Tintra
Hit the color standard within Delta-E, first time, without the lab loop.
agent.tint_color
Products
Buy the stage that hurts. Add the rest when it pays.
Six products, one plant-edge runtime, one audit and genealogy backbone, one data flywheel. Dispex grinds the mill base, Rheon lets it down to spec, Tintra tints it to the standard, Specton is the shared perception layer feeding every module, Palleon filters, fills and handles the finished product, and Coatwin simulates every decision before the batch runs.
Illustrative scenario: Plant run · one architectural deep tint base from dosing to pallet · bead mill, let-down tank, tint station, filling line. Not a measured run.
The ecosystem
Six products, one loop
These are the stages of one dose, disperse, let-down, tint, fill and inspect loop plus the twin that plans it, not separate bets. They share the plant-edge runtime, the spectral and vision stack, the quality governance, the control connectors and one compounding flywheel.
Dispex
Disperse to exact fineness and color development, first pass, every batch.
agent.dose_disperse
Rheon
Let down and thin to exact viscosity and rheology, no drift, no rework.
agent.letdown_thin
Specton
See color, contamination and fill faults the instant they happen, not in the lab.
agent.defect_inspect
Palleon
Filter, fill and handle every drum, pail and tote, clean, exact and hands-free.
agent.filter_fill
Coatwin
Hit target color, rheology and takt before the batch ever runs.
agent.orchestrator
Color-match wedge · agent.tint_colorTintra
Hit the color standard within Delta-E, first time, without the lab loop.
The problem
Color match is the most punishing step in a paint plant. A batch must land on a customer standard within a tight Delta-E, so tinting means adding colorant, pulling a draw-down, reading a spectrophotometer and adding again, a manual loop that burns time, colorant and a scarce color-matcher's judgment. Miss the tolerance and the batch gets re-tinted, held or rejected. Waterborne and low-VOC systems make color harder still, and the color-matchers who carry the craft are retiring faster than plants can replace them.
What Tintra does
Tintra is Tinteon's autonomous tint-and-color module. It controls tinting and colorant dosing and drives spectrophotometric color-match to hit the standard within Delta-E on the first pass. From the batch's spectral curve and the target standard it predicts the exact colorant additions, sequences them with retint limits and converges to tolerance while learning each colorant system's behavior. It encodes the color-matcher's craft as a model that improves with every match.
Key features
- Spectral color-match prediction and colorant-dose recommendation to a standard
- Autonomous tint sequencing with retint and additive limits
- First-time-right Delta-E targeting with live convergence
- Per-colorant-system models across waterborne, solvent and powder
- Cited, auditable color decisions with human approval gates
AI capabilities
| Capability | Status |
|---|---|
| Spectral color-match prediction and colorant-dose optimization | design scope |
| Autonomous tint sequencing under tolerance and retint limits | staged, assist first |
| Grounded color-standard retrieval with citations | design scope |
| Per-formula color response and physics-informed colorant curves | planned |
NVIDIA stack
Jetson Orin (Thor planned) for edge spectral inference and dispenser control per line; TensorRT for low-latency color-match scoring; Holoscan and DeepStream to fuse spectrophotometer and draw-down camera streams; cuOpt to sequence colorant additions and batch color families; NeMo, Retriever and Guardrails for grounded reasoning over color standards; Triton and NIM to serve spectral and color-reasoning models; DGX/HGX for training (planned).
- For
- Architectural tint-base and in-plant tinting operations, automotive OEM and refinish color, industrial and coil color-matching; color-matchers and formulation engineers who own Delta-E and retint rate.
- Price
- $14,000 per tinting line per month, expanding to the Plant tier; outcome pricing on measured retint and colorant-waste reduction.
- First release
- Spectral color-match prediction and colorant-dose recommendation in assist mode on one tint line, measuring baseline Delta-E first-time-right and retint rate; then autonomous tint sequencing within tolerance.
- In the loop
- Consumes Dispex mill bases, shares the spectral stack with Specton, and has every match pre-validated in the Coatwin twin.
Dispersion wedge · agent.dose_disperseDispex
Disperse to exact fineness and color development, first pass, every batch.
The problem
Pigment dispersion and milling set the ceiling for a coating's color, gloss, hiding power and stability, yet they stay craft-bound. Operators pick mill energy, bead and media load, temperature and residence time by feel, then discover over- or under-dispersion at the Hegman gauge or in the lab. Fineness drift forces re-milling, wastes energy and media, and produces off-color and low-hiding rejects. The formulators who read a mill base by eye are retiring, and no two mills behave the same.
