning fibre into yarn of consistent count, twist, strength and evenness drifts constantly with fibre lot, humidity and machine wear. Slubs, thick and thin places and count variation created at the frame propagate into weaving faults, barré and shade variation that only surface rolls later, as seconds and buyer rejects.
| Component | Role |
|---|---|
| Jetson Orin | Frame-edge inference for evenness and vision fusion |
| RTX / L4 edge server | Multi-frame aggregation and prognostics |
| TensorRT | Low-latency evenness and anomaly inference at the frame |
| Holoscan | Fuses evenness meters, tension and speed sensors and inline vision |
| Triton | Serves yarn-quality, drift and prognostics models |
| cuOpt | Spindle and lot assignment, doffing schedules under quality constraints |
What it does
The closed loop on this stage
Spindra fuses yarn-evenness meters, tension and speed sensors and inline vision with fibre-lot context to sense and predict count, twist and evenness drift and slub formation in real time, then recommends or, with graduated autonomy, applies draft, twist, speed and tension corrections at the frame.
- Real-time count, twist and evenness sensing with drift prediction
- Fibre-lot-aware draft, twist, speed and tension recommendations and closed-loop control
- Spinning-frame prognostics on drafting, spindles and rotors
- Doffing-waste and end-break reduction
- Publishes yarn-quality genealogy consumed by Loomix, Shadeon and Twinly
Product · Fabric-formation stage; consumes Vireon and Spindra, feeds Twinly and Shadeon
Loomix: Autonomous weaving and knitting that stops the fault before the pick.
Broken picks and ends, holes, floats, tension bands and barré form in milliseconds and run for metres before an operator reacts. Tension, speed and construction setpoints are craft-bound and machine-specific, and a skilled weaving and knitting workforce is scarce and cannot watch every machine.
What it does
The closed loop on this stage
Loomix fuses warp, weft or knit-loop tension, speed, stop events and inline vision from Vireon with construction specs to predict faults before they propagate, then recommends or applies tension, speed, let-off and take-up corrections at the loom or knitting machine.
- Real-time tension and construction fault prediction: picks, ends, holes, floats, barré
- Loom and knit setpoint recommendations and graduated closed-loop control
- Stop-cause analytics and predictive maintenance on looms and knitting heads
- Construction-spec-aware control per fabric style
- Consumes Vireon vision and Spindra yarn genealogy; feeds Twinly and Shadeon
| Component | Role |
|---|---|
| Jetson Orin | Loom and knit-edge inference for tension and vision fusion |
| RTX / L4 edge server | Many-loom aggregation and prognostics |
| Holoscan | Fuses tension, speed, stop events and camera streams into loom state |
| TensorRT | Sub-100 ms fault prediction per machine ASPIRATIONAL |
| Triton | Serves tension, fault and prognostics models per cell |
| cuOpt | Loom and style assignment, rework sequencing under delivery constraints |
Product · Dyeing and finishing stage; consumes upstream genealogy, feeds Twinly
Shadeon: Right-first-time dyeing. The shade hits before the bath fills.
Dyeing and finishing are the most chemistry-, water- and energy-hungry stages in textiles and the biggest source of rejects. Shade matching depends on scarce colourists, fixed recipes and spot lab checks. A shade miss forces a re-dye or scrap, wasting water, energy, chemicals and time, and triggers buyer chargebacks.
| Component | Role |
|---|---|
| RTX / L4 edge servers | Real-time spectral colour science and recipe inference |
| Jetson Orin | Dye-line-edge dosing and shade control, spectrophotometer fusion |
| CUDA + RAPIDS | GPU spectral and colour-science maths and recipe search |
| TensorRT + Triton | Low-latency shade and recipe inference, served per line |
| NeMo Retriever and Guardrails | Grounds colour and sustainability answers in OEKO-TEX, ZDHC and bluesign standards |
| cuOpt | Dye-lot sequencing and water and energy allocation |
What it does
The closed loop on this stage
Shadeon predicts dye recipes and spectral shade outcomes from substrate, fibre-blend and machine context, matches to the buyer standard under multiple illuminants, and drives adaptive dosing, temperature ramp and process correction toward right-first-time, cutting re-dyes, water, energy and chemistry.
