Platform

Perception at the line. Reasoning above it. Guardrails around both.

The Tinteon platform is a plant-edge inference runtime, a plant orchestrator with a policy engine, the Coatwin twin, and a cloud or on-prem training loop. Agents perceive from spectrophotometers, cameras, inline rheology, mill and dispenser PLCs, lab data and MES, predict fineness, viscosity, Delta-E, hiding power, contamination and fill faults, and act through guarded connectors.

Plant edge + cloud or on-premTen agents, one orchestratorAudit log from day one

run_scn_01 · agent graph · scenario 10 nodes · 1 approval gate
01 · orchestrator order.receive ✓ SUCCEEDED 02 · orchestrator twin.simulate ✓ SUCCEEDED 03 · dose_disperse disperse.mill ✓ SUCCEEDED 04 · letdown_thin letdown.thin ✓ SUCCEEDED 05 · tint_color tint.match ✓ SUCCEEDED 06 · defect_inspect inspect.spectral ✓ SUCCEEDED 07 · orchestrator approve.human ◆ APPROVAL 08 · filter_fill filter.fill ✓ SUCCEEDED 09 · robot_handling handle.palletize ✓ SUCCEEDED 10 · quality_conf release.genealogy ✓ SUCCEEDED

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.

Architecture

The loop, end to end

Perceive the raw material, mill base and batch; plan disperse, let-down, tint, fill and inspect; run with adaptive dispersion and tint control; sense and predict color, fineness, rheology and contamination; optimize yield, rework, waste, solvent, energy and takt; flag off-color and off-spec risk; log; retrain.

01 · Sense

Plant-edge ingestion

Spectrophotometers, line-scan and RGB cameras, inline rheology, mill and disperser controls, tint dispensers, filling scales, robots, MES and quality systems are normalized into one plant event bus at the edge, with DeepStream and Holoscan handling the high-rate streams.

02 · Infer

Edge models

Fine-tuned color, gloss, hiding-power and contamination vision and spectral color-match models, dispersion and fineness, tint-dosing and rheology models, plus time-series prognostics for mill, dispenser and filling equipment, served with TensorRT and Triton.

03 · Reason

Plant orchestrator

Retrieves formulas, color standards, quality specs and VOC rules with citations, asks the agents for recommendations, runs constraint checks, rehearses high-impact moves on Coatwin and applies the autonomy policy.

04 · Act and learn

Guarded write-back

Approved actions go back through OT connectors inside tag, rate, magnitude and retint limits. Every action and every formulator or color-matcher correction becomes a labeled event for the training loop.

Run timeline

A run is the unit of work

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
  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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. 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.

Tool calls

The agent shows its work

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.