What Dispex does
Dispex is Tinteon's autonomous dose-and-disperse module. It controls raw-material dosing, dispersion and milling in a closed loop, regulating mill energy, media, temperature and residence to hit target fineness and color development without over- or under-grinding. It predicts fineness and color strength from spectral, power and process signals during the grind, corrects setpoints live and learns each mill's behavior batch after batch. Every formulator correction becomes labeled training data.
Key features
- Closed-loop mill-energy, media, temperature and residence control
- Live fineness (Hegman) and color-development prediction during the grind
- Per-mill behavioral models that adapt to equipment and pigment system
- Over- and under-dispersion risk scoring with early re-grind avoidance
- Human-in-the-loop approval with graduated autonomy and audit trail
AI capabilities
| Capability | Status |
|---|---|
| Multimodal fineness and color-strength prediction from spectral, power and time-series signals | design scope |
| Dispersion setpoint recommendation and closed-loop control | staged, assist first |
| Over- and under-dispersion risk scoring | design scope |
| Physics-informed pigment-dispersion-energy models | planned |
NVIDIA stack
Jetson Orin (Thor planned) at the mill for spectral, power and vision streams at 50 to 150 ms; TensorRT for edge scoring of fineness, color and anomaly models; Holoscan and DeepStream to fuse spectrophotometer, temperature and mill-power streams; RAPIDS for feature generation over mill telemetry; Modulus for physics-informed dispersion surrogates (planned); Triton and NIM to serve the models; DGX/HGX for training (planned).
- For
- Architectural, automotive, industrial, coil, powder and specialty coatings makers running bead, basket and horizontal mills; formulation and process engineers who own dispersion windows and mill yield.
- Price
- $14,000 per dispersion line per month, expanding to the Plant tier; outcome pricing on measured re-mill and energy reduction.
- First release
- Advisory fineness and color prediction on one mill in shadow mode, measuring baseline re-mill and energy; then assist setpoint recommendations, then closed low-risk mill-energy control.
- In the loop
- Owns the first stage of the loop; its mill base feeds Rheon and Tintra, and every grind is validated in the Coatwin twin before the run.
Let-down and rheology · agent.letdown_thinRheon
Let down and thin to exact viscosity and rheology, no drift, no rework.
The problem
After dispersion, a coating is let down and thinned to hit exact solids, viscosity and rheology, because how the paint flows decides how it applies, sags, levels and stores. Operators chase the spec by adding solvent or resin and rechecking on a bench viscometer, a slow loop that overshoots, wastes solvent and drifts batch to batch. Waterborne and high-solids systems are more sensitive still, and a rheology fault degrades application and stability long after the batch leaves the plant.
What Rheon does
Rheon is Tinteon's letdown-and-thin and rheology-control module. It controls let-down, thinning, solids and viscosity in a closed loop, reading inline rheology and predicting viscosity and rheological behavior to converge on spec without overshoot. It manages stability and batch quality across temperature and shear, cuts solvent use and rework, and learns each formula's rheology response so it hits the target with the fewest possible additions.
Key features
- Closed-loop let-down, thinning and solids control to a rheology spec
- Inline viscosity and rheology prediction with live convergence
- Stability and shear and temperature behavior modeling
- Solvent and resin addition minimization to cut waste and VOC
- Human approval gates with graduated autonomy and full audit trail
AI capabilities
| Capability | Status |
|---|---|
| Inline viscosity and rheology prediction and let-down setpoint optimization | design scope |
| Closed-loop thinning and solids control | staged, assist first |
| Stability risk scoring | design scope |
| Physics-informed rheology models coupling shear, temperature and formula | planned |
NVIDIA stack
Jetson Orin (Thor planned) for edge inference on inline rheology and process streams per line; TensorRT for low-latency viscosity scoring at the let-down stage; Holoscan and DeepStream to fuse inline rheology, temperature, solids and mix-power streams; RAPIDS for rheology and stability features; Modulus for physics-informed rheology surrogates (planned); Triton and NIM to serve rheology and time-series models; DGX/HGX for training (planned).
- For
- Coatings makers running let-down and thinning stages across architectural, automotive, industrial, coil and high-solids and waterborne systems; process engineers who own viscosity, solids and stability specs.
- Price
- $14,000 per line per month inside the Line tier, expanding to the Plant tier; outcome pricing on measured solvent and rework reduction.
- First release
- Inline viscosity and rheology prediction in shadow mode on one let-down line, measuring baseline solvent use and rework; then assist let-down recommendations, then closed low-risk thinning control.
- In the loop
- Owns the let-down stage between Dispex and Tintra, carries the Quality-and-Rheology agent, and has its moves validated in the Coatwin twin.
Shared perception layer · agent.defect_inspectSpecton
See color, contamination and fill faults the instant they happen, not in the lab.