- Spectral, multi-illuminant shade matching to buyer standards with metamerism control
- Dye-recipe prediction and adaptive dosing, temperature and ramp control
- Right-first-time optimisation: fewer re-dyes, less water, energy and chemistry
- Colourist craft captured as memory, with an assurance-grade sustainability audit trail
- Consumes fibre, yarn and construction genealogy from Spindra and Loomix; feeds Twinly
Product · Handling layer keeping every line fed at takt
Doffex: Robotic hands for the mill: doffing, rolls and beams moved without operators.
Mills are paced by heavy, repetitive, injury-prone material handling: doffing full packages off spinning frames, lifting and transporting greige and finished rolls, changing warp beams and feeding inspection and dye lines. The work is understaffed and a hidden bottleneck that starves autonomous lines of throughput.
What it does
The closed loop on this stage
Doffex is vision-guided mobile manipulation that doffs packages, grips and transports rolls and beams, and feeds spinning, weaving, knitting, inspection and dye lines. Policies are trained and validated in simulation, adapt to package and roll variety and mill layout, and synchronise with the line agents’ takt.
- Vision-guided doffing, roll and beam gripping, transport and line feeding
- Adapts to package size, roll weight and mill layout with sim-trained policies
- Takt-synchronised with Spindra, Loomix and Shadeon
- Safety-rated human-robot collaboration with a handling audit trail
- Simulation-first validation before any physical deployment
| Component | Role |
|---|---|
| Jetson Orin | On-robot perception, planning and control; Thor later ASPIRATIONAL |
| RTX / OVX | Isaac Sim training and digital-twin cells |
| Isaac Sim, ROS, Manipulator, Lab | Train, simulate and deploy handling policies |
| Omniverse + Replicator / Cosmos | Mill-cell twin for layout validation; synthetic package, roll and lighting variety |
| TensorRT | Optimised on-robot inference |
| DGX/HGX | Large-scale policy training ASPIRATIONAL |
Product · Optimisation brain over every product; qualifies runs before production
Twinly: The as-produced fabric twin that hits quality, shade and takt before the run.
Mills commit fibre, yarn, machine time, water, energy and chemicals to a run and only discover whether it hits quality, shade, hand and takt after the fabric is made. Dye-lot sequencing, line balancing and utility allocation are set by experience, and there is no way to test a change before the line runs it.
| Component | Role |
|---|---|
| OVX / RTX | Runs the Omniverse fabric-line twin and simulation |
| Omniverse + Replicator | Builds the as-produced twin and synthetic scenarios |
| cuOpt | Dye-lot sequencing, line balancing, water, energy and machine allocation |
| Cosmos | Rare production scenarios for robustness |
| Modulus | Physics-informed surrogates per process stage ASPIRATIONAL |
| Triton | Serves surrogate and prediction models |
What it does
The closed loop on this stage
Twinly builds an Omniverse-based twin of spinning, weaving, knitting, dyeing, finishing and roll flow, fed by real Vireon, Spindra, Loomix and Shadeon genealogy. It simulates a run to predict quality, shade, hand, takt, yield, water and energy, then optimises construction, recipe, sequencing, line balance and resources, and pushes validated actions back to the line agents.
- As-produced twin of spinning, weaving, knitting, dyeing, finishing and roll flow
- Pre-run prediction of quality, shade, hand, takt, yield, water and energy
- cuOpt optimisation: dye-lot sequencing, line balancing, water and energy allocation
- Action sandbox: test tension, dosing, speed and rework changes before the real line
- Twin-to-run qualification memory that improves with every simulated and real run
Shared platform
What every product runs on
Orchestrator
Agent orchestration
The mill orchestrator, the nine agents, the policy engine, the approval gates and the run record. This is the layer that decides and acts.
Genealogy
Roll-level record
Fibre to yarn to greige to dyed to finished roll, metre-indexed, shared by all six products.
Conformance
Evidence and audit
Hold and release decisions, buyer packets and the signed record of every autonomous action.