tool-call stream · run_scn_01
  1. 05:40:02mes.read_order({ batch: "B-4471", product: "TB-DEEP-07", standard: "STD-2210" })
  2. 05:40:02ok formula locked · tolerance Delta-E v4 · VOC limit on product
  3. 05:40:03lab.read_results({ lot: "PIG-8831", test: "incoming pigment" })
  4. 05:40:03ok lot inside spec · accepted for dosing
  5. 05:40:04twin.simulate({ candidates: 24, horizon: "batch" })
  6. 05:40:45ok best path #9 · tolerance held · lowest solvent and energy per batch
  7. 05:40:46policy.evaluate({ plan: 9, stage: "bounded" })
  8. 05:40:46ok 7 writes permitted · 1 write requires human approval
  9. 05:40:47plc.write_setpoint({ tag: "MILL2.ENERGY", basis: "power+spectral" })
  10. 07:28:30ok Hegman on target · color strength on target · no re-mill
  11. 07:29:00viscosity.predict({ tank: "LD-3", basis: "inline rheology+solids" })
  12. 07:29:00ok two resin and one solvent addition predicted · stability clear
  13. 07:29:01plc.write_setpoint({ tag: "LD3.SOLVENT_DOSE", window: "formula" })
  14. 07:55:10ok viscosity on spec · no overshoot
  15. 07:56:00spectro.read_curve({ station: "TINT-2", standard: "STD-2210" })
  16. 07:56:01dispenser.write({ colorant: "B", basis: "spectral prediction", retint_limit: 1 })
  17. 08:10:12ok draw-down inside Delta-E tolerance · one retint remaining
  18. 08:10:13vision.stream({ cameras: 12, models: ["color_gloss", "hiding_power", "seed_foam", "fill_label"] })
  19. 08:21:48flag: seed · pail 0417 · attributed to filter cartridge F-2 loading
  20. 08:21:49defect.attribute({ event: "seed", cause: "filter.cartridge_F2" })
  21. 08:21:49ok filter_fill notified · cartridge change scheduled · fill held 40 s
  22. 08:21:52approval.request({ action: "retint.beyond_limit", reason: "tighter Delta-E on lowest-solvent path" })
  23. 08:24:02ok approved by the shift color-matcher · tolerance untouched · one bounded addition
  24. 08:24:03plc.write_setpoint({ tag: "FIL1.TARGET_WEIGHT", basis: "fill-weight+foam feedback" })
  25. 09:48:40ok pails on weight · no spills · labels verified
  26. 09:49:38mes.release_batch({ batch: "B-4471", genealogy: "full" })
  27. 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.

Plant edge

The edge node is the product

A draw-down is read in seconds, a filling line moves hundreds of pails an hour and the mills never stop, so Tinteon's inference runs beside the equipment and keeps working if the cloud does not.

  • Local inference. Color, hiding-power, contamination and fill decisions in 50 to 150 ms per frame and holds in under 250 ms, as design targets, on Jetson Orin or Thor and plant-edge GPU servers.
  • Deterministic stream fusion. DeepStream and Holoscan fuse 8 to 24 camera and sensor streams per line with spectrophotometer, inline rheology, mill-power and fill-weight telemetry.
  • Model routing. Triton and NIM serve vision, spectral, time-series and coatings-knowledge models under one plant router, routed by product family, colorant system and line. Design target: sub-second recommendations for operators.
  • Fails to existing control. If the node, the network or a model stops, the plant keeps running on its mill, dispenser and filling-line control and interlocks.
  • Tenant-scoped memory. Per-plant yield-and-color history and per-formulator and per-color-matcher corrections stay with the plant.

What runs where

Workloads by location
WorkloadWhere
Spectral and vision inspection, control inferenceLine edge
Orchestrator, policy engine, audit logPlant edge
Training and fine-tuningDGX/HGX, cloud or on-prem GPUs (planned)
Coatwin twin and color and rheology simulationOVX-class or cloud GPUs (planned)
Synthetic rare-fault generationGPU cloud (planned)
RAPIDS analytics, model governanceCloud or private cloud
Digital twin

As-made, not as-designed

Coatwin couples GPU-accelerated spectral color-match prediction and dispersion and rheology simulation with the live plant state, so a dispersion, let-down and tint path is rehearsed before raw materials, mill time and line hours are spent.

Before the run

Path and envelope search

Candidate paths are ranked on predicted Delta-E, fineness margin, viscosity, solvent use, energy and takt. Anything outside the customer tolerance or the VOC limit is discarded before it is ever proposed.

During the run

Setpoints for the agents

Optimized setpoints are handed to Dispex, Rheon and Tintra. Distilled surrogates run at the edge for on-line envelope checks.

After the run

Calibration

Twin-versus-actual drift is measured on every batch and recalibrates the simulation. Validated synthetic rare faults harden every model.

Coatwin in detail

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.

Jetson Orin / Thor · DeepStream · TensorRT · Holoscan

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.

Triton · NIM

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.

DGX / HGX · NeMo

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.

Omniverse · Modulus · OVX

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.