The problem
Quality in a paint plant is judged too late. Color, gloss, hiding power and fineness get checked by spot lab draw-downs, while contamination, seeds, foam and fill and label faults surface at filling or, worse, at the customer. By then a bad batch is already made, filled and labeled, and the plant eats re-tinting, rejects and complaints. Inspection is manual, sampled and reactive, and the inspectors and color-matchers who catch faults by eye are in short supply.
What Specton does
Specton is Tinteon's defect-and-inspect module: real-time spectral and vision inspection across the plant. It fuses spectrophotometer, line-scan, RGB and, when available, hyperspectral streams to sense and predict color, gloss, hiding power, fineness, contamination, seeds, foam and fill and label faults inline, scoring every batch and container as it moves. It flags off-color and off-spec risk early enough to hold or correct, and feeds labeled faults back into the color, dispersion and rheology models across the ecosystem.
Key features
- Inline spectral and vision inspection for color, gloss, hiding power and fineness
- Contamination, seed, foam and fill and label fault detection and prediction
- Early off-color and off-spec risk scoring with hold recommendations
- Immutable, assurance-grade quality audit trail per batch and container
- Labeled-fault feedback that trains Dispex, Tintra and Rheon
AI capabilities
| Capability | Status |
|---|---|
| Fine-tuned color, gloss, hiding-power and contamination vision and spectral models | design scope |
| Fill, label, seed and foam fault detection | design scope |
| Off-spec risk prediction from fused spectral and vision signals | design scope |
| Hyperspectral sensing and synthetic rare-fault augmentation | planned |
NVIDIA stack
Jetson Orin (Thor planned) for 8 to 24 camera and sensor streams per line at 50 to 150 ms per frame; Metropolis and DeepStream for multi-camera inspection pipelines; Holoscan for spectrophotometric and hyperspectral fusion; TensorRT for low-latency inspection and anomaly scoring; Cosmos and Omniverse Replicator to synthesize rare off-color, seed, contamination and fill faults (planned); Triton and NIM to serve vision and spectral models; DGX/HGX and IGX dev kits for training and high-rate ingestion.
- For
- Coatings makers running dispersion, tinting, filtration and filling lines who need inline color and contamination assurance; quality and compliance managers who own conformance and traceability.
- Price
- $14,000 per inspected line per month, expanding to the Plant tier; outcome pricing on measured contamination and fill reject reduction.
- First release
- Inline color, contamination and fill inspection on one line in shadow mode, measuring baseline rejects and complaints; then control-linked holds and labeled-fault feedback to the control modules.
- In the loop
- The shared perception layer: its inline signals drive Dispex, Tintra, Rheon and Palleon, and its labeled faults train the Coatwin twin.
Physical close of the loop · agent.filter_fillPalleon
Filter, fill and handle every drum, pail and tote, clean, exact and hands-free.
The problem
The back end of a paint plant is heavy, repetitive and error-prone. Coatings must be filtered free of seeds and contamination, filled to exact weight without foam or spills, and moved as drums, pails, totes and pallets, work that still leans on scarce operators lifting and staging containers by hand. Contamination, fill-weight and label faults drive rejects and complaints, and the manual handling caps line takt while injuring a workforce the plant cannot replace.
What Palleon does
Palleon is Tinteon's filter-and-fill and robotic-handling module. It controls filtration and filling to exact weight without contamination or fill faults, and drives robotic drum, pail, tote and packaging handling that moves and positions containers and packs. It coordinates filling holds with Specton's inline inspection, balances filling-line takt and closes the physical loop from clean fill to palletized, labeled, traceable product, with safety-gated robots that act in the plant.
Key features
- Closed-loop filtration and exact-weight filling without contamination or foam
- Robotic drum, pail, tote and pallet handling and packaging
- Filling-line takt balancing and line-side replenishment
- Inspection-linked holds coordinated with Specton
- Safety-gated autonomy: action envelopes, approvals and rollback
AI capabilities
| Capability | Status |
|---|---|
| Fill-fault, contamination and fill-weight detection | design scope |
| Robotic perception and grasp and place for drums, pails and totes | staged; complex packs planned |
| Takt and line-balancing optimization | design scope |
| Simulation-validated robot motion before deployment | planned |
NVIDIA stack
Jetson Orin (Thor planned) for on-robot perception and edge control in handling cells; IGX and Holoscan dev kits for safety-grade sensor ingestion at the filling line; Isaac ROS, Isaac Sim and Isaac Lab for handling and sim-to-real policies; Metropolis, DeepStream and TensorRT for fill-level, contamination and label vision; cuOpt for filling-line takt and replenishment; Omniverse and Cosmos for robot-cell twins and synthetic handling scenarios (planned); Triton and NIM to serve the models; Fleet Command for edge robot and model fleets (planned).
