Fleet of plant edges
Manage models, autonomy levels, and versions across every train in every site from one control plane.
Enterprise
One standard for every train, in every site.
For pharma networks and CDMOs running dozens of trains across continents: one control plane, one validation posture, one set of models that improve everywhere as each site corrects them.
$600k+typical land ACV
134%NRR target
24/7plant-edge operation
Enterprise
Built for multi-site pharma and CDMO networks
Multi-site deployment, plant-edge fleet management, custom route and crystallization models, validation support, and on-prem or hybrid installation with NVIDIA AI Enterprise.
Validation package
Qualification documentation, model version locks, and change-control artifacts your quality unit can review.
Outcome-linked pricing
Enterprise agreements can tie a component of fees to polymorph consistency, yield, or reprocessing reduction.
Dedicated engineering
Solutions engineers who speak crystallization, PAT, and GMP — not just software.
Fleet
Manage autonomy the way you manage recipes
A single control plane shows every plant-edge node, the model version it is running, its autonomy level, and its performance against the site baseline — with promotion and rollback under change control.
- Per-train autonomy configuration and audit
- Staged model promotion with shadow evaluation
- Cross-site performance benchmarking (opt-in)
- Central evidence export for inspections
Deployment
On-prem, hybrid, or air-gapped
Deploy on NVIDIA AI Enterprise inside your own infrastructure, or let us run the training and fleet plane while inference stays entirely at your plants. Your routes never leave your boundary.
- NVIDIA AI Enterprise supported deployment
- Air-gapped installations with offline model bundles
- Regional data residency for multinational networks
Engagement
How an enterprise rollout runs
Land narrow, prove the number, then expand under a network agreement.
- Weeks 0–4
Plant review & scoping
Walk the train, map the tag list and PAT stack, agree the pilot metric with manufacturing and quality.
- Weeks 4–12
Shadow campaign
Polymorra perceives and predicts alongside your chemists. Baseline and model performance established.
- Quarter 2
Assist mode
Recommendations approved by chemists. Corrections train the site model. Validation package assembled.
- Quarter 3+
Bounded autonomy & expansion
Qualified trains move to auto-control; the agreement expands to further trains and sites.
Accelerated computing
An NVIDIA-accelerated stack, from the train to the fleet
Perception at the edge, reasoning in the cloud, and a reactor-and-crystallizer twin in between.
Stack
Jetson at the train
Plant-edge inference per reactor or crystallizer train: PVM crystal-image models, FBRM feature extraction, Raman and NIR soft sensors, anomaly and safety classifiers. [ASPIRATIONAL]
Stack
TensorRT + Holoscan
Low-latency perception and sensor-stream preprocessing for in-situ imaging and PAT spectra inside validated control windows.
Stack
Triton + NIM
Route-specific polymorph, impurity, particle-size, endpoint, and batch-reasoning models served with validated version locks and rollback.
Stack
Omniverse + Cosmos
Reactor-and-crystallizer twin plus synthesis of rare crystallization faults — oiling-out, fouling, seed drift, wrong-polymorph nucleation. [ASPIRATIONAL]
Stack
RAPIDS + cuOpt
Telemetry ETL at campaign scale, plus scheduling, solvent recovery, and crystallization-profile optimization.
Stack
NeMo + DGX
Fine-tuned chemistry-process and batch-record reasoning trained on de-identified design-partner data and chemist corrections. [ASPIRATIONAL]
Plant-edge console
One screen for the batch that is running right now
Supersaturation, particle size distribution, predicted polymorph, impurity trajectory, and the next control move — with the evidence behind each number.
Polymorra plant-edge console showing live supersaturation, particle size distribution, predicted polymorphic form, and impurity trajectory for a running crystallization, with the recommended next control move.
Integrations
Connects to the systems already running your plant
Polymorra reads and writes through the reactor DCS, PAT instruments, crystallizer and isolation skids, historians, and MES you already validated.
Reactor control & DCS
Emerson DeltaVSiemens PCS 7Honeywell ExperionOPC UAModbus/TCP
PAT & analytics
Mettler-Toledo FBRMPVM in-situ imagingReactIREndress+Hauser RamanNIRHPLC / XRPD imports
Isolation & drying
Nutsche filter-dryersCentrifugesAgitated dryersConical millsMicronizers
MES, historian & quality
Körber PAS-XEmerson SyncadeOSIsoft PILIMSeBR / QMS exports
Trust & compliance
Validated for GMP manufacturing
Polymorra is engineered for regulated drug-substance production: grounded outputs, immutable audit trails, graduated autonomy, and validation documentation from day one.
21 CFR Part 11
Immutable, validated audit log for every agent perception, recommendation, and control action, with e-signature-ready review flows.
GMP / ICH Q7
Change control, validated model versioning, and deployment documentation designed for drug-substance manufacturing.
SOC 2
SOC 2 Type I in progress, Type II on the roadmap; SSO/RBAC, encryption in transit and at rest. [ASPIRATIONAL]
Route & IP protection
Per-tenant isolation of routes, recipes, spectra, and crystal images. No cross-tenant training. On-prem option.
Graduated autonomy
Shadow → assist → bounded auto-control. Every autonomy level is explicitly configured, bounded, and revocable.
Grounded outputs
Every recommendation cites the spectra, images, telemetry, SOP, or specification it was derived from.
Plant-edge first
Inference runs on-site so control loops survive network loss; cloud is for training, fleet, and analytics.
Human-in-the-loop
Chemist and QA checkpoints are first-class: approve, correct, or reject — and every correction trains the models.
Voices from the plant
What operators say
Composite quotes from design-partner discovery interviews. [PLACEHOLDER — to be replaced with named references post-pilot]
“The crystallization step is where our campaigns live or die. Seeing supersaturation, particle size, and predicted polymorph in one place — and having the profile adjust itself — is what we have wanted for twenty years.”
“We do not want another dashboard. We want the batch to come out right and the record to be reviewable by exception. That is the only pitch that gets past QA.”
“Tech transfer is our bottleneck. If the twin can predict the plant crystal from the lab crystal, that is worth more than the software costs.”
Pricing
Land on one train. Expand to the plant.
Pricing follows the value of the batch: per reactor or crystallizer train, per plant, or an enterprise agreement with outcome components.
Line
Manufacturers validating ROI on the wedge workflow.
$13,000
per reactor or crystallizer train / month
- Reaction-control, crystallization/polymorph-control, or PAT-sensing AI for one train
- Plant-edge runtime with validated model versioning
- Connectors for one DCS, one PAT stack, and one MES
- Review console for chemists and PAT engineers
- Part 11 audit trail from day one
Most popular
Plant
Scaling plants adopting the full autonomous loop.
$85,000
per plant / month
- React-and-charge + crystallize-and-seed agents
- Purity-and-polymorph PAT sensing across trains
- Isolate-and-dry plus flow-and-continuous optimization
- Batch-record review by exception
- Reactor-and-crystallizer digital twin
- Campaign scheduling and solvent-recovery optimization
Enterprise
CDMOs and pharma networks standardizing on Polymorra.
Custom
land $600k – $7M ACV
- Multi-site deployment and plant-edge fleet management
- Custom route, crystallization, and impurity models
- Validation support and qualification documentation
- On-prem or hybrid deployment with NVIDIA AI Enterprise
- SLAs, dedicated solutions engineering, and outcome pricing
Standardize the hardest step in your network.
Start with one crystallizer or reactor train. Prove polymorph, yield, and reprocessing ROI in a validation-friendly pilot. Then expand across the plant.