Real-time soft sensors
Titer, VCD, metabolites, glycosylation, charge variants, and aggregates, updated live.
Perception layer · titer & CQA sensing
Know the batch before the assay does.
Real-time titer and quality-attribute readings that land in seconds, not the hours or days offline analytics take.
Runs on Jetson Orin/Thor at the edge, DGX/HGX for training
The problem
The two numbers that matter arrive too late.
Biomanufacturers run blind on how much drug the culture is making and whether its critical quality attributes (glycosylation, charge variants, aggregates) are on spec. Those answers come from offline analytics that lag hours to days behind the living culture. By the time a lab result lands, the glycosylation has already shifted or the culture has already crashed, and the batch is a deviation or a reprocess.
PAT and Raman hardware already sit on the reactor. Turning their raw spectra into trustworthy, GMP-grade titer and CQA readings is a soft-sensing problem few facilities have solved.
What Titeon does
Validated soft sensors the rest of the platform acts on.
Titeon fuses in-line Raman, spectroscopy, microscopy, and process telemetry into soft sensors that predict titer, VCD, metabolites, glycosylation, charge variants, aggregates, and contamination risk in real time. It runs at the edge, so a drifting attribute raises an alarm in seconds, and every prediction carries a confidence and a traceable source for Part 11 review.
Multimodal fusion
In-line Raman, spectroscopy, and microscopy combined, with a confidence on every prediction.
Early warning
Contamination-risk and CQA-excursion alarms before the offline assay confirms them.
Part 11 traceability
Every reading sourced, versioned, and signed for review by exception.
Fits your stack
Connectors to PAT analyzers, bioreactor DCS, and MES.
The perception spine
Culteon, Purion, and Sentira all act on Titeon's readings.
- Multimodal soft-sensing across Raman, spectra, vision, and telemetry
- Glycosylation and charge-variant prediction grounded in molecule modeling
- Cell-imaging and turbidity vision for viability and contamination cues
- Synthetic augmentation of rare CQA-excursion spectra
Under the hood
Sensing that reads the culture as it lives.
Umetrics and SIMCA-class tools model offline. Titeon senses in real time at the edge and acts as the perception spine for a closed control loop. Its cross-site library of labeled spectra is the part point tools cannot build, and it is what lets the soft sensors generalize across cell lines.
Built on NVIDIA
GPU-essential from the analyzer to the model.
- Edge hardwareJetson Orin and Thor (IGX) run Raman, spectroscopy, and microscopy inference at 1 to 10 Hz next to the reactor.
- TrainingDGX and HGX train multimodal soft sensors over large spectra and image sets.
- LibrariesHoloscan, DeepStream, and TensorRT run the real-time sensor and vision pipelines. BioNeMo grounds the molecule-level CQA models. Cosmos and Omniverse Replicator synthesize rare excursion and contamination spectra.
- ServingTriton and NIM serve titer, VCD, and CQA models on site GPUs under NVIDIA AI Enterprise for auditable GMP inference.
Commercials
The lowest-friction way onto the floor.
- PricingBioseon Line module at $13,000 per bioreactor per month for titer and CQA sensing, bundled into the Site tier, with a premium tier for custom CQA models per molecule.
- Who buysQA, PAT, and CQA managers champion and approve. MSAT directors hold the budget.
- The moatA proprietary cross-site library of labeled Raman and PAT spectra paired with offline CQA outcomes, the exact dataset that lets soft sensors predict glycosylation before the assay.
- First deploymentIngest one PAT analyzer and DCS, ship titer and VCD soft sensors with confidence, then add glycosylation prediction on partner data. Sensing needs no write-back to controls, so it opens the facility.
Where it fits
Titeon perceives. Everything else acts on it.
Start with sensing.
Titeon writes nothing back to your controls, so it is the easiest module to prove. Point it at one analyzer and compare its readings against your offline results.