- For
- Coatings makers running filtration, filling and packaging lines with drum, pail and tote handling; operations directors who own filling takt, fill accuracy, contamination and labor safety.
- Price
- $14,000 per filling line per month, expanding to the Plant tier and enterprise multi-site robot fleets; outcome pricing on measured reject and takt improvement.
- First release
- Exact-weight filling with inline contamination and fill inspection and one constrained pail and drum handling cell in assist mode; then multi-cell robotic handling after safety validation.
- In the loop
- Closes the physical end of the loop after Dispex, Rheon and Tintra, coordinates holds with Specton, and has its cells laid out and validated in the Coatwin twin.
Keystone digital twin · agent.orchestratorCoatwin
Hit target color, rheology and takt before the batch ever runs.
The problem
Every new formula, color or grade change is a gamble made on the running line, the most expensive place to learn. Plants commit dispersion energy, let-down moves and tint additions, then discover off-color, off-rheology or off-takt results after the batch is made. There is no way to test a batch before committing raw materials and line time, and sequencing color families and changeovers across a plant wastes solvent, energy and hours.
What Coatwin does
Coatwin is Tinteon's as-made batch digital twin and the keystone of the ecosystem. It is a GPU-accelerated simulation of dispersion, let-down, tinting and color development that evaluates candidate recipes and predicts as-made Delta-E, rheology and takt before the run. It validates every Dispex, Rheon, Tintra and Specton decision in simulation, auto-optimizes the dispersion, let-down and tint path to the target, and sequences batches and changeovers across the plant for minimum waste and downtime.
Key features
- As-made twin of dispersion, let-down, tinting and color development
- Pre-run recipe evaluation with predicted Delta-E, rheology and takt
- Auto-optimization of dispersion, let-down and tint paths to the target
- Color-family batch and changeover sequencing across the plant
- Central validation and simulation service for every Tinteon module
AI capabilities
| Capability | Status |
|---|---|
| Recipe auto-optimization against predicted color, rheology and takt | design scope |
| GPU-accelerated spectral color-match prediction and dispersion and rheology simulation | design scope; parts planned |
| Color-family batching and changeover sequencing | design scope |
| Physics-informed color, dispersion and rheology surrogates paired with real batch telemetry | planned |
NVIDIA stack
DGX and OVX to run the Omniverse twin and the dispersion, rheology and color simulation; H100 and HGX to train physics-ML surrogates on batch genealogy and spectral telemetry; RTX workstations for twin authoring and engineering review; Omniverse as the coatings-line twin environment; Modulus for physics-informed surrogates (planned); cuOpt for color-family batching, changeover, solvent, energy and takt sequencing; Cosmos and Omniverse Replicator for synthetic rare-fault scenarios; Omniverse Cloud and NVIDIA AI Enterprise with NIM for scalable simulation and governed serving (planned).
- For
- Multi-color, multi-formula and specialty coatings makers with frequent color and grade changes; engineering and technology teams standardizing color and rheology across plants.
- Price
- Premium module in the Plant tier at $88,000 per plant per month and in Enterprise agreements; per-plant twin plus multi-site custom formula, color and rheology model contracts from $650k to $8.5M ACV.
- First release
- Advisory twin for one line simulating dispersion, tint and color for color and grade changes; then closed pre-run validation feeding Dispex, Rheon, Tintra and Specton.
- In the loop
- The shared simulation and optimization brain: it validates and sequences every other module, and the Plant Orchestrator rehearses high-impact moves on it before they reach a line.
Run timeline
The products in one run
Every Tinteon run is an ordered, inspectable sequence. This is run_scn_01, an illustrative scenario: Plant run · one architectural deep tint base from dosing to pallet · bead mill, let-down tank, tint station, filling line. Scenario complete · batch inside spec · one human approval at the tint station.
run_scn_01
scenario · not measured
SUCCEEDED
-
01
order.receive
SUCCEEDED
0.8 s
Plant Orchestrator · Pulled the formula, the customer color standard and its tolerance, the viscosity and solids spec, the raw-material lot records and the product's VOC limit from the coatings MES and the lab system; locked the target envelope for the run.
-
02
twin.simulate
SUCCEEDED
41 s
Plant Orchestrator · Simulated 24 candidate dispersion, let-down and tint paths on the Coatwin as-made twin; ranked them on predicted Delta-E, fineness margin, viscosity, solvent use, energy and takt, and discarded every candidate that moved outside the customer tolerance or the VOC limit.