Mill edge appliance
Hardware
A GPU appliance that runs the loop locally and keeps running when the uplink is lost.
Console & HMI
Interfaces
A web console with a ⌘K palette for engineers, and a machine-side panel for operators who never open a laptop.
Shared models
Federated, isolated
Defect and shade datasets improve shared models across fibres, constructions and shades while each tenant’s data stays its own.
Agent graph
One run, ten steps, one human decision
This is the shape of a dye lot on Yarneon, shown as an illustrative scenario rather than a customer run. Ingest and simulation fan out, converge on a colourist approval gate, then dosing, verification, finishing, inspection and release. The accent traces the active path; every node opens in the inspector.
Scroll the graph sideways · or open the text equivalent below
SUCCEEDED APPROVAL FAILED RUNNING
Text equivalent, workflow steps, dependencies and status
| Step | Stage | Depends on | Status | Duration |
|---|---|---|---|---|
| ingest | conformance | none | SUCCEEDED | 0.8s |
| twin | simulate | ingest | SUCCEEDED | 46s |
| recipe | dye + colour | ingest | SUCCEEDED | 2.4s |
| approve | human gate | twin, recipe | APPROVAL | 4m 12s |
| dose | bath control | approve | SUCCEEDED | 118m |
| shade | verify ΔE | dose | SUCCEEDED | 9.1s |
| finish | stenter | dose | SUCCEEDED | 64m |
| inspect | vision | shade, finish | FAILED | 38m |
| rework | replan | inspect | SUCCEEDED | 1.6s |
| grade | release | rework | SUCCEEDED | 3.0s |
- Parallel branches2twin simulation and recipe prediction run together
- Human gates1colourist approval, 15 minutes, attributed
- Failures recovered1weft streak on roll 09, replanned in-run
Run timeline
RUN-4471 · Indigo poplin, 3,180 kg, due Thursday
The same scenario run as an ordered timeline: step, status, duration and the tool result behind it. Inspection failed on one roll, the run recovered, replanned the cut and still held the ship date.
RUN-4471
RUN COMPLETE
Scenario mill · reactive exhaust jet dyeing · illustrative run, not a customer deployment
Goal: Dye lot DL-4471 · 3,180 kg · 40s combed cotton poplin · shade Indigo 19-4028 TCX · ΔE ≤ 0.8 · due Thu 06:00
-
01 ingest.lot_state SUCCEEDED 0.8s
Pulls greige genealogy for 14 rolls: yarn lots, loom, greige GSM 138, absorbency and residual size from the prep line.
Agent, input and output
agent Quality-and-Conformance result ← 14 rolls · 3,180 kg · mean GSM 138.2 (σ 1.1) · prep OK -
02 twin.simulate_lot SUCCEEDED 46s
Omniverse fabric-line twin simulates the exhaust curve, machine loading and takt for three candidate recipes before a drop of dye is used.
Agent, input and output
agent Yield-and-Takt result ← 3 candidates scored · best predicted ΔE 0.52 · 118 min cycle -
03 dye.predict_recipe SUCCEEDED 2.4s
Spectral recipe model proposes a 3-dye combination against the buyer standard, corrected for this substrate’s absorbency and the current water hardness.
Agent, input and output
agent Dye-and-Color result ← 2.14% Navy RGB · 0.61% Blue BRF · 0.08% Black B · salt 62 g/L -
04 human.approve_recipe APPROVAL 4m 12s
Recipe deviates >5% from the standing card, so autonomy is capped: the colourist approves, rejects or edits before any dosing. Guardrail policy MILL-02/DYE-APPROVAL.
Agent, input and output
agent Dye-and-Color result → awaiting colourist · approved on shift 04:18 -
05 dye.control_bath SUCCEEDED 118m
Closed-loop dosing and ramp control against live bath spectrophotometry; two mid-cycle corrections applied when exhaustion ran 4% ahead of model.
Agent, input and output
agent Dye-and-Color result ← exhaust 96.4% · 2 corrections · bath ΔE 0.41 at drain -
06 shade.verify_lot SUCCEEDED 9.1s
Per-roll spectral read against Indigo 19-4028 TCX under D65/TL84/A; metamerism scored and rolls sorted into shade bands.