Cosmos · Omniverse Replicator

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.

cuOpt

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.

RAPIDS

Data engineering

Batch-genealogy, quality, equipment and rework telemetry ETL for feature generation, color correlation and cross-plant benchmarks on the GPU.

Isaac · Jetson

Robotic handling

Drum, pail, tote and pallet handling, with perception and motion policies built and validated in simulation before they move a container.

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.

Autonomy stages and the human role at each
StageWhat the agent doesWhat the person doesWhen
ShadowPredicts fineness, viscosity, Delta-E, hiding power, contamination and fill faults; writes nothingRuns the plant as today; compares predictions to the lab, the spectrophotometer and PLC outcomesFirst phase with every design partner
AssistRecommends bounded mill, let-down, colorant, filtration and fill moves with the evidenceA formulator, color-matcher or quality manager approves or rejects each oneAfter accuracy is proven against the baseline
BoundedWrites low-risk dispersion, tinting and inspection setpoints inside documented formula, tolerance, VOC, equipment and rollback limitsApproves anything above the limits; reviews the shift recordAfter the quality and ROI gates agreed up front
ExceptionsEscalates anything outside its envelope, any move against a customer standard or VOC limit, and release decisionsAlways decides these; the agent never doesPermanent
Multi-agent handoff

Agents negotiate, they do not collide

Two agents will want the same actuator. The orchestrator arbitrates on the run goal, with the customer color standard, the VOC limit and a clean fill above everything, and the handoff is logged like any other step.

Contested move: filter cartridge change on the filling line

  1. 01yield_takt.request(skip change) SUCCEEDED0.2 s

    Yield-and-Takt wants to defer the filter cartridge change to the shift break so the filling line stays on takt and the next color family starts on time.

  2. 02filter_fill.request(change now) SUCCEEDED0.2 s

    Filter-and-Fill requires the change now because inspection attributed two seeds to the loaded cartridge. Contamination in a released pail is a customer complaint.

  3. 03orchestrator.arbitrate SUCCEEDED0.4 s

    Product conformance outranks takt under every run goal. The cartridge change wins the actuator; the request to defer is logged with its score and the reason it lost.

  4. 04yield_takt.handoff(resequenced) SUCCEEDED80 s

    Yield-and-Takt recovers the schedule by pulling the next batch's wash earlier and moving a lighter color family ahead. Takt is met without filling through a loaded cartridge.

Arbitration rules

  • Run goal first. Every request is scored against the declared goal, not against the requesting agent's local objective.
  • Conformance outranks everything. The customer color standard, the VOC limit and a clean fill are never optimization variables. A contaminated or off-color pail is a complaint; a takt miss is a schedule.
  • Time-boxed ownership. An agent holds a contested actuator for a bounded window, then must re-justify.
  • Everything is logged. The losing request, the score and the reason all appear in the run record.
  • Deadlocks escalate to a human rather than resolving by timeout.

See the agent roster

Agent roster

Ten agents and an orchestrator

Each agent owns a stage of the plant, a bounded tool set and a measured outcome. They negotiate for shared actuators through the orchestrator, never directly. Seven ship inside the six products; two arrive with the Plant tier, and the knowledge agent has no write tools at all.

agent.dose_disperse

Dose-and-Disperse

Dosing, dispersion, milling, fineness, color development

Reads mill power, media temperature, residence time and spectral reflectance against the formula and holds mill energy, media load, temperature and residence at target, so the mill base reaches Hegman fineness and color strength on the first pass instead of being re-milled after a gauge check.

mill.read_telemetryfineness.predictplc.write_setpoint(mill.energy)

Design scope: fineness and color strength on target, no re-mill

Ships in: Dispex

agent.letdown_thin

Letdown-and-Thin

Let-down, thinning, solids, viscosity

Fuses inline rheology, temperature, solids and mix power to predict viscosity and rheological behavior, then controls let-down, thinning and solids inside the formula window to converge on spec with the fewest additions and the least solvent.