-
03
disperse.mill
SUCCEEDED
1 h 48 m
Dose-and-Disperse · Held mill energy, media temperature and residence to the predicted fineness curve from mill power and spectral reflectance, trimming inside the formula window instead of grinding to a fixed time and checking the Hegman gauge afterward.
-
04
letdown.thin
SUCCEEDED
26 m
Letdown-and-Thin · Predicted viscosity from inline rheology, temperature and solids during let-down and converged on spec with two resin additions and one solvent addition instead of the standing four, inside the formula window; no stability risk was flagged.
-
05
tint.match
SUCCEEDED
14 m
Tint-and-Color · Read the batch's spectral curve against the customer standard, predicted the colorant additions and dosed the first pass; the draw-down read inside tolerance on Delta-E after one addition, with one retint still available under the declared limit.
-
06
inspect.spectral
SUCCEEDED
continuous
Defect-and-Inspect · 12 camera and spectral streams at the plant edge: color, gloss, hiding power, fineness and seed checks on the batch, fill-weight and label checks on every pail; two seeds were attributed to one filter cartridge and Filter-and-Fill scheduled the change.
-
07
approve.human
APPROVAL
2 m 10 s
Plant Orchestrator · The lowest-solvent candidate wanted a second colorant addition beyond the declared retint limit to tighten Delta-E further. Held for the shift color-matcher, who kept the customer tolerance untouched and approved one bounded addition with a tighter draw-down check.
-
08
filter.fill
SUCCEEDED
continuous
Filter-and-Fill · Filtered through the fresh cartridge and filled pails to exact weight using fill-weight and foam feedback from inspection; the filler corrected upstream instead of rejecting downstream.
-
09
handle.palletize
SUCCEEDED
continuous
Robot-and-Handling · Moved filled pails to the pallet inside the declared safety zone with a simulation-validated handling policy; one pallet-pattern change was executed after the zone check cleared.
-
10
release.genealogy
SUCCEEDED
58 s
Quality-and-Conformance · Batch released: raw-material lots, grind profile, let-down moves, colorant additions and spectral curves, inspection outcomes, VOC and solvent use and every human decision written to the batch genealogy and checked against spec.
Compare
What is in each plan
Modules are licensed per line on the Line tier and bundled on Plant and Enterprise.
| Capability | Line | Plant | Enterprise |
|---|---|---|---|
| Lines covered | 1 | All on site | All in group |
| Agent modules | 1 of 10 | All 10 | All 10 + custom models |
| Coatwin twin | Not included | Included | Custom twin formats |
| Plant-edge node | Included | Per line | Fleet managed |
| Guarded PLC and dispenser writes | Scoped tags | All scoped tags | Group policy |
| Batch genealogy | Included | Included | Included + export |
| Autonomy stages | Shadow, assist, bounded | Shadow, assist, bounded | Shadow, assist, bounded |
| Deployment | Plant edge + cloud | Plant edge + cloud | On-prem or private cloud |
| Outcome pricing | On request | Available | Standard |
| Indicative price | $14,000 / mo | $88,000 / mo | $650k – $8.5M ACV |
Tool calls
One log, every product
Every tool invocation, argument and result is written to an immutable, human-readable log, and every reasoning step is expandable. Nothing about a run is hidden from the plant. The log below is the scenario run, not a measured one.
- 05:40:02mes.read_order({ batch: "B-4471", product: "TB-DEEP-07", standard: "STD-2210" })
- 05:40:02ok formula locked · tolerance Delta-E v4 · VOC limit on product
- 05:40:03lab.read_results({ lot: "PIG-8831", test: "incoming pigment" })
- 05:40:03ok lot inside spec · accepted for dosing
- 05:40:04twin.simulate({ candidates: 24, horizon: "batch" })
- 05:40:45ok best path #9 · tolerance held · lowest solvent and energy per batch
- 05:40:46policy.evaluate({ plan: 9, stage: "bounded" })
- 05:40:46ok 7 writes permitted · 1 write requires human approval
- 05:40:47plc.write_setpoint({ tag: "MILL2.ENERGY", basis: "power+spectral" })
- 07:28:30ok Hegman on target · color strength on target · no re-mill
- 07:29:00viscosity.predict({ tank: "LD-3", basis: "inline rheology+solids" })
- 07:29:00ok two resin and one solvent addition predicted · stability clear
- 07:29:01plc.write_setpoint({ tag: "LD3.SOLVENT_DOSE", window: "formula" })
- 07:55:10ok viscosity on spec · no overshoot
- 07:56:00spectro.read_curve({ station: "TINT-2", standard: "STD-2210" })
- 07:56:01dispenser.write({ colorant: "B", basis: "spectral prediction", retint_limit: 1 })
- 08:10:12ok draw-down inside Delta-E tolerance · one retint remaining
- 08:10:13vision.stream({ cameras: 12, models: ["color_gloss", "hiding_power", "seed_foam", "fill_label"] })
- 08:21:48flag: seed · pail 0417 · attributed to filter cartridge F-2 loading
- 08:21:49defect.attribute({ event: "seed", cause: "filter.cartridge_F2" })
- 08:21:49ok filter_fill notified · cartridge change scheduled · fill held 40 s
- 08:21:52approval.request({ action: "retint.beyond_limit", reason: "tighter Delta-E on lowest-solvent path" })
- 08:24:02ok approved by the shift color-matcher · tolerance untouched · one bounded addition
- 08:24:03plc.write_setpoint({ tag: "FIL1.TARGET_WEIGHT", basis: "fill-weight+foam feedback" })
- 09:48:40ok pails on weight · no spills · labels verified
- 09:49:38mes.release_batch({ batch: "B-4471", genealogy: "full" })
- 09:50:36ok batch released · scenario complete
Reasoning trace
Goal, plan, thought, action, observation, exactly as the orchestrator would record it.