Agent, input and output
agent Shade-and-Quality result ← mean ΔE 0.58 · 13 rolls band A · 1 roll band B -
07 finish.control_stenter SUCCEEDED 64m
Stenter chemistry, overfeed and curing profile set to hold hand, 148 cm width and residual shrinkage under 3%.
Agent, input and output
agent Finish-and-Hand result ← width 148.3 cm · shrink 2.1% warp / 1.4% weft -
08 inspect.scan_rolls FAILED 38m
In-line vision flags a recurring 6 cm weft streak on roll 09 between 412 m and 445 m, traced to a stenter pin-chain slip, not a dye fault.
Agent, input and output
agent Defect-and-Inspect result ← 1 defect cluster · roll 09 · 33 m affected · class WEFT_STREAK -
09 plan.rework_route SUCCEEDED 1.6s
cuOpt re-plans the cut and rework route: 33 m diverted to seconds, remaining 14,890 m re-sequenced so the buyer’s Thursday ship date still holds.
Agent, input and output
agent Yield-and-Takt result ← 33 m to seconds (0.22%) · ship date held -
10 quality.grade_and_release SUCCEEDED 3.0s
Four-point grading, roll genealogy and the conformance packet (AATCC 61, ISO 105-C06, ZDHC MRSL declaration) are assembled and released to the buyer portal.
Agent, input and output
agent Quality-and-Conformance result ← 13 rolls Grade A · 1 roll Grade B · packet signed
RUN OUTCOME
Lot released first time, on shade, on date.
| Measure | Value | Context |
|---|---|---|
| Final mean ΔE | 0.58 | against a 0.80 tolerance |
| Re-dyes avoided | 1 | the standing card would have missed shade |
| Seconds | 0.22% | versus the scenario mill baseline of 1.9% |
| Water used | 46 L/kg | versus 59 L/kg on the scenario recipe card |
| Human decisions | 1 | the recipe approval gate |
Why this matters
A mill does not fail on the good lots. It fails on the lot where the substrate drifted, the recipe card was wrong, and nobody found out until the buyer opened the carton. Yarneon makes that lot legible while it is still in the machine.
The agent roster
Nine agents, one mill orchestrator
Each agent owns a stage of the mill, senses its own signals and actuates its own setpoints. The orchestrator plans across them, escalates on policy, and keeps one record of the whole run.
Weave-and-Knit
Loom & knitting-machine control
Holds warp and weft tension, pick density, let-off and take-up on air-jet, rapier and circular-knit machines so construction stays on spec without broken picks, ends-out, floats or holes.
Dye-and-Color
Dyeing chemistry, recipe & shade
Predicts and doses dye recipes from substrate state, then closes the loop on exhaust curves, temperature ramps, pH and salt so the lot lands on shade first time instead of after two re-dyes.
Finish-and-Hand
Finishing chemistry, hand & stability
Controls stenter chemistry, overfeed, residence and temperature to hit hand, GSM, width and dimensional stability, with shrinkage and skew held to buyer tolerance across the roll.
Defect-and-Inspect
Vision fabric-defect sensing
Line-scan and NIR vision detects and classifies slubs, holes, streaks, stains, floats, barré, skew and width faults in-line at full loom and stenter speed, then maps every fault to roll position.
Shade-and-Quality
Colour, fastness & grade optimisation
Spectral models score every roll against the buyer standard (ΔE, metamerism, fastness risk) and sort rolls into shade bands so cutting rooms never mix two shades in one garment.
Yield-and-Takt
Yield, waste, water, energy & balancing
Sequences dye lots and balances the line against takt, then allocates water, steam and electricity to cut the mill’s two biggest costs after fibre, reprocessing and utilities.
Robot-and-Handling
Roll, beam & doffing automation
Drives doffing, beam changes and roll transport with vision-guided manipulators and AMRs, so the scarce labour on the floor moves from lifting rolls to supervising the run.
Quality-and-Conformance
Right-first-time, genealogy & traceability
Keeps immutable roll genealogy from bale to bolt and assembles the conformance packet, test methods, chemistry declarations and audit trail, that buyers and auditors demand.