rheology.read_inlineviscosity.predictplc.write_setpoint(letdown.dose)

Design scope: viscosity on spec without overshoot, less solvent

Ships in: Rheon

agent.tint_color

Tint-and-Color

Tinting, colorant dosing, spectrophotometric color match, Delta-E

Takes the batch's spectral curve and the target standard, predicts the colorant additions that land inside Delta-E tolerance, sequences them under retint and additive limits and converges on the first pass, encoding the color-matcher's craft as a model that improves with every match.

spectro.read_curvecolorant.predict_dosedispenser.write(colorant)

Design scope: Delta-E inside tolerance first time, retint limits held

Ships in: Tintra

agent.filter_fill

Filter-and-Fill

Filtration, seeds and contamination, exact-weight filling

Controls filtration and filling to exact weight without foam, spills or contamination, coordinates filling holds with inline inspection and balances filling-line takt, so finished product leaves clean, on weight and labeled.

filler.read_telemetryplc.write_setpoint(fill.weight)inspect.hold

Design scope: exact fill weight, no contamination or fill faults

Ships in: Palleon

agent.defect_inspect

Defect-and-Inspect

Color, gloss, hiding power, fineness, contamination, fill and label faults

Fuses spectrophotometer, line-scan and RGB streams at the plant edge to score color, gloss, hiding power, fineness, seeds, foam and fill and label faults on every batch and container, flags off-color and off-spec risk early enough to hold or correct, and feeds each labeled fault back to the color, dispersion and rheology models.

vision.stream(cams)spectral.scoredefect.attribute

Design target: 50 to 150 ms per-frame decisions, sub-250 ms holds

Ships in: Specton

agent.quality_rheology

Quality-and-Rheology

Color, rheology, stability, batch quality

Predicts finished-batch color, rheology and stability across temperature and shear from the dispersion, let-down and tint outcomes, and proposes the formula and process moves that protect quality before the batch is released.

stability.predictspec.checkrecipe.propose

Design scope: color and rheology quality predicted before release

Ships in: Rheon

agent.yield_takt

Yield-and-Takt

Yield, rework, waste, solvent and VOC, energy, line balancing

Prices every candidate move in re-tints, re-mills, liters of solvent, kilograms of VOC and kilowatt-hours, sequences batches by color family and wash burden, places changeovers and balances the moving line so takt is met without starving the filling line.

cuopt.sequencesolvent.budgetenergy.budget

Design scope: yield up, rework, solvent and energy down

Ships in: Plant tier

agent.robot_handling

Robot-and-Handling

Drum, pail, tote and packaging handling

Drives drum, pail, tote and pallet handling and packaging with perception and motion policies validated in simulation first, inside safety zones, with audited actions and operator approval. It starts with constrained cells and does not claim plant-wide robotic labor.

isaac.policy(handling)robot.move(bounded)zone.check

Design scope: constrained handling cells, safety zones, approvals

Ships in: Palleon

agent.quality_conf

Quality-and-Conformance

Right-first-time, non-conformance, batch genealogy, traceability

Builds the batch genealogy: raw-material lots, grind profile, let-down moves, colorant additions, spectral curves, inspection outcomes, VOC and solvent use and every human decision, and gates release against the product spec, the customer color standard and the plant's quality procedures.

mes.release_batchgenealogy.writeaudit.write

Design scope: complete, immutable release records

Ships in: Plant tier

agent.coatings_knowledge

Coatings-Knowledge

Grounded formula, color-standard and procedure questions

Answers formulators', color-matchers' and quality managers' questions over formulas, color standards, ISO 9001 and customer quality specs, VOC and REACH rules and genealogy procedures, with a citation on every answer. It has no write tools and cannot act on the plant.