GoalDisperse batch B-4471 to Hegman fineness, let it down to visco…
Disperse batch B-4471 to Hegman fineness, let it down to viscosity spec, tint it inside Delta-E of standard STD-2210, filter and fill it to exact weight and release it with full genealogy.
PlanSimulate the whole batch on the twin first. Lead with fineness…
Simulate the whole batch on the twin first. Lead with fineness so the let-down gets the right mill base and the tint station gets the right color strength. Keep the customer tolerance and the VOC limit as hard constraints. Let the dispenser converge only inside the declared retint limit; hold anything beyond it for a human.
ThoughtThe standing practice grinds to a fixed time, lets down by fou…
The standing practice grinds to a fixed time, lets down by four additions and tints by draw-down loops. With live fineness and viscosity prediction and a spectral color-match model the batch can land on the first pass. The saving is rework, colorant and solvent, not tolerance: the customer standard is never a candidate for optimization.
Actiontwin.simulate(candidates=24) → path #9: Hegman on target in on…
twin.simulate(candidates=24) → path #9: Hegman on target in one grind, three let-down additions, one colorant pass, lowest predicted solvent and energy per batch, takt met.
ObservationPath #9 wants a second colorant addition beyond the declared r…
Path #9 wants a second colorant addition beyond the declared retint limit to tighten Delta-E further. The policy engine routes that single move to the shift color-matcher and permits the other seven writes.
ActionExecute path #9 at the bounded stage: mill energy, let-down do…
Execute path #9 at the bounded stage: mill energy, let-down dosing and the first colorant pass proceed; inspection runs continuously; the extra addition waits.
ObservationApproval granted at 08:24:02 with the tolerance untouched and …
Approval granted at 08:24:02 with the tolerance untouched and a tighter draw-down check. Two seeds were attributed to filter cartridge F-2 and Filter-and-Fill scheduled the change with a 40 second hold.
OutcomeScenario complete. The batch is released with raw-material lot…
Scenario complete. The batch is released with raw-material lots, grind profile, let-down moves, colorant additions, spectral curves, inspection outcomes, VOC and solvent use and the human decision in the genealogy. No measured plant result is claimed; this is the run the platform is designed to execute.
Autonomy
Four stages, set per loop
A plant does not go from manual to bounded control in one step. Tinteon makes the stage explicit per loop, auditable and reversible at any time, and some decisions never leave the person.
| Stage | What the agent does | What the person does | When |
|---|---|---|---|
| Shadow | Predicts fineness, viscosity, Delta-E, hiding power, contamination and fill faults; writes nothing | Runs the plant as today; compares predictions to the lab, the spectrophotometer and PLC outcomes | First phase with every design partner |
| Assist | Recommends bounded mill, let-down, colorant, filtration and fill moves with the evidence | A formulator, color-matcher or quality manager approves or rejects each one | After accuracy is proven against the baseline |
| Bounded | Writes low-risk dispersion, tinting and inspection setpoints inside documented formula, tolerance, VOC, equipment and rollback limits | Approves anything above the limits; reviews the shift record | After the quality and ROI gates agreed up front |
| Exceptions | Escalates anything outside its envelope, any move against a customer standard or VOC limit, and release decisions | Always decides these; the agent never does | Permanent |
Accelerated computing
Physical AI, at the plant edge
A tint station reads a draw-down in seconds and a filling line moves hundreds of pails an hour, so perception has to be local and fast. Tinteon runs GPU inference at the plant edge and keeps training, simulation and optimization in the cloud, in a private cloud or on-prem. Items marked planned are on the roadmap, not running.