Text equivalent
What each agent senses and actuates
The same roster as a table, because an agent that will move a setpoint on your machine should be legible in plain rows before it is legible in a diagram.
| Agent | Senses | Actuates | Metric watched |
|---|---|---|---|
| Spin-and-Yarn | Evenness (Uster CVm%) · Imperfections IPI /km · Twist per inch · End-break rate · Roving/draft state | Draft ratio · Spindle speed · Twist multiplier · Doffing schedule | Watches: yarn IPI and CV% variance |
| Weave-and-Knit | Warp tension curve · Pick/course density · Stop causes · Loom efficiency % · Beam depletion | Let-off / take-up · Machine speed · Tension setpoints · Stop-and-repair routing | Watches: loom stops and construction faults |
| Dye-and-Color | Bath spectrophotometry · Exhaustion curve · Liquor ratio, pH, conductivity · Temperature ramp | Dosing schedule · Ramp rate & hold · Salt/alkali addition · Sampling & release | Watches: right-first-time shade |
| Finish-and-Hand | GSM, width, overfeed · Residual shrinkage · Handle/stiffness proxy · Curing temperature profile | Pad-bath concentration · Overfeed & pin width · Line speed · Curing profile | Watches: shrinkage and width out of tolerance |
| Defect-and-Inspect | Line-scan RGB + NIR frames · Defect class & severity · Metres between faults · Roll position map | Stop / slow line · Cut-plan marking · Rework routing · Grade assignment | Watches: defect escape rate |
| Shade-and-Quality | ΔE 2000 vs standard · Metamerism index · Fastness test history · Shade band assignment | Shade banding · Release / hold / re-dye · Buyer submission packet | Watches: shade-related chargebacks |
| Yield-and-Takt | Takt vs actual per stage · Litres water / kg fabric · kWh & steam per lot · Seconds & waste % | Dye-lot sequence · Machine assignment · Rework queue · Utility allocation | Watches: water and steam per kg |
| Robot-and-Handling | Roll/beam pose estimate · Gripper force feedback · AMR fleet state · Handling queue depth | Doff & beam-change cycles · Roll transport moves · Package palletising | Watches: manual handling hours |
| Quality-and-Conformance | Roll genealogy graph · Non-conformance records · AATCC/ISO test results · Chemistry declarations | Hold / release decisions · CAPA creation · Buyer & audit packet export | Watches: audit packet assembly time |
Trust signals
What the runs actually produce
No customer results are published yet. These are platform facts and plan terms from our own documents. Outcomes will be measured against each mill’s own trailing twelve months, in shadow mode before anything is controlled.
9
Mill agents, one per stage, from spinning to release.
6
Products in the loop: Vireon, Spindra, Loomix, Shadeon, Doffex and Twinly.
3 to 5
Design partners we are onboarding first, one wedge workflow each.
$14k
Per line per month on the Line plan. Mill and Enterprise sit above it.
Items marked ASPIRATIONAL are design targets ahead of production validation.
Integrations
It speaks to the machines you already own
Yarneon is not a rip-and-replace. It connects to the looms, frames, jets, stenters, cameras, spectrophotometers and MES already on your floor.
Loom & knit controllers
Picanol, Toyota, Tsudakoma, Karl Mayer and Mayer & Cie controllers over OPC UA and vendor PLC tags.
Spinning frames
Rieter, Trützschler, Saurer and Murata frames, draft, twist, speed and end-break telemetry.
Dyeing & finishing
Thies, Fongs, Brazzoli jets and Monforts/Brückner stenters via PLC, recipe systems and dosing units.
Colour & lab
Datacolor and X-Rite spectrophotometers, colour libraries, Pantone TCX standards and lab-dip workflows.
Inspection hardware
Line-scan RGB and NIR cameras, Uster and Elbit inspection frames, existing light boxes.
MES / ERP
SAP, Datatex, TIM, Coats Digital and homegrown mill MES over REST, files and database CDC.
Utilities & sustainability
Water, steam and electricity meters; ZDHC Gateway, Higg FEM and OEKO-TEX reporting.