rag.retrieve(cited)answer.compose

Design rule: every answer cites a source; no write tools

Ships in: Every tier

agent.orchestrator · coordinates all ten

Plant Orchestrator

Planning, arbitration, human approval, twin rehearsal

Plans the run, rehearses high-impact moves on the Coatwin twin, arbitrates between agents that want the same actuator, enforces the autonomy stage per loop and routes anything above the site threshold to a named human. Grounds its reasoning in the plant's formulas, color standards and quality procedures through cited retrieval.

plan.composepolicy.evaluateapproval.requesttwin.simulate

Design rule: every write policy-checked, every output cited

Ships in: Every tier

Design targets

What the platform is engineered against

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.

Developers

Every action is a record

There is no SDK to download yet. What design partners get is the integration surface: connectors, an autonomy policy declared per loop, and an audit record for every reading, recommendation, write and approval. This is the shape of one record, illustrative.

What the surface gives you

  • Connectors to mill and disperser PLCs, tint dispensers, spectrophotometers, inline rheometers, filling lines, lab systems, MES, cameras and meters, with declared allow-lists and limits
  • An autonomy policy per loop: stage, tags, rate, magnitude and retint limits, named approvers
  • Citations on every recommendation to the formula, color standard, spec or procedure it relied on
  • Model versions named in every record, with rollback by version
  • Export of the audit log and batch genealogy to your quality system

What the docs cover Developer overview

audit record · illustrative
// one write, as the audit log would hold it
{
  "run": "run_scn_01",
  "step": "tint.match",
  "agent": "agent.tint_color",
  "stage": "bounded",
  "action": { "tool": "dispenser.write", "tag": "TINT2.COLORANT_B" },
  "limits": { "max_addition": "declared per colorant", "retints": "1 remaining" },
  "evidence": ["spectro.read_curve", "colorant.predict_dose"],
  "citation": "std:STD-2210 tolerance v4 §2",
  "policy": "permitted",
  "models": { "color_match": "versioned", "policy": "versioned" },
  "human": null,
  "outcome": "inside Delta-E tolerance · one retint remaining"
}
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.

Economic buyer

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.

Champion

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.

Approver

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.

Dispersion and milling

PLC and controls of dispersers, bead, basket and horizontal mills, with mill power, media temperature and residence telemetry

Setpoint reads, guarded writes, interlocks untouched

Tinting and dispensing

Tint dispensers and colorant dosing systems

Colorant additions inside declared retint and additive limits

Spectrophotometry and color management

Spectrophotometers, draw-down cameras and color-standard libraries

Spectral curves and Delta-E in; cited matches out

Inline rheology and lab

Inline rheometers and viscometers, temperature and solids sensors, LIMS results

Continuous viscosity and stability state

Filtration and filling

Filtration skids, filling lines, fill-weight scales, labelers

Telemetry in; fill-weight and hold commands inside approved windows

Inspection

Multi-camera and spectral stations for color, gloss, hiding power, seeds, foam, fill and label faults

Frames, fault events, hold recommendations

Coatings MES, formulation and traceability

Orders, formulas, color standards, product specs, batch genealogy

Targets in, release records out

Energy, solvent, robots

Plant and asset meters, solvent and VOC accounting; Isaac-driven drum, pail and tote cells

Hard constraints for scheduling; bounded handling

See all integrations

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

Assurance and certification status
ItemScopeStatus
SOC 2 Type ICloud control plane QUEUED Roadmap, first 6 months
SOC 2 Type IICloud control plane QUEUED Roadmap, 6 to 12 months
ISO 9001 · VOC and REACH · customer color standardsGrounding and record-keeping RUNNING Design basis for retrieval and the audit log
Per-tenant isolationData, memory, models RUNNING Design rule
On-prem deploymentFormula-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.

Read the security overview

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.

Talk to us Enterprise details

  • 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.

Get started

See the platform on your line

One line, one baseline, shadow mode first. We will show you the run record before anything is written.