Edge perception
8 to 24 camera and sensor streams per line through DeepStream pipelines and TensorRT color, gloss, hiding-power, contamination and fill models; Holoscan synchronizes spectrophotometers, line-scan cameras, inline rheology, mill power and fill-weight streams at the plant edge. Design target: 50 to 150 ms per frame.
Model serving
Vision, spectral, time-series and coatings-knowledge models behind one plant router, with version routing by product family, colorant system and line. Design target: sub-second recommendations for operators, sub-250 ms holds for filling and inspection.
Training (planned)
Spectral color-match, dispersion and fineness, rheology and contamination models fine-tuned on batch telemetry, images and supervised color-matcher corrections; NeMo-based coatings reasoning. Design target: 2,000 to 5,000 GPU-hours per major model family.
Digital twin (planned)
The Coatwin as-made batch twin: GPU-accelerated spectral color-match prediction and dispersion and rheology simulation run before the batch, for color and grade changes and batch planning when a trial is expensive. Design target: 10,000 to 100,000 scenarios per design partner.
Synthetic data (planned)
Rare off-color, seed, contamination, foam, label, hiding-power and fill-fault cases generated with domain randomization, marked synthetic and validated against real plant data before use.
Optimization
Color-family batching, wash and changeover minimization, solvent and energy allocation and filling-line takt, recomputed on the GPU daily and intra-shift when the plant is disrupted.
Data engineering
Batch-genealogy, quality, equipment and rework telemetry ETL for feature generation, color correlation and cross-plant benchmarks on the GPU.
Robotic handling
Drum, pail, tote and pallet handling, with perception and motion policies built and validated in simulation before they move a container.
Design targets
Product design targets
The numbers Tinteon is engineered against, from the GPU utilization plan.
50–150 ms
per-frame edge decision on color, hiding power, contamination and fill models
<250 ms
hold decision for filling and inspection actions
<1 s
recommendation latency for formulators and color-matchers
8–24
camera and sensor streams per dispersion, tinting or filling line
2,000–5,000
GPU-hours of initial training per major model family
10k–100k
simulated batch and fault scenarios per design partner
Design targets from the GPU utilization plan, all marked aspirational in the architecture. Nothing on this page is a measured plant result; measurements start when the first design-partner line runs in shadow mode.
From the plant floor
Who this is built for
The three people in a coatings plant whose week changes when the process runs itself, and what each of them needs from Tinteon.
Plant or Operations Director
Owns production rate, quality, rework and yield, waste, solvent and energy, and compliance. Wants a plant that holds color and spec at higher rate with fewer interventions, and a number that justifies the spend.
Formulation or Process Engineer and Color-Matcher
Owns formulas, dispersion, tint and color-match process windows and yield. Approves and corrects the agents in assist mode; those corrections train the models.
Quality or Compliance Manager
Owns product quality under ISO 9001 and customer color standards, color and contamination conformance, VOC and REACH compliance, and batch genealogy. Needs every action grounded, cited and written to an immutable record.
IT/OT and EHS leads approve the deployment. There are no customer quotes on this site yet; design partners will speak for themselves when they choose to.
Integrations
It speaks plant, not cloud
Tinteon reads and writes through the systems already on the floor. No parallel historian, no new HMI, no rip-and-replace. Connectors are built against each design partner's stack first; long-tail integrations are out of scope for the first release.
PLC and controls of dispersers, bead, basket and horizontal mills, with mill power, media temperature and residence telemetry
Setpoint reads, guarded writes, interlocks untouched
Tint dispensers and colorant dosing systems
Colorant additions inside declared retint and additive limits
Spectrophotometers, draw-down cameras and color-standard libraries
Spectral curves and Delta-E in; cited matches out
Inline rheometers and viscometers, temperature and solids sensors, LIMS results
Continuous viscosity and stability state
Filtration skids, filling lines, fill-weight scales, labelers
Telemetry in; fill-weight and hold commands inside approved windows
Multi-camera and spectral stations for color, gloss, hiding power, seeds, foam, fill and label faults
Frames, fault events, hold recommendations
Orders, formulas, color standards, product specs, batch genealogy
Targets in, release records out
Plant and asset meters, solvent and VOC accounting; Isaac-driven drum, pail and tote cells
Hard constraints for scheduling; bounded handling
Guardrails
An agent that can move a setpoint needs a leash
Tinteon writes to production equipment in a chemical plant. Every capability is scoped, every write is policy-checked, every output is cited, and every action is written to an append-only audit log the plant owns.
- Bounded action space. Each agent can only write to an explicit tag allow-list, inside per-tag rate, magnitude and retint limits, at the autonomy stage the plant has set.