Robotics
Vision-guided manipulators and AMRs on NVIDIA Isaac and Jetson for doffing, beams and roll transport.
Vendor names are listed for compatibility reference only and do not imply endorsement or partnership.
Guardrails
An agent earns the right to touch a machine
Nothing here is a global "AI on" switch. Autonomy is granted per setpoint, bounded by policy, reversible by any operator and logged permanently.
- Graduated autonomy
- Every workflow moves observe → assist → bounded auto-control. Autonomy ceilings are per-setpoint policy, not a global switch.
- Human-in-the-loop gates
- Approval gates fire on deviation thresholds, new substrates, or any action outside the authorised envelope. Approvals are attributed and time-stamped.
- Reversibility
- Every control action ships with a revert path and a last-known-good setpoint. Operators can take manual control at any moment, from the HMI or the panel.
- Immutable audit log
- Assurance-grade, append-only record of every observation, decision, tool call, approval and actuation, exportable for buyer and regulatory audit.
- Tenant isolation
- Recipes, construction libraries and roll data are isolated per tenant. No cross-tenant training. Permission-aware retrieval with enforced citations.
- Sandboxed tools
- Agents call machines through a typed, scoped tool layer with rate and range limits. There is no path from a model output to an unbounded PLC write.
Pricing
Land on one line. Expand across the mill.
Priced per line, per mill or per group, with outcome-based components on the workflows where the value is measurable.
Line
Mills validating ROI on a single wedge workflow.
- One agent workflow on one line, yarn/fabric control, dyeing, or inspection
- Mill-edge inference appliance and connector for that line
- Run timeline, tool-call log and immutable audit trail
- Assist mode with human approval on every control action
- Standard email and shared-channel support, 1 business-day response
Mill
Full loopScaling mills adopting the full perceive–decide–act loop.
- All nine agents: spin, weave/knit, dye, finish, defect, shade, yield/takt, robotics, conformance
- As-produced fabric digital twin with pre-run simulation
- Graduated autonomy with per-workflow approval policies and spend limits
- Mill-edge fleet management and offline fallback control
- Roll genealogy, buyer conformance packets and sustainability reporting
- Named mill engineer and quarterly outcome review
Enterprise
Integrated textile groups standardising on Yarneon.
- Multi-site deployment with group-level benchmarking
- Custom fibre, construction and shade models trained on your archive
- On-prem or private-VPC deployment via NVIDIA AI Enterprise
- SSO, SCIM, RBAC, data residency and signed SLAs
- Outcome-based commercial components on yield, seconds, re-dyes and utilities
- Dedicated solutions team and 24×7 support
Annual prepay saves 15 to 20% depending on term. Full detail, including outcome-based terms, on the pricing page.
Questions
What mills ask before they let an agent near a jet
Both, in that order. Every workflow starts in observe mode, graduates to assist (the agent proposes, a human commits), and only then to bounded auto-control on the specific setpoints you authorise. Autonomy ceilings, approval gates and spend limits are policy objects you own, and every action is reversible and logged.
The control loop lives at the mill edge. Inference, guardrails and the audit log run locally on the edge appliance, so a lost uplink degrades reporting and retraining, not machine control. Buffered telemetry syncs when the link returns.
Design partners start with one wedge line in shadow mode: connectors and telemetry first, then models scored against what the mill actually produced, then assist mode where the agent proposes and an engineer approves. Whole-mill rollout follows once the wedge holds its numbers. Durations depend on how instrumented the mill already is, so we quote them after the assessment, not before.
To predict recipes well, yes, and that IP never leaves your tenant. Retrieval is multi-tenant isolated, models fine-tuned on your data are yours, and on-prem deployment is available for groups that will not put recipes in any cloud.
A Jetson-class edge device per inspection or control cell, one GPU server per mill for multi-model serving, line-scan cameras where in-line inspection is in scope, and a spectrophotometer feed for colour work. We survey the existing fleet first, most mills already have more sensing than they use.
Walk the products on your floor
Bring your machine list and your defect history. We will show you exactly which product touches which line.