- Standards and limits are read, never written. The customer color standard and its tolerance, the VOC and solvent limits under the plant's permit and the batch release decision stay with the quality system and the people who own it.
- Policy engine before every write. Autonomy stage, interlock state, product, formula, shift and operator presence are evaluated before a setpoint or a colorant addition moves.
- Grounded and cited. Every recommendation carries a citation to the formula, color standard, spec or procedure it relied on. Retrieval is tenant-isolated and permission-aware.
- Immutable audit log. Append-only, exportable and retained on the plant's own storage, aligned to ISO 9001, VOC and REACH and customer color-standard record-keeping.
- Hard fallback. If the edge node, the network or a model stops, the plant keeps running on its existing mill, dispenser and filling-line control and interlocks.
- Tenant and IP isolation. Formulas, color standards, raw-material data and tolerance models never cross a customer boundary. On-prem deployment available.
Assurance posture
| Item | Scope | Status |
|---|---|---|
| SOC 2 Type I | Cloud control plane | QUEUED Roadmap, first 6 months |
| SOC 2 Type II | Cloud control plane | QUEUED Roadmap, 6 to 12 months |
| ISO 9001 · VOC and REACH · customer color standards | Grounding and record-keeping | RUNNING Design basis for retrieval and the audit log |
| Per-tenant isolation | Data, memory, models | RUNNING Design rule |
| On-prem deployment | Formula-sensitive producers | RUNNING Design option |
Tinteon supports your quality and VOC records. It is not a certification and it does not replace your quality system or your permit.
Enterprise
Standardize autonomy across the group
One policy model, one audit trail and one set of yield, rework, waste, solvent, energy and color benchmarks across every plant in the group, with each site's formulas, color standards and tolerance models kept private to that site.
- Multi-site plant-edge fleet with shared model governance
- Custom formula, color and tolerance models per site
- SSO and role-based access, named approvers (roadmap, 6 to 12 months)
- Model versioning, validation reports and rollback
- On-prem or private-cloud deployment
- SLAs and outcome-based components on the highest-value workflows
FAQ
Straight answers
The questions plant directors, formulators, color-matchers and quality managers ask in the first meeting.
Only at the autonomy stage your plant has set, and only to an explicit allow-list of low-risk loops inside documented limits. Every design partner starts in shadow mode, where Tinteon predicts and writes nothing. Assist mode follows, where a formulator or color-matcher approves each recommendation. Bounded autonomy on dispersion, tinting and inspection loops comes after the quality and ROI gates agreed up front.
They are not optimization variables. The customer standard and its tolerance, the VOC and solvent limits under your permit and the batch release decision stay with your quality procedures and your people. Tinteon reads them, cites them and writes every reading to an immutable audit log attached to the batch genealogy. It is grounded in ISO 9001, VOC and REACH and customer color standards; it is not a certification and does not replace your quality system.
Tinteon sits above your existing automation as a supervisory layer. If it stops, the plant keeps running on its current mill, dispenser and filling-line control and the interlocks it already has. A Tinteon outage degrades the plant to the way it runs today, not to a stop.
The first phase is shadow mode on one line: Tinteon reads your spectrophotometer, mill and dispenser history, inline rheology, lab results and MES while you run the plant as usual, and we measure its predictions against your lab, your draw-downs and PLC outcomes. Recommendations start when accuracy is proven against that baseline, and improve as plant-specific history and color-matcher corrections accumulate.
Formulas, color standards, tolerance models and raw-material data are tenant-scoped and never used to train another customer's models. Retrieval is multi-tenant isolated and permission-aware. Cross-plant learning, where a customer opts in, is federated and IP-isolated. On-prem deployment is available for producers protecting sensitive formulas.
You are, the same as with any control strategy. That is why every write is policy-checked, bounded, logged and reversible, every output carries a citation to the formula, standard or procedure it relied on, and anything above your threshold waits for a named approver. The audit log records the request, the reasoning, the limits applied and the human decision.
As a design partner, on one line, with one hard metric: Delta-E first-time-right rate and retints, re-mills and mill energy, solvent per batch and viscosity variance, or contamination and fill rejects. We instrument the line in shadow mode, measure the baseline, move to assist mode when accuracy is proven, and expand only when the number holds.
Full multi-module autonomy across the whole plant, long-tail integrations beyond the design partners' stacks, and self-serve onboarding. The first release is one wedge workflow, its connectors, the agent loop with human checkpoints, the review console and the assurance-grade quality and VOC audit log.
Get started
Pick your first product
Most plants start with Tintra on a tint line or Dispex on a mill. Tell us which number you need to